sandbox/modWFarea.R
In USDAForestService/FIESTA: Forest Inventory Estimation and Analysis
#' West-Fest module - Generate population data for WF module.
#'
#' Generates population data for generating 'Westfall' Ratio2Size estimates.
#'
#' If variables are NULL, then it will prompt user to input variables.
#'
#' Necessary variables:\cr
#' \tabular{llll}{ \tab \bold{Data}
#' \tab \bold{Variable} \tab \bold{Description}\cr
#' \tab cond \tab cuniqueid \tab Unique identifier for each plot, to link to pltassgn (ex. PLT_CN).\cr \tab
#' \tab CONDID \tab Unique identifier of each condition on plot. Set CONDID=1,
#' if only 1 condition per plot.\cr
#' \tab \tab CONDPROP_UNADJ \tab Unadjusted proportion of condition on each plot. Set CONDPROP_UNADJ=1, if only 1
#' condition per plot.\cr
#' \tab \tab COND_STATUS_CD \tab Status of each forested condition on plot (i.e. accessible forest, nonforest, water, etc.)\cr \tab
#' \tab NF_COND_STATUS_CD \tab If ACI=TRUE. Status of each nonforest condition
#' on plot (i.e. accessible nonforest, nonsampled nonforest)\cr
#' \tab \tab SITECLCD \tab If landarea=TIMBERLAND. Measure of site productivity.\cr \tab
#' \tab RESERVCD \tab If landarea=TIMBERLAND. Reserved status.\cr
#'
#' \tab pltassgn \tab puniqueid \tab Unique identifier for each plot, to link
#' to cond (ex. CN).\cr
#' \tab \tab STATECD \tab Identifies state each plot is located in.\cr \tab \tab INVYR \tab Identifies inventory year of each
#' plot.\cr
#' \tab \tab PLOT_STATUS_CD \tab Status of each plot (i.e. sampled, nonsampled). If not included, all plots are assumed as sampled.\cr }
#'
#' For available reference tables: sort(unique(FIESTAutils::ref_codes$VARIABLE)) \cr
#'
#' @param WFpopdat List. Population data objects returned from modWFpop().
#' @param landarea String. The sample area filter for estimates ("ALL",
#' "FOREST", "TIMBERLAND"). If landarea=FOREST, filtered to COND_STATUS_CD =
#' 1; If landarea=TIMBERLAND, filtered to SITECLCD in(1:6) and RESERVCD = 0.
#' @param pcfilter String. A filter for plot or cond attributes (including
#' pltassgn). Must be R logical syntax.
#' @param rowvar String. Name of row domain variable in cond. If only one
#' domain, rowvar = domain variable. If more than one domain, include colvar.
#' If no domain, rowvar = NULL.
#' @param colvar String. Name of column domain variable in cond.
#' @param sumunits Logical. If TRUE, estimation units are summed and returned
#' in one table.
#' @param returntitle Logical. If TRUE, returns title(s) of the estimation
#' table(s).
#' @param savedata Logical. If TRUE, saves table(s) to outfolder.
#' @param table_opts List. See help(table_options()) for a list of
#' options.
#' @param title_opts List. See help(title_options()) for a list of options.
#' @param savedata_opts List. See help(savedata_options()) for a list
#' of options. Only used when savedata = TRUE.
#' @param gui Logical. If gui, user is prompted for parameters.
#' @param ... Parameters for modWFpop() if WFpopdat is NULL.
#' @return A list with estimates with percent sampling error for rowvar (and
#' colvar). If sumunits=TRUE or unitvar=NULL and colvar=NULL, one data frame
#' is returned. Otherwise, a list object is returned with the following
#' information. If savedata=TRUE, all data frames are written to outfolder.
#'
#' \item{est}{ Data frame. Area estimates, in area units (e.g., acres), by
#' rowvar, colvar (and estimation unit). If sumunits=TRUE or one estimation
#' unit and colvar=NULL, or allin1=TRUE, estimates and percent sampling error
#' are in one data frame. }
#' \item{pse}{ Data frame. Percent sampling errors (Confidence level 68%)
#' for estimates by rowvar and colvar (and estimation unit). }
#' \item{titlelst}{ List. If returntitle=TRUE a list with table title(s). The
#' list contains one title if est and pse are in the same table and two titles
#' if est and pse are in separate tables. Row and column tables are also included
#' in list. }
#' \item{raw}{ List. If rawdata=TRUE, a list including the processing data used
#' for estimation including: number of plots and conditions; stratification
#' information; and 1 to 8 tables with calculated values for table cells and
#' totals (See processing data below). }
#'
#' Raw data
#'
#' \item{plotsampcnt}{ Table. Number of plots by plot status (e.g., sampled
#' forest on plot, sampled nonforest, nonsampled). }
#' \item{condsampcnt}{ DF. Number of conditions by condition status
#' (forest land, nonforest land, noncensus water, census water, nonsampled). }
#' \item{unitarea}{ DF. Area by estimation unit. }
#' \item{expcondtab}{ DF. Condition-level area expansion factors. }
#' \item{domdat}{ DF. Final data table used for estimation. }
#'
#' \item{stratdat}{ Data frame. Strata information by estimation unit. }
#' \tabular{lll}{ \tab \bold{Variable} \tab \bold{Description} \cr
#' \tab unitvar \tab estimation unit \cr \tab strvar \tab stratum value \cr
#' \tab strwtvar \tab number of pixels by strata and estimation unit \cr
#' \tab n.strata \tab number of plots in strata (after totally nonsampled
#' plots removed) \cr
#' \tab n.total \tab number of plots for estimation unit \cr
#' \tab strwt \tab proportion of area (or plots) by strata and estimation
#' unit (strata weight) \cr \tab CONDPROP_UNADJ_SUM \tab summed condition
#' proportion by strata and estimation unit \cr
#' \tab CONDPROP_ADJFAC \tab adjusted condition proportion by strata after
#' nonresponse plots removed \cr
#' \tab AREA \tab total area for estimation unit \cr
#' \tab CONDPROP_ADJFAC \tab average area \cr }
#'
#' \item{processing data}{ Data frames. Separate data frames containing
#' calculated variables used in estimation process. The number of processing
#' tables depends on the input parameters. The tables include: total by
#' estimation unit (unit.totest); rowvar totals (unit.rowest), colvar totals,
#' if not NULL (unit.colvar); and a combination of rowvar and colvar, if colvar
#' is not NULL (unit.grpvar). If sumunits=TRUE, the raw data for the summed
#' estimation units are also included (totest, rowest, colest, grpest,
#' respectively). These tables do not included estimate proportions (nhat and
#' nhat.var).
#'
#' The data frames include the following information: \tabular{lll}{ \tab
#' \bold{Variable} \tab \bold{Description}\cr
#' \tab nhat \tab estimate proportion of land \cr
#' \tab nhat.var \tab variance estimate of estimated proportion of land \cr
#' \tab NBRPLT.gt0 \tab Number of non-zero plots used in estimates \cr
#' \tab AREA \tab total area for estimation unit \cr
#' \tab est \tab estimated area of land nhat*areavar \cr
#' \tab est.var \tab variance estimate of estimate acres of land
#' nhat.var*areavar^2 \cr
#' \tab est.se \tab standard error of estimated area of land sqrt(est.var) \cr
#' \tab est.cv \tab coefficient of variation of estimated area of land est.se/est
#' \cr \tab pse \tab percent sampling error of estimate est.cv*100 \cr
#' \tab CI99left \tab left tail of 99 percent confidence interval for
#' estimated area \cr
#' \tab CI99right \tab right tail of 99 percent confidence interval for
#' estimated area \cr
#' \tab CI95left \tab left tail of 95 percent confidence interval for
#' estimated area \cr
#' \tab CI95right \tab right tail of 95 percent confidence interval for
#' estimated area \cr
#' \tab CI67left \tab left tail of 67 percent confidence interval for
#' estimated area \cr
#' \tab CI67right \tab right tail of 67 percent confidence interval for
#' estimated area \cr } }
#'
#' savedata\cr
#' if savedata=TRUE...\cr
#' tables with estimate and percent standard error will be written as *csv
#' files to outfolder. if rawdata=TRUE, the rawdata will be output to the
#' outfolder in a folder named rawdata (if raw_fmt="csv") or a database in
#' the outfolder, if (raw_fmt != "csv").
#'
#' if outfn.pre is not null...\cr
#' a prefix is added to output files if raw_fmt = 'csv', prefix is added to
#' file names in rawdata folder if raw_fmt != 'csv', prefix is added to dsn name
#' @note
#'
#' ADJUSTMENT FACTOR:\cr The adjustment factor is necessary to account for
#' nonsampled conditions. It is calculated for each estimation unit by strata
#' by summing the unadjusted condition proportions (CONDPROP_UNADJ) and
#' dividing by the number of plots in the strata/estimation unit.
#'
#' If ACI=FALSE, only nonsampled forest conditions are accounted for in the
#' adjustment factor. \cr If ACI=TRUE, the nonsampled nonforest conditions are
#' removed as well and accounted for in adjustment factor. This is if you are
#' interested in estimates for all lands or nonforest lands in the
#' All-Condition-Inventory.
#'
#' STRATA:\cr Stratification is used to reduce variance in population estimates
#' by partitioning the population into homogenous classes (strata), such as
#' forest and nonforest. For stratified sampling methods, the strata sizes
#' (weights) must be either known or estimated. Remotely-sensed data is often
#' used to generate strata weights with proporation of pixels by strata. If
#' stratification is desired (strata=TRUE), the required data include: stratum
#' assignment for the center location of each plot, stored in either pltassgn
#' or cond; and a look-up table with the area or proportion of the total area
#' of each strata value by estimation unit, making sure the name of the strata
#' (and estimation unit) variable and values match the plot assignment name(s)
#' and value(s).
#'
#' sumunits:\cr An estimation unit is a population, or area of interest, with
#' known area and number of plots. Individual counties or combined
#' Super-counties are common estimation units for FIA. An estimation unit may
#' also be a subpopulation of a larger population (e.g., Counties within a
#' State). Subpopulations are mutually exclusive and independent within a
#' population, therefore estimated totals and variances are additive. For
#' example, State-level estimates are generated by summing estimates from all
#' subpopulations within the State (Bechtold and Patterson. 2005. Chapter 2).
#' Each plot must be assigned to only one estimation unit.
#'
#' If sumunits=TRUE, estimates are generated by estimation unit, summed
#' together, and returned as one estimate. If rawdata=TRUE, estimates by
#' individual estimation unit are also returned.
#'
#' If sumunits=FALSE, estimates are generated and returned by estimation unit
#' as one data frame. If savedata=TRUE, a separate file is written for each
#' estimation unit.
#'
#' stratcombine:\cr If TRUE and less than 2 plots in any one estimation unit,
#' all estimation units with 10 or less plots are combined. The current method
#' for combining is to group the estimation unit with less than 10 plots with
#' the estimation unit following in consecutive order (numeric or
#' alphabetical), restrained by survey unit (UNITCD) if included in dataset,
#' and continuing until the number of plots equals 10. If there are no
#' estimation units following in order, it is combined with the estimation unit
#' previous in order.
#'
#' rowlut/collut:\cr There are several objectives for including rowlut/collut
#' look-up tables: 1) to include descriptive names that match row/column codes
#' in the input table; 2) to use number codes that match row/column names in
#' the input table for ordering rows; 3) to add rows and/or columns with 0
#' values for consistency. No duplicate names are allowed.
#'
#' Include 2 columns in the table:\cr 1-the merging variable with same name as
#' the variable in the input merge table;\cr 2-the ordering or descriptive
#' variable.\cr If the ordering variable is the rowvar/colvar in the input
#' table and the descriptive variable is in rowlut/collut, set
#' row.orderby/col.orderby equal to rowvar/colvar. If the descriptive variable
#' is the rowvar/colvar in the input table, and the ordering code variable is
#' in rowlut/collut, set row.orderby/col.orderby equal to the variable name of
#' the code variable in rowlut/collut.
#' @author Tracey S. Frescino, Paul L. Patterson, Elizabeth A. Freeman
#' @references Scott, Charles T.; Bechtold, William A.; Reams, Gregory A.;
#' Smith, William D.; Westfall, James A.; Hansen, Mark H.; Moisen, Gretchen G.
#' 2005. Sample-based estimators used by the Forest Inventory and Analysis
#' national information management system. Gen. Tech. Rep. SRS-80. Asheville,
#' NC: U.S. Department of Agriculture, Forest Service, Southern Research
#' Station, p.53-77.
#' @keywords data
modWFarea <- function(WFpopdat,
landarea = "FOREST",
pcfilter = NULL,
rowvar = NULL,
colvar = NULL,
sumunits = TRUE,
returntitle = FALSE,
savedata = FALSE,
table_opts = NULL,
title_opts = NULL,
savedata_opts = NULL,
gui = FALSE,
...){
###################################################################################
## DESCRIPTION:
## Generates acre estimates by domain (and estimation unit)
###################################################################################
## CHECK GUI - IF NO ARGUMENTS SPECIFIED, ASSUME GUI=TRUE
if (nargs() == 0 && is.null(WFpopdat)) {
gui <- TRUE
}
## If gui.. set variables to NULL
if (gui) {
landarea=strvar=areavar=sumunits=adj=strata=getwt=cuniqueid=ACI=
puniqueid=savedata=addtitle=returntitle=rawdata=unitvar <- NULL
#if (!row.FIAname) row.FIAname <- NULL
#if (!col.FIAname) col.FIAname <- NULL
}
## INITIALIZE SETTINGS
esttype <- "AREA"
parameters <- FALSE
returnlst <- list()
rawdata <- TRUE
nonresp <- TRUE
## Set global variables
ONEUNIT=n.total=n.strata=strwt=TOTAL=
rawfolder=n.resp=n.nonresp=SUBPPROP_UNADJ=pmeasprop <- NULL
#estvar <- "CONDPROP_ADJ"
##################################################################
## CHECK PARAMETER NAMES
##################################################################
## Check input parameters
input.params <- names(as.list(match.call()))[-1]
formallst <- c(names(formals(modWFarea)),
names(formals(modWFpop)))
if (!all(input.params %in% formallst)) {
miss <- input.params[!input.params %in% formallst]
stop("invalid parameter: ", toString(miss))
}
## Check parameter lists
pcheck.params(input.params, table_opts=table_opts, title_opts=title_opts,
savedata_opts=savedata_opts)
## Set savedata defaults
savedata_defaults_list <- formals(savedata_options)[-length(formals(savedata_options))]
for (i in 1:length(savedata_defaults_list)) {
assign(names(savedata_defaults_list)[[i]], savedata_defaults_list[[i]])
}
## Set user-supplied savedata values
if (length(savedata_opts) > 0) {
if (!savedata) {
message("savedata=FALSE with savedata parameters... no data are saved")
}
for (i in 1:length(savedata_opts)) {
if (names(savedata_opts)[[i]] %in% names(savedata_defaults_list)) {
assign(names(savedata_opts)[[i]], savedata_opts[[i]])
} else {
stop(paste("Invalid parameter: ", names(savedata_opts)[[i]]))
}
}
}
## Set table defaults
table_defaults_list <- formals(table_options)[-length(formals(table_options))]
for (i in 1:length(table_defaults_list)) {
assign(names(table_defaults_list)[[i]], table_defaults_list[[i]])
}
## Set user-supplied table values
if (length(table_opts) > 0) {
for (i in 1:length(table_opts)) {
if (names(table_opts)[[i]] %in% names(table_defaults_list)) {
assign(names(table_opts)[[i]], table_opts[[i]])
} else {
stop(paste("Invalid parameter: ", names(table_opts)[[i]]))
}
}
}
## Set title defaults
title_defaults_list <- formals(title_options)[-length(formals(title_options))]
for (i in 1:length(title_defaults_list)) {
assign(names(title_defaults_list)[[i]], title_defaults_list[[i]])
}
## Set user-supplied title values
if (length(title_opts) > 0) {
for (i in 1:length(title_opts)) {
if (names(title_opts)[[i]] %in% names(title_defaults_list)) {
assign(names(title_opts)[[i]], title_opts[[i]])
} else {
stop(paste("Invalid parameter: ", names(title_opts)[[i]]))
}
}
}
##################################################################
## CHECK PARAMETER INPUTS
##################################################################
list.items <- c("condx", "pltcondx", "cuniqueid", "condid",
"ACI.filter", "unitarea", "unitvar", "stratalut", "strvar",
"plotsampcnt", "condsampcnt")
WFpopdat <- pcheck.object(WFpopdat, "WFpopdat", list.items=list.items)
if (is.null(WFpopdat)) return(NULL)
condx <- WFpopdat$condx
pltcondx <- WFpopdat$pltcondx
cuniqueid <- WFpopdat$cuniqueid
condid <- WFpopdat$condid
ACI.filter <- WFpopdat$ACI.filter
unitarea <- WFpopdat$unitarea
areavar <- WFpopdat$areavar
areaunits <- WFpopdat$areaunits
unitvar <- WFpopdat$unitvar
unitvars <- WFpopdat$unitvars
strata <- WFpopdat$strata
stratalut <- WFpopdat$stratalut
strvar <- WFpopdat$strvar
expcondtab <- WFpopdat$expcondtab
plotsampcnt <- WFpopdat$plotsampcnt
condsampcnt <- WFpopdat$condsampcnt
states <- WFpopdat$states
invyrs <- WFpopdat$invyrs
estvar.name <- WFpopdat$estvar.area
stratcombinelut <- WFpopdat$stratcombinelut
strwtvar <- WFpopdat$strwtvar
strunitvars <- c(unitvar, strvar)
strata <- WFpopdat$strata
P2POINTCNT <- WFpopdat$P2POINTCNT
if (nonresp) {
RHGlut <- WFpopdat$RHGlut
nonresplut <- WFpopdat$nonresplut
RHGlut[, P2POINTCNT := n.resp + n.nonresp]
strunitvarsRHG <- c(strunitvars, "RHG")
}
########################################
## Check area units
########################################
unitchk <- pcheck.areaunits(unitarea=unitarea, areavar=areavar,
areaunits=areaunits, metric=metric)
unitarea <- unitchk$unitarea
areavar <- unitchk$areavar
areaunits <- unitchk$outunits
if (is.null(key(unitarea))) {
setkeyv(unitarea, unitvar)
}
###################################################################################
## Check parameters and apply plot and condition filters
###################################################################################
estdat <- check.estdata(esttype=esttype, pltcondf=pltcondx,
cuniqueid=cuniqueid, condid=condid, sumunits=sumunits,
landarea=landarea, ACI.filter=ACI.filter, pcfilter=pcfilter,
allin1=allin1, estround=estround, pseround=pseround,
divideby=divideby, addtitle=addtitle, returntitle=returntitle,
rawdata=rawdata, rawonly=rawonly, savedata=savedata,
outfolder=outfolder, overwrite_dsn=overwrite_dsn,
overwrite_layer=overwrite_layer, outfn.pre=outfn.pre,
outfn.date=outfn.date, append_layer=append_layer,
raw_fmt=raw_fmt, raw_dsn=raw_dsn, gui=gui)
if (is.null(estdat)) return(NULL)
pltcondf <- estdat$pltcondf
cuniqueid <- estdat$cuniqueid
sumunits <- estdat$sumunits
landarea <- estdat$landarea
allin1 <- estdat$allin1
estround <- estdat$estround
pseround <- estdat$pseround
divideby <- estdat$divideby
addtitle <- estdat$addtitle
returntitle <- estdat$returntitle
rawdata <- estdat$rawdata
rawonly <- estdat$rawonly
savedata <- estdat$savedata
outfolder <- estdat$outfolder
overwrite_layer <- estdat$overwrite_layer
raw_fmt <- estdat$raw_fmt
raw_dsn <- estdat$raw_dsn
rawfolder <- estdat$rawfolder
if ("STATECD" %in% names(pltcondf)) {
states <- pcheck.states(sort(unique(pltcondf$STATECD)))
}
if ("INVYR" %in% names(pltcondf)) {
invyr <- sort(unique(pltcondf$INVYR))
}
###################################################################################
### Check row and column data
###################################################################################
rowcolinfo <- check.rowcol(gui=gui, esttype=esttype,
condf=pltcondf, cuniqueid=cuniqueid,
rowvar=rowvar, colvar=colvar,
row.FIAname=row.FIAname, col.FIAname=col.FIAname,
row.orderby=row.orderby, col.orderby=col.orderby,
row.add0=row.add0, col.add0=col.add0,
title.rowvar=title.rowvar, title.colvar=title.colvar,
rowlut=rowlut, collut=collut,
rowgrp=rowgrp, rowgrpnm=rowgrpnm, rowgrpord=rowgrpord,
landarea=landarea)
condf <- rowcolinfo$condf
uniquerow <- rowcolinfo$uniquerow
uniquecol <- rowcolinfo$uniquecol
domainlst <- rowcolinfo$domainlst
rowvar <- rowcolinfo$rowvar
colvar <- rowcolinfo$colvar
domain <- rowcolinfo$grpvar
row.orderby <- rowcolinfo$row.orderby
col.orderby <- rowcolinfo$col.orderby
row.add0 <- rowcolinfo$row.add0
col.add0 <- rowcolinfo$col.add0
title.rowvar <- rowcolinfo$title.rowvar
title.colvar <- rowcolinfo$title.colvar
rowgrpnm <- rowcolinfo$rowgrpnm
title.rowgrp <- rowcolinfo$title.rowgrp
grpvar <- rowcolinfo$grpvar
rm(rowcolinfo)
## Generate a uniquecol for estimation units
if (!sumunits && colvar == "NONE") {
uniquecol <- data.table(unitarea[[unitvar]])
setnames(uniquecol, unitvar)
uniquecol[[unitvar]] <- factor(uniquecol[[unitvar]])
}
#####################################################################################
### Get estimation data for area estimates
#####################################################################################
## Sum of measured proportions used for Ratio2Size denominator
pmeassubp <- condx[, list(SUBP_MEASPROP_UNADJ = sum(SUBPPROP_UNADJ)),
by=c(strunitvars, "RHG", cuniqueid)]
pmeassubp.name <- "SUBP_MEASPROP_UNADJ"
## Merge filtered condition data (condf) to all conditions (condx)
###################################################################################
setkeyv(condx, c(cuniqueid, condid))
setkeyv(condf, c(cuniqueid, condid))
cdomdat <- condx[condf]
###################################################################################
### Get titles for output tables
###################################################################################
alltitlelst <- check.titles(dat=cdomdat, esttype=esttype,
sumunits=sumunits, title.main=title.main, title.ref=title.ref,
title.rowvar=title.rowvar, title.rowgrp=title.rowgrp,
title.colvar=title.colvar, title.unitvar=title.unitvar,
title.filter=title.filter, title.unitsn=areaunits,
unitvar=unitvar, rowvar=rowvar, colvar=colvar,
addtitle=addtitle, returntitle=returntitle,
rawdata=rawdata, states=states, invyrs=invyrs,
landarea=landarea, pcfilter=pcfilter,
allin1=allin1, divideby=divideby, outfn.pre=outfn.pre)
title.unitvar <- alltitlelst$title.unitvar
title.est <- alltitlelst$title.est
title.pse <- alltitlelst$title.pse
title.estpse <- alltitlelst$title.estpse
title.ref <- alltitlelst$title.ref
outfn.estpse <- alltitlelst$outfn.estpse
outfn.param <- alltitlelst$outfn.param
if (rawdata) {
outfn.rawdat <- alltitlelst$outfn.rawdat
}
###################################################################################
## GENERATE ESTIMATES
###################################################################################
unit_totest=unit_rowest=unit_colest=unit_grpest=rowunit=totunit <- NULL
addtotal <- ifelse(rowvar == "TOTAL" || length(unique(condf[[rowvar]])) > 1, TRUE, FALSE)
strataRHG <- merge(stratalut, RHGlut)
message("getting estimates using WF...")
# if (addtotal) {
## Get total estimate and merge area
cdomdattot <- cdomdat[, lapply(.SD, sum, na.rm=TRUE),
by=c(strunitvarsRHG, cuniqueid, "TOTAL"), .SDcols=estvar.name]
unit_totest <- Ratio2Size(yn = estvar.name,
yd = pmeassubp.name,
ysum = cdomdattot,
dsum = pmeassubp,
esttype = esttype,
uniqueid = cuniqueid,
stratalut = stratalut,
RHGlut = RHGlut,
unitvar = unitvar,
strvar = strvar,
domain = "TOTAL")
tabs <- check.matchclass(unitarea, unit_totest, unitvar)
unitarea <- tabs$tab1
unit_totest <- tabs$tab2
setkeyv(unit_totest, unitvar)
unit_totest <- unit_totest[unitarea, nomatch=0]
if (totals) {
unit_totest <- getpse(unit_totest, areavar=areavar, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
} else {
unit_totest <- getpse(unit_totest, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
}
# }
## Get row estimate
if (rowvar != "TOTAL") {
cdomdatsum <- cdomdat[, lapply(.SD, sum, na.rm=TRUE),
by=c(strunitvarsRHG, cuniqueid, rowvar), .SDcols=estvar.name]
unit_rowest <- Ratio2Size(yn = estvar.name,
yd = pmeassubp.name,
ysum = cdomdatsum,
dsum = pmeassubp,
esttype = esttype,
uniqueid = cuniqueid,
stratalut = stratalut,
RHGlut = RHGlut,
unitvar = unitvar,
strvar = strvar,
domain = rowvar)
}
## Get column (and cell) estimate
if (colvar != "NONE") {
cdomdatsum <- cdomdat[, lapply(.SD, sum, na.rm=TRUE),
by=c(strunitvarsRHG, cuniqueid, colvar), .SDcols=estvar.name]
unit_colest <- Ratio2Size(yn = estvar.name,
yd = pmeassubp.name,
ysum = cdomdatsum,
dsum = pmeassubp,
esttype = esttype,
uniqueid = cuniqueid,
stratalut = stratalut,
RHGlut = RHGlut,
unitvar = unitvar,
strvar = strvar,
domain = colvar)
cdomdatsum <- cdomdat[, lapply(.SD, sum, na.rm=TRUE),
by=c(strunitvarsRHG, cuniqueid, grpvar), .SDcols=estvar.name]
unit_grpest <- Ratio2Size(yn = estvar.name,
yd = pmeassubp.name,
ysum = cdomdatsum,
dsum = pmeassubp,
esttype = esttype,
uniqueid = cuniqueid,
stratalut = stratalut,
RHGlut = RHGlut,
unitvar = unitvar,
strvar = strvar,
domain = grpvar)
}
###################################################################################
## Check add0 and Add area
###################################################################################
if (!sumunits && nrow(unitarea) > 1) col.add0 <- TRUE
if (!is.null(unit_rowest)) {
unit_rowest <- add0unit(x=unit_rowest, xvar=rowvar,
uniquex=uniquerow, unitvar=unitvar,
xvar.add0=row.add0)
tabs <- check.matchclass(unitarea, unit_rowest, unitvar)
unitarea <- tabs$tab1
unit_rowest <- tabs$tab2
if (!is.null(row.orderby) && row.orderby != "NONE") {
setorderv(unit_rowest, c(row.orderby))
}
setkeyv(unit_rowest, unitvar)
unit_rowest <- unit_rowest[unitarea, nomatch=0]
if (totals) {
unit_rowest <- getpse(unit_rowest, areavar=areavar, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
} else {
unit_rowest <- getpse(unit_rowest, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
}
setkeyv(unit_rowest, c(unitvar, rowvar))
}
if (!is.null(unit_colest)) {
unit_colest <- add0unit(x=unit_colest, xvar=colvar,
uniquex=uniquecol,unitvar=unitvar,
xvar.add0=col.add0)
tabs <- check.matchclass(unitarea, unit_colest, unitvar)
unitarea <- tabs$tab1
unit_colest <- tabs$tab2
if (!is.null(col.orderby) && col.orderby != "NONE") {
setorderv(unit_colest, c(col.orderby))
}
setkeyv(unit_colest, unitvar)
unit_colest <- unit_colest[unitarea, nomatch=0]
if (totals) {
unit_colest <- getpse(unit_colest, areavar=areavar, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
} else {
unit_colest <- getpse(unit_colest, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
}
setkeyv(unit_colest, c(unitvar, colvar))
}
if (!is.null(unit_grpest)) {
unit_grpest <- add0unit(x=unit_grpest, xvar=rowvar,
uniquex=uniquerow, unitvar=unitvar,
xvar.add0=row.add0, xvar2=colvar,
uniquex2=uniquecol, xvar2.add0=col.add0)
tabs <- check.matchclass(unitarea, unit_grpest, unitvar)
unitarea <- tabs$tab1
unit_grpest <- tabs$tab2
if (!is.null(row.orderby) && row.orderby != "NONE") {
if (!is.null(col.orderby) && col.orderby != "NONE") {
setorderv(unit_grpest, c(row.orderby, col.orderby))
} else {
setorderv(unit_grpest, c(row.orderby))
}
} else if (!is.null(col.orderby) && col.orderby != "NONE") {
setorderv(unit_grpest, c(col.orderby))
}
setkeyv(unit_grpest, unitvar)
unit_grpest <- unit_grpest[unitarea, nomatch=0]
if (totals) {
unit_grpest <- getpse(unit_grpest, areavar=areavar, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
} else {
unit_grpest <- getpse(unit_grpest, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
}
setkeyv(unit_grpest, c(unitvar, rowvar, colvar))
}
###################################################################################
## Get row and column totals for units if sumunits=FALSE
###################################################################################
## For sumunits=FALSE, get estimation unit totals
if (!sumunits && (length(unique(unitarea[[unitvar]])) > 1 && !is.null(grpvar))) {
## AGGREGATE UNIT stratalut FOR ROWVAR and GRAND TOTAL
stratalut2 <- data.table(stratalut, ONEUNIT=1)
strunitvars2 <- c("ONEUNIT", strvar)
stratalut2 <- stratalut2[, lapply(.SD, sum, na.rm=TRUE),
by=strunitvars2, .SDcols=c(strwtvar, "n.strata")]
stratalut2[, strwt:=prop.table(get(strwtvar)), by="ONEUNIT"]
stratalut2[, n.total := sum(n.strata)]
setkeyv(stratalut2, strunitvars2)
unitarea2 <- data.table(unitarea, ONEUNIT=1)
unitarea2 <- unitarea2[, lapply(.SD, sum, na.rm=TRUE), by="ONEUNIT",
.SDcols=areavar]
setkey(unitarea2, "ONEUNIT")
RHGlut2 <- data.table(RHGlut, ONEUNIT=1)
RHGlut2 <- RHGlut2[, lapply(.SD, sum, na.rm=TRUE),
by=strunitvars2, .SDcols=c("n.resp", "n.nonresp", "P2POINTCNT",
"n.totresp", "n.total", "RHG.strwt")]
setkeyv(RHGlut2, strunitvars2)
strataRHG2 <- merge(stratalut2, RHGlut2)
strunitvarsRHG2 <- c(strunitvars2, "RHG")
pmeasprop2 <- data.table(pmeasprop, ONEUNIT=1)
cdomdat[, ONEUNIT := 1]
## CALCULATE UNIT TOTALS FOR ROWVAR
cdomdatsum <- cdomdat[, lapply(.SD, sum, na.rm=TRUE),
by=c(strunitvarsRHG2, cuniqueid, rowvar), .SDcols=estvar.name]
rowunit <- Ratio2Size(yn = estvar.name,
yd = pmeassubp.name,
ysum = cdomdatsum,
dsum = pmeasprop2,
esttype = esttype,
uniqueid = cuniqueid,
stratalut = stratalut2,
RHGlut = RHGlut2,
unitvar = "ONEUNIT",
strvar = strvar,
domain = rowvar)
rowunit <- add0unit(x=rowunit, xvar=rowvar, uniquex=uniquerow,
unitvar="ONEUNIT", xvar.add0=row.add0)
tabs <- check.matchclass(unitarea2, rowunit, "ONEUNIT")
unitarea2 <- tabs$tab1
rowunit <- tabs$tab2
setkeyv(rowunit, "ONEUNIT")
rowunit <- rowunit[unitarea2, nomatch=0]
if (totals) {
rowunit <- getpse(rowunit, areavar=areavar, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
} else {
rowunit <- getpse(rowunit, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
}
setkeyv(rowunit, c("ONEUNIT", rowvar))
## CALCULATE GRAND TOTAL FOR ALL UNITS
cdomdatsum <- cdomdat[, lapply(.SD, sum, na.rm=TRUE),
by=c(strunitvarsRHG2, cuniqueid, "TOTAL"), .SDcols=estvar.name]
totunit <- Ratio2Size(yn = estvar.name,
yd = pmeassubp.name,
ysum = cdomdatsum,
dsum = pmeasprop2,
esttype = esttype,
uniqueid = cuniqueid,
stratalut = stratalut2,
RHGlut = RHGlut2,
unitvar = "ONEUNIT",
strvar = strvar,
domain = "TOTAL")
tabs <- check.matchclass(unitarea2, totunit, "ONEUNIT")
unitarea2 <- tabs$tab1
totunit <- tabs$tab2
setkeyv(totunit, "ONEUNIT")
totunit <- totunit[unitarea2, nomatch=0]
if (totals) {
totunit <- getpse(totunit, areavar=areavar, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
} else {
totunit <- getpse(totunit, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
}
}
###################################################################################
## GENERATE OUTPUT TABLES
###################################################################################
message("getting output...")
estnm <- "est"
tabs <- est.outtabs(esttype=esttype, sumunits=sumunits, areavar=areavar,
unitvar=unitvar, unitvars=unitvars, unit_totest=unit_totest,
unit_rowest=unit_rowest, unit_colest=unit_colest, unit_grpest=unit_grpest,
rowvar=rowvar, colvar=colvar, uniquerow=uniquerow, uniquecol=uniquecol,
rowgrp=rowgrp, rowgrpnm=rowgrpnm, rowunit=rowunit, totunit=totunit,
allin1=allin1, savedata=savedata, addtitle=addtitle, title.ref=title.ref,
title.rowvar=title.rowvar, title.colvar=title.colvar, title.rowgrp=title.rowgrp,
title.unitvar=title.unitvar, title.estpse=title.estpse, title.est=title.est,
title.pse=title.pse, rawdata=rawdata, rawonly=rawonly, outfn.estpse=outfn.estpse,
outfolder=outfolder, outfn.date=outfn.date, overwrite=overwrite_layer,
estnm=estnm, estround=estround, pseround=pseround, divideby=divideby,
returntitle=returntitle, estnull=estnull, psenull=psenull, raw.keep0=raw.keep0)
est2return <- tabs$tabest
pse2return <- tabs$tabpse
if (!is.null(est2return)) {
returnlst$est <- setDF(est2return)
}
if (!is.null(pse2return)) {
returnlst$pse <- setDF(pse2return)
}
if (returntitle) {
returnlst$titlelst <- alltitlelst
}
if (rawdata) {
rawdat <- tabs$rawdat
rawdat$domdat <- setDF(cdomdat)
if (savedata) {
if (!is.null(title.estpse)) {
title.raw <- paste(title.estpse, title.ref)
} else {
title.raw <- paste(title.est, title.ref, sep="; ")
}
for (i in 1:length(rawdat)) {
tabnm <- names(rawdat[i])
rawtab <- rawdat[[i]]
outfn.rawtab <- paste0(outfn.rawdat, "_", tabnm)
if (tabnm %in% c("plotsampcnt", "condsampcnt", "stratcombinelut")) {
write2csv(rawtab, outfolder=rawfolder, outfilenm=outfn.rawtab,
outfn.date=outfn.date, overwrite=overwrite_layer)
} else if (is.data.frame(rawtab)) {
if (raw_fmt != "csv") {
out_layer <- tabnm
} else {
out_layer <- outfn.rawtab
}
datExportData(rawtab,
savedata_opts=list(outfolder=rawfolder,
out_fmt=raw_fmt,
out_dsn=raw_dsn,
out_layer=out_layer,
overwrite_layer=overwrite_layer,
append_layer=append_layer,
add_layer=TRUE))
}
}
}
rawdat$module <- "WF"
rawdat$esttype <- esttype
rawdat$WFmethod <- ifelse(strata, "PS", "HT")
if (!is.null(rowvar)) rawdat$rowvar <- rowvar
if (!is.null(colvar)) rawdat$colvar <- colvar
rawdat$areaunits <- areaunits
returnlst$raw <- rawdat
}
if ("STATECD" %in% names(pltcondf)) {
returnlst$statecd <- sort(unique(pltcondf$STATECD))
}
if ("INVYR" %in% names(pltcondf)) {
returnlst$invyr <- sort(unique(pltcondf$INVYR))
}
return(returnlst)
}
USDAForestService/FIESTA documentation built on April 5, 2025, 4:13 a.m.
R Package Documentation
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#' West-Fest module - Generate population data for WF module.
#'
#' Generates population data for generating 'Westfall' Ratio2Size estimates.
#'
#' If variables are NULL, then it will prompt user to input variables.
#'
#' Necessary variables:\cr
#' \tabular{llll}{ \tab \bold{Data}
#' \tab \bold{Variable} \tab \bold{Description}\cr
#' \tab cond \tab cuniqueid \tab Unique identifier for each plot, to link to pltassgn (ex. PLT_CN).\cr \tab
#' \tab CONDID \tab Unique identifier of each condition on plot. Set CONDID=1,
#' if only 1 condition per plot.\cr
#' \tab \tab CONDPROP_UNADJ \tab Unadjusted proportion of condition on each plot. Set CONDPROP_UNADJ=1, if only 1
#' condition per plot.\cr
#' \tab \tab COND_STATUS_CD \tab Status of each forested condition on plot (i.e. accessible forest, nonforest, water, etc.)\cr \tab
#' \tab NF_COND_STATUS_CD \tab If ACI=TRUE. Status of each nonforest condition
#' on plot (i.e. accessible nonforest, nonsampled nonforest)\cr
#' \tab \tab SITECLCD \tab If landarea=TIMBERLAND. Measure of site productivity.\cr \tab
#' \tab RESERVCD \tab If landarea=TIMBERLAND. Reserved status.\cr
#'
#' \tab pltassgn \tab puniqueid \tab Unique identifier for each plot, to link
#' to cond (ex. CN).\cr
#' \tab \tab STATECD \tab Identifies state each plot is located in.\cr \tab \tab INVYR \tab Identifies inventory year of each
#' plot.\cr
#' \tab \tab PLOT_STATUS_CD \tab Status of each plot (i.e. sampled, nonsampled). If not included, all plots are assumed as sampled.\cr }
#'
#' For available reference tables: sort(unique(FIESTAutils::ref_codes$VARIABLE)) \cr
#'
#' @param WFpopdat List. Population data objects returned from modWFpop().
#' @param landarea String. The sample area filter for estimates ("ALL",
#' "FOREST", "TIMBERLAND"). If landarea=FOREST, filtered to COND_STATUS_CD =
#' 1; If landarea=TIMBERLAND, filtered to SITECLCD in(1:6) and RESERVCD = 0.
#' @param pcfilter String. A filter for plot or cond attributes (including
#' pltassgn). Must be R logical syntax.
#' @param rowvar String. Name of row domain variable in cond. If only one
#' domain, rowvar = domain variable. If more than one domain, include colvar.
#' If no domain, rowvar = NULL.
#' @param colvar String. Name of column domain variable in cond.
#' @param sumunits Logical. If TRUE, estimation units are summed and returned
#' in one table.
#' @param returntitle Logical. If TRUE, returns title(s) of the estimation
#' table(s).
#' @param savedata Logical. If TRUE, saves table(s) to outfolder.
#' @param table_opts List. See help(table_options()) for a list of
#' options.
#' @param title_opts List. See help(title_options()) for a list of options.
#' @param savedata_opts List. See help(savedata_options()) for a list
#' of options. Only used when savedata = TRUE.
#' @param gui Logical. If gui, user is prompted for parameters.
#' @param ... Parameters for modWFpop() if WFpopdat is NULL.
#' @return A list with estimates with percent sampling error for rowvar (and
#' colvar). If sumunits=TRUE or unitvar=NULL and colvar=NULL, one data frame
#' is returned. Otherwise, a list object is returned with the following
#' information. If savedata=TRUE, all data frames are written to outfolder.
#'
#' \item{est}{ Data frame. Area estimates, in area units (e.g., acres), by
#' rowvar, colvar (and estimation unit). If sumunits=TRUE or one estimation
#' unit and colvar=NULL, or allin1=TRUE, estimates and percent sampling error
#' are in one data frame. }
#' \item{pse}{ Data frame. Percent sampling errors (Confidence level 68%)
#' for estimates by rowvar and colvar (and estimation unit). }
#' \item{titlelst}{ List. If returntitle=TRUE a list with table title(s). The
#' list contains one title if est and pse are in the same table and two titles
#' if est and pse are in separate tables. Row and column tables are also included
#' in list. }
#' \item{raw}{ List. If rawdata=TRUE, a list including the processing data used
#' for estimation including: number of plots and conditions; stratification
#' information; and 1 to 8 tables with calculated values for table cells and
#' totals (See processing data below). }
#'
#' Raw data
#'
#' \item{plotsampcnt}{ Table. Number of plots by plot status (e.g., sampled
#' forest on plot, sampled nonforest, nonsampled). }
#' \item{condsampcnt}{ DF. Number of conditions by condition status
#' (forest land, nonforest land, noncensus water, census water, nonsampled). }
#' \item{unitarea}{ DF. Area by estimation unit. }
#' \item{expcondtab}{ DF. Condition-level area expansion factors. }
#' \item{domdat}{ DF. Final data table used for estimation. }
#'
#' \item{stratdat}{ Data frame. Strata information by estimation unit. }
#' \tabular{lll}{ \tab \bold{Variable} \tab \bold{Description} \cr
#' \tab unitvar \tab estimation unit \cr \tab strvar \tab stratum value \cr
#' \tab strwtvar \tab number of pixels by strata and estimation unit \cr
#' \tab n.strata \tab number of plots in strata (after totally nonsampled
#' plots removed) \cr
#' \tab n.total \tab number of plots for estimation unit \cr
#' \tab strwt \tab proportion of area (or plots) by strata and estimation
#' unit (strata weight) \cr \tab CONDPROP_UNADJ_SUM \tab summed condition
#' proportion by strata and estimation unit \cr
#' \tab CONDPROP_ADJFAC \tab adjusted condition proportion by strata after
#' nonresponse plots removed \cr
#' \tab AREA \tab total area for estimation unit \cr
#' \tab CONDPROP_ADJFAC \tab average area \cr }
#'
#' \item{processing data}{ Data frames. Separate data frames containing
#' calculated variables used in estimation process. The number of processing
#' tables depends on the input parameters. The tables include: total by
#' estimation unit (unit.totest); rowvar totals (unit.rowest), colvar totals,
#' if not NULL (unit.colvar); and a combination of rowvar and colvar, if colvar
#' is not NULL (unit.grpvar). If sumunits=TRUE, the raw data for the summed
#' estimation units are also included (totest, rowest, colest, grpest,
#' respectively). These tables do not included estimate proportions (nhat and
#' nhat.var).
#'
#' The data frames include the following information: \tabular{lll}{ \tab
#' \bold{Variable} \tab \bold{Description}\cr
#' \tab nhat \tab estimate proportion of land \cr
#' \tab nhat.var \tab variance estimate of estimated proportion of land \cr
#' \tab NBRPLT.gt0 \tab Number of non-zero plots used in estimates \cr
#' \tab AREA \tab total area for estimation unit \cr
#' \tab est \tab estimated area of land nhat*areavar \cr
#' \tab est.var \tab variance estimate of estimate acres of land
#' nhat.var*areavar^2 \cr
#' \tab est.se \tab standard error of estimated area of land sqrt(est.var) \cr
#' \tab est.cv \tab coefficient of variation of estimated area of land est.se/est
#' \cr \tab pse \tab percent sampling error of estimate est.cv*100 \cr
#' \tab CI99left \tab left tail of 99 percent confidence interval for
#' estimated area \cr
#' \tab CI99right \tab right tail of 99 percent confidence interval for
#' estimated area \cr
#' \tab CI95left \tab left tail of 95 percent confidence interval for
#' estimated area \cr
#' \tab CI95right \tab right tail of 95 percent confidence interval for
#' estimated area \cr
#' \tab CI67left \tab left tail of 67 percent confidence interval for
#' estimated area \cr
#' \tab CI67right \tab right tail of 67 percent confidence interval for
#' estimated area \cr } }
#'
#' savedata\cr
#' if savedata=TRUE...\cr
#' tables with estimate and percent standard error will be written as *csv
#' files to outfolder. if rawdata=TRUE, the rawdata will be output to the
#' outfolder in a folder named rawdata (if raw_fmt="csv") or a database in
#' the outfolder, if (raw_fmt != "csv").
#'
#' if outfn.pre is not null...\cr
#' a prefix is added to output files if raw_fmt = 'csv', prefix is added to
#' file names in rawdata folder if raw_fmt != 'csv', prefix is added to dsn name
#' @note
#'
#' ADJUSTMENT FACTOR:\cr The adjustment factor is necessary to account for
#' nonsampled conditions. It is calculated for each estimation unit by strata
#' by summing the unadjusted condition proportions (CONDPROP_UNADJ) and
#' dividing by the number of plots in the strata/estimation unit.
#'
#' If ACI=FALSE, only nonsampled forest conditions are accounted for in the
#' adjustment factor. \cr If ACI=TRUE, the nonsampled nonforest conditions are
#' removed as well and accounted for in adjustment factor. This is if you are
#' interested in estimates for all lands or nonforest lands in the
#' All-Condition-Inventory.
#'
#' STRATA:\cr Stratification is used to reduce variance in population estimates
#' by partitioning the population into homogenous classes (strata), such as
#' forest and nonforest. For stratified sampling methods, the strata sizes
#' (weights) must be either known or estimated. Remotely-sensed data is often
#' used to generate strata weights with proporation of pixels by strata. If
#' stratification is desired (strata=TRUE), the required data include: stratum
#' assignment for the center location of each plot, stored in either pltassgn
#' or cond; and a look-up table with the area or proportion of the total area
#' of each strata value by estimation unit, making sure the name of the strata
#' (and estimation unit) variable and values match the plot assignment name(s)
#' and value(s).
#'
#' sumunits:\cr An estimation unit is a population, or area of interest, with
#' known area and number of plots. Individual counties or combined
#' Super-counties are common estimation units for FIA. An estimation unit may
#' also be a subpopulation of a larger population (e.g., Counties within a
#' State). Subpopulations are mutually exclusive and independent within a
#' population, therefore estimated totals and variances are additive. For
#' example, State-level estimates are generated by summing estimates from all
#' subpopulations within the State (Bechtold and Patterson. 2005. Chapter 2).
#' Each plot must be assigned to only one estimation unit.
#'
#' If sumunits=TRUE, estimates are generated by estimation unit, summed
#' together, and returned as one estimate. If rawdata=TRUE, estimates by
#' individual estimation unit are also returned.
#'
#' If sumunits=FALSE, estimates are generated and returned by estimation unit
#' as one data frame. If savedata=TRUE, a separate file is written for each
#' estimation unit.
#'
#' stratcombine:\cr If TRUE and less than 2 plots in any one estimation unit,
#' all estimation units with 10 or less plots are combined. The current method
#' for combining is to group the estimation unit with less than 10 plots with
#' the estimation unit following in consecutive order (numeric or
#' alphabetical), restrained by survey unit (UNITCD) if included in dataset,
#' and continuing until the number of plots equals 10. If there are no
#' estimation units following in order, it is combined with the estimation unit
#' previous in order.
#'
#' rowlut/collut:\cr There are several objectives for including rowlut/collut
#' look-up tables: 1) to include descriptive names that match row/column codes
#' in the input table; 2) to use number codes that match row/column names in
#' the input table for ordering rows; 3) to add rows and/or columns with 0
#' values for consistency. No duplicate names are allowed.
#'
#' Include 2 columns in the table:\cr 1-the merging variable with same name as
#' the variable in the input merge table;\cr 2-the ordering or descriptive
#' variable.\cr If the ordering variable is the rowvar/colvar in the input
#' table and the descriptive variable is in rowlut/collut, set
#' row.orderby/col.orderby equal to rowvar/colvar. If the descriptive variable
#' is the rowvar/colvar in the input table, and the ordering code variable is
#' in rowlut/collut, set row.orderby/col.orderby equal to the variable name of
#' the code variable in rowlut/collut.
#' @author Tracey S. Frescino, Paul L. Patterson, Elizabeth A. Freeman
#' @references Scott, Charles T.; Bechtold, William A.; Reams, Gregory A.;
#' Smith, William D.; Westfall, James A.; Hansen, Mark H.; Moisen, Gretchen G.
#' 2005. Sample-based estimators used by the Forest Inventory and Analysis
#' national information management system. Gen. Tech. Rep. SRS-80. Asheville,
#' NC: U.S. Department of Agriculture, Forest Service, Southern Research
#' Station, p.53-77.
#' @keywords data
modWFarea <- function(WFpopdat,
landarea = "FOREST",
pcfilter = NULL,
rowvar = NULL,
colvar = NULL,
sumunits = TRUE,
returntitle = FALSE,
savedata = FALSE,
table_opts = NULL,
title_opts = NULL,
savedata_opts = NULL,
gui = FALSE,
...){
###################################################################################
## DESCRIPTION:
## Generates acre estimates by domain (and estimation unit)
###################################################################################
## CHECK GUI - IF NO ARGUMENTS SPECIFIED, ASSUME GUI=TRUE
if (nargs() == 0 && is.null(WFpopdat)) {
gui <- TRUE
}
## If gui.. set variables to NULL
if (gui) {
landarea=strvar=areavar=sumunits=adj=strata=getwt=cuniqueid=ACI=
puniqueid=savedata=addtitle=returntitle=rawdata=unitvar <- NULL
#if (!row.FIAname) row.FIAname <- NULL
#if (!col.FIAname) col.FIAname <- NULL
}
## INITIALIZE SETTINGS
esttype <- "AREA"
parameters <- FALSE
returnlst <- list()
rawdata <- TRUE
nonresp <- TRUE
## Set global variables
ONEUNIT=n.total=n.strata=strwt=TOTAL=
rawfolder=n.resp=n.nonresp=SUBPPROP_UNADJ=pmeasprop <- NULL
#estvar <- "CONDPROP_ADJ"
##################################################################
## CHECK PARAMETER NAMES
##################################################################
## Check input parameters
input.params <- names(as.list(match.call()))[-1]
formallst <- c(names(formals(modWFarea)),
names(formals(modWFpop)))
if (!all(input.params %in% formallst)) {
miss <- input.params[!input.params %in% formallst]
stop("invalid parameter: ", toString(miss))
}
## Check parameter lists
pcheck.params(input.params, table_opts=table_opts, title_opts=title_opts,
savedata_opts=savedata_opts)
## Set savedata defaults
savedata_defaults_list <- formals(savedata_options)[-length(formals(savedata_options))]
for (i in 1:length(savedata_defaults_list)) {
assign(names(savedata_defaults_list)[[i]], savedata_defaults_list[[i]])
}
## Set user-supplied savedata values
if (length(savedata_opts) > 0) {
if (!savedata) {
message("savedata=FALSE with savedata parameters... no data are saved")
}
for (i in 1:length(savedata_opts)) {
if (names(savedata_opts)[[i]] %in% names(savedata_defaults_list)) {
assign(names(savedata_opts)[[i]], savedata_opts[[i]])
} else {
stop(paste("Invalid parameter: ", names(savedata_opts)[[i]]))
}
}
}
## Set table defaults
table_defaults_list <- formals(table_options)[-length(formals(table_options))]
for (i in 1:length(table_defaults_list)) {
assign(names(table_defaults_list)[[i]], table_defaults_list[[i]])
}
## Set user-supplied table values
if (length(table_opts) > 0) {
for (i in 1:length(table_opts)) {
if (names(table_opts)[[i]] %in% names(table_defaults_list)) {
assign(names(table_opts)[[i]], table_opts[[i]])
} else {
stop(paste("Invalid parameter: ", names(table_opts)[[i]]))
}
}
}
## Set title defaults
title_defaults_list <- formals(title_options)[-length(formals(title_options))]
for (i in 1:length(title_defaults_list)) {
assign(names(title_defaults_list)[[i]], title_defaults_list[[i]])
}
## Set user-supplied title values
if (length(title_opts) > 0) {
for (i in 1:length(title_opts)) {
if (names(title_opts)[[i]] %in% names(title_defaults_list)) {
assign(names(title_opts)[[i]], title_opts[[i]])
} else {
stop(paste("Invalid parameter: ", names(title_opts)[[i]]))
}
}
}
##################################################################
## CHECK PARAMETER INPUTS
##################################################################
list.items <- c("condx", "pltcondx", "cuniqueid", "condid",
"ACI.filter", "unitarea", "unitvar", "stratalut", "strvar",
"plotsampcnt", "condsampcnt")
WFpopdat <- pcheck.object(WFpopdat, "WFpopdat", list.items=list.items)
if (is.null(WFpopdat)) return(NULL)
condx <- WFpopdat$condx
pltcondx <- WFpopdat$pltcondx
cuniqueid <- WFpopdat$cuniqueid
condid <- WFpopdat$condid
ACI.filter <- WFpopdat$ACI.filter
unitarea <- WFpopdat$unitarea
areavar <- WFpopdat$areavar
areaunits <- WFpopdat$areaunits
unitvar <- WFpopdat$unitvar
unitvars <- WFpopdat$unitvars
strata <- WFpopdat$strata
stratalut <- WFpopdat$stratalut
strvar <- WFpopdat$strvar
expcondtab <- WFpopdat$expcondtab
plotsampcnt <- WFpopdat$plotsampcnt
condsampcnt <- WFpopdat$condsampcnt
states <- WFpopdat$states
invyrs <- WFpopdat$invyrs
estvar.name <- WFpopdat$estvar.area
stratcombinelut <- WFpopdat$stratcombinelut
strwtvar <- WFpopdat$strwtvar
strunitvars <- c(unitvar, strvar)
strata <- WFpopdat$strata
P2POINTCNT <- WFpopdat$P2POINTCNT
if (nonresp) {
RHGlut <- WFpopdat$RHGlut
nonresplut <- WFpopdat$nonresplut
RHGlut[, P2POINTCNT := n.resp + n.nonresp]
strunitvarsRHG <- c(strunitvars, "RHG")
}
########################################
## Check area units
########################################
unitchk <- pcheck.areaunits(unitarea=unitarea, areavar=areavar,
areaunits=areaunits, metric=metric)
unitarea <- unitchk$unitarea
areavar <- unitchk$areavar
areaunits <- unitchk$outunits
if (is.null(key(unitarea))) {
setkeyv(unitarea, unitvar)
}
###################################################################################
## Check parameters and apply plot and condition filters
###################################################################################
estdat <- check.estdata(esttype=esttype, pltcondf=pltcondx,
cuniqueid=cuniqueid, condid=condid, sumunits=sumunits,
landarea=landarea, ACI.filter=ACI.filter, pcfilter=pcfilter,
allin1=allin1, estround=estround, pseround=pseround,
divideby=divideby, addtitle=addtitle, returntitle=returntitle,
rawdata=rawdata, rawonly=rawonly, savedata=savedata,
outfolder=outfolder, overwrite_dsn=overwrite_dsn,
overwrite_layer=overwrite_layer, outfn.pre=outfn.pre,
outfn.date=outfn.date, append_layer=append_layer,
raw_fmt=raw_fmt, raw_dsn=raw_dsn, gui=gui)
if (is.null(estdat)) return(NULL)
pltcondf <- estdat$pltcondf
cuniqueid <- estdat$cuniqueid
sumunits <- estdat$sumunits
landarea <- estdat$landarea
allin1 <- estdat$allin1
estround <- estdat$estround
pseround <- estdat$pseround
divideby <- estdat$divideby
addtitle <- estdat$addtitle
returntitle <- estdat$returntitle
rawdata <- estdat$rawdata
rawonly <- estdat$rawonly
savedata <- estdat$savedata
outfolder <- estdat$outfolder
overwrite_layer <- estdat$overwrite_layer
raw_fmt <- estdat$raw_fmt
raw_dsn <- estdat$raw_dsn
rawfolder <- estdat$rawfolder
if ("STATECD" %in% names(pltcondf)) {
states <- pcheck.states(sort(unique(pltcondf$STATECD)))
}
if ("INVYR" %in% names(pltcondf)) {
invyr <- sort(unique(pltcondf$INVYR))
}
###################################################################################
### Check row and column data
###################################################################################
rowcolinfo <- check.rowcol(gui=gui, esttype=esttype,
condf=pltcondf, cuniqueid=cuniqueid,
rowvar=rowvar, colvar=colvar,
row.FIAname=row.FIAname, col.FIAname=col.FIAname,
row.orderby=row.orderby, col.orderby=col.orderby,
row.add0=row.add0, col.add0=col.add0,
title.rowvar=title.rowvar, title.colvar=title.colvar,
rowlut=rowlut, collut=collut,
rowgrp=rowgrp, rowgrpnm=rowgrpnm, rowgrpord=rowgrpord,
landarea=landarea)
condf <- rowcolinfo$condf
uniquerow <- rowcolinfo$uniquerow
uniquecol <- rowcolinfo$uniquecol
domainlst <- rowcolinfo$domainlst
rowvar <- rowcolinfo$rowvar
colvar <- rowcolinfo$colvar
domain <- rowcolinfo$grpvar
row.orderby <- rowcolinfo$row.orderby
col.orderby <- rowcolinfo$col.orderby
row.add0 <- rowcolinfo$row.add0
col.add0 <- rowcolinfo$col.add0
title.rowvar <- rowcolinfo$title.rowvar
title.colvar <- rowcolinfo$title.colvar
rowgrpnm <- rowcolinfo$rowgrpnm
title.rowgrp <- rowcolinfo$title.rowgrp
grpvar <- rowcolinfo$grpvar
rm(rowcolinfo)
## Generate a uniquecol for estimation units
if (!sumunits && colvar == "NONE") {
uniquecol <- data.table(unitarea[[unitvar]])
setnames(uniquecol, unitvar)
uniquecol[[unitvar]] <- factor(uniquecol[[unitvar]])
}
#####################################################################################
### Get estimation data for area estimates
#####################################################################################
## Sum of measured proportions used for Ratio2Size denominator
pmeassubp <- condx[, list(SUBP_MEASPROP_UNADJ = sum(SUBPPROP_UNADJ)),
by=c(strunitvars, "RHG", cuniqueid)]
pmeassubp.name <- "SUBP_MEASPROP_UNADJ"
## Merge filtered condition data (condf) to all conditions (condx)
###################################################################################
setkeyv(condx, c(cuniqueid, condid))
setkeyv(condf, c(cuniqueid, condid))
cdomdat <- condx[condf]
###################################################################################
### Get titles for output tables
###################################################################################
alltitlelst <- check.titles(dat=cdomdat, esttype=esttype,
sumunits=sumunits, title.main=title.main, title.ref=title.ref,
title.rowvar=title.rowvar, title.rowgrp=title.rowgrp,
title.colvar=title.colvar, title.unitvar=title.unitvar,
title.filter=title.filter, title.unitsn=areaunits,
unitvar=unitvar, rowvar=rowvar, colvar=colvar,
addtitle=addtitle, returntitle=returntitle,
rawdata=rawdata, states=states, invyrs=invyrs,
landarea=landarea, pcfilter=pcfilter,
allin1=allin1, divideby=divideby, outfn.pre=outfn.pre)
title.unitvar <- alltitlelst$title.unitvar
title.est <- alltitlelst$title.est
title.pse <- alltitlelst$title.pse
title.estpse <- alltitlelst$title.estpse
title.ref <- alltitlelst$title.ref
outfn.estpse <- alltitlelst$outfn.estpse
outfn.param <- alltitlelst$outfn.param
if (rawdata) {
outfn.rawdat <- alltitlelst$outfn.rawdat
}
###################################################################################
## GENERATE ESTIMATES
###################################################################################
unit_totest=unit_rowest=unit_colest=unit_grpest=rowunit=totunit <- NULL
addtotal <- ifelse(rowvar == "TOTAL" || length(unique(condf[[rowvar]])) > 1, TRUE, FALSE)
strataRHG <- merge(stratalut, RHGlut)
message("getting estimates using WF...")
# if (addtotal) {
## Get total estimate and merge area
cdomdattot <- cdomdat[, lapply(.SD, sum, na.rm=TRUE),
by=c(strunitvarsRHG, cuniqueid, "TOTAL"), .SDcols=estvar.name]
unit_totest <- Ratio2Size(yn = estvar.name,
yd = pmeassubp.name,
ysum = cdomdattot,
dsum = pmeassubp,
esttype = esttype,
uniqueid = cuniqueid,
stratalut = stratalut,
RHGlut = RHGlut,
unitvar = unitvar,
strvar = strvar,
domain = "TOTAL")
tabs <- check.matchclass(unitarea, unit_totest, unitvar)
unitarea <- tabs$tab1
unit_totest <- tabs$tab2
setkeyv(unit_totest, unitvar)
unit_totest <- unit_totest[unitarea, nomatch=0]
if (totals) {
unit_totest <- getpse(unit_totest, areavar=areavar, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
} else {
unit_totest <- getpse(unit_totest, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
}
# }
## Get row estimate
if (rowvar != "TOTAL") {
cdomdatsum <- cdomdat[, lapply(.SD, sum, na.rm=TRUE),
by=c(strunitvarsRHG, cuniqueid, rowvar), .SDcols=estvar.name]
unit_rowest <- Ratio2Size(yn = estvar.name,
yd = pmeassubp.name,
ysum = cdomdatsum,
dsum = pmeassubp,
esttype = esttype,
uniqueid = cuniqueid,
stratalut = stratalut,
RHGlut = RHGlut,
unitvar = unitvar,
strvar = strvar,
domain = rowvar)
}
## Get column (and cell) estimate
if (colvar != "NONE") {
cdomdatsum <- cdomdat[, lapply(.SD, sum, na.rm=TRUE),
by=c(strunitvarsRHG, cuniqueid, colvar), .SDcols=estvar.name]
unit_colest <- Ratio2Size(yn = estvar.name,
yd = pmeassubp.name,
ysum = cdomdatsum,
dsum = pmeassubp,
esttype = esttype,
uniqueid = cuniqueid,
stratalut = stratalut,
RHGlut = RHGlut,
unitvar = unitvar,
strvar = strvar,
domain = colvar)
cdomdatsum <- cdomdat[, lapply(.SD, sum, na.rm=TRUE),
by=c(strunitvarsRHG, cuniqueid, grpvar), .SDcols=estvar.name]
unit_grpest <- Ratio2Size(yn = estvar.name,
yd = pmeassubp.name,
ysum = cdomdatsum,
dsum = pmeassubp,
esttype = esttype,
uniqueid = cuniqueid,
stratalut = stratalut,
RHGlut = RHGlut,
unitvar = unitvar,
strvar = strvar,
domain = grpvar)
}
###################################################################################
## Check add0 and Add area
###################################################################################
if (!sumunits && nrow(unitarea) > 1) col.add0 <- TRUE
if (!is.null(unit_rowest)) {
unit_rowest <- add0unit(x=unit_rowest, xvar=rowvar,
uniquex=uniquerow, unitvar=unitvar,
xvar.add0=row.add0)
tabs <- check.matchclass(unitarea, unit_rowest, unitvar)
unitarea <- tabs$tab1
unit_rowest <- tabs$tab2
if (!is.null(row.orderby) && row.orderby != "NONE") {
setorderv(unit_rowest, c(row.orderby))
}
setkeyv(unit_rowest, unitvar)
unit_rowest <- unit_rowest[unitarea, nomatch=0]
if (totals) {
unit_rowest <- getpse(unit_rowest, areavar=areavar, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
} else {
unit_rowest <- getpse(unit_rowest, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
}
setkeyv(unit_rowest, c(unitvar, rowvar))
}
if (!is.null(unit_colest)) {
unit_colest <- add0unit(x=unit_colest, xvar=colvar,
uniquex=uniquecol,unitvar=unitvar,
xvar.add0=col.add0)
tabs <- check.matchclass(unitarea, unit_colest, unitvar)
unitarea <- tabs$tab1
unit_colest <- tabs$tab2
if (!is.null(col.orderby) && col.orderby != "NONE") {
setorderv(unit_colest, c(col.orderby))
}
setkeyv(unit_colest, unitvar)
unit_colest <- unit_colest[unitarea, nomatch=0]
if (totals) {
unit_colest <- getpse(unit_colest, areavar=areavar, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
} else {
unit_colest <- getpse(unit_colest, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
}
setkeyv(unit_colest, c(unitvar, colvar))
}
if (!is.null(unit_grpest)) {
unit_grpest <- add0unit(x=unit_grpest, xvar=rowvar,
uniquex=uniquerow, unitvar=unitvar,
xvar.add0=row.add0, xvar2=colvar,
uniquex2=uniquecol, xvar2.add0=col.add0)
tabs <- check.matchclass(unitarea, unit_grpest, unitvar)
unitarea <- tabs$tab1
unit_grpest <- tabs$tab2
if (!is.null(row.orderby) && row.orderby != "NONE") {
if (!is.null(col.orderby) && col.orderby != "NONE") {
setorderv(unit_grpest, c(row.orderby, col.orderby))
} else {
setorderv(unit_grpest, c(row.orderby))
}
} else if (!is.null(col.orderby) && col.orderby != "NONE") {
setorderv(unit_grpest, c(col.orderby))
}
setkeyv(unit_grpest, unitvar)
unit_grpest <- unit_grpest[unitarea, nomatch=0]
if (totals) {
unit_grpest <- getpse(unit_grpest, areavar=areavar, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
} else {
unit_grpest <- getpse(unit_grpest, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
}
setkeyv(unit_grpest, c(unitvar, rowvar, colvar))
}
###################################################################################
## Get row and column totals for units if sumunits=FALSE
###################################################################################
## For sumunits=FALSE, get estimation unit totals
if (!sumunits && (length(unique(unitarea[[unitvar]])) > 1 && !is.null(grpvar))) {
## AGGREGATE UNIT stratalut FOR ROWVAR and GRAND TOTAL
stratalut2 <- data.table(stratalut, ONEUNIT=1)
strunitvars2 <- c("ONEUNIT", strvar)
stratalut2 <- stratalut2[, lapply(.SD, sum, na.rm=TRUE),
by=strunitvars2, .SDcols=c(strwtvar, "n.strata")]
stratalut2[, strwt:=prop.table(get(strwtvar)), by="ONEUNIT"]
stratalut2[, n.total := sum(n.strata)]
setkeyv(stratalut2, strunitvars2)
unitarea2 <- data.table(unitarea, ONEUNIT=1)
unitarea2 <- unitarea2[, lapply(.SD, sum, na.rm=TRUE), by="ONEUNIT",
.SDcols=areavar]
setkey(unitarea2, "ONEUNIT")
RHGlut2 <- data.table(RHGlut, ONEUNIT=1)
RHGlut2 <- RHGlut2[, lapply(.SD, sum, na.rm=TRUE),
by=strunitvars2, .SDcols=c("n.resp", "n.nonresp", "P2POINTCNT",
"n.totresp", "n.total", "RHG.strwt")]
setkeyv(RHGlut2, strunitvars2)
strataRHG2 <- merge(stratalut2, RHGlut2)
strunitvarsRHG2 <- c(strunitvars2, "RHG")
pmeasprop2 <- data.table(pmeasprop, ONEUNIT=1)
cdomdat[, ONEUNIT := 1]
## CALCULATE UNIT TOTALS FOR ROWVAR
cdomdatsum <- cdomdat[, lapply(.SD, sum, na.rm=TRUE),
by=c(strunitvarsRHG2, cuniqueid, rowvar), .SDcols=estvar.name]
rowunit <- Ratio2Size(yn = estvar.name,
yd = pmeassubp.name,
ysum = cdomdatsum,
dsum = pmeasprop2,
esttype = esttype,
uniqueid = cuniqueid,
stratalut = stratalut2,
RHGlut = RHGlut2,
unitvar = "ONEUNIT",
strvar = strvar,
domain = rowvar)
rowunit <- add0unit(x=rowunit, xvar=rowvar, uniquex=uniquerow,
unitvar="ONEUNIT", xvar.add0=row.add0)
tabs <- check.matchclass(unitarea2, rowunit, "ONEUNIT")
unitarea2 <- tabs$tab1
rowunit <- tabs$tab2
setkeyv(rowunit, "ONEUNIT")
rowunit <- rowunit[unitarea2, nomatch=0]
if (totals) {
rowunit <- getpse(rowunit, areavar=areavar, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
} else {
rowunit <- getpse(rowunit, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
}
setkeyv(rowunit, c("ONEUNIT", rowvar))
## CALCULATE GRAND TOTAL FOR ALL UNITS
cdomdatsum <- cdomdat[, lapply(.SD, sum, na.rm=TRUE),
by=c(strunitvarsRHG2, cuniqueid, "TOTAL"), .SDcols=estvar.name]
totunit <- Ratio2Size(yn = estvar.name,
yd = pmeassubp.name,
ysum = cdomdatsum,
dsum = pmeasprop2,
esttype = esttype,
uniqueid = cuniqueid,
stratalut = stratalut2,
RHGlut = RHGlut2,
unitvar = "ONEUNIT",
strvar = strvar,
domain = "TOTAL")
tabs <- check.matchclass(unitarea2, totunit, "ONEUNIT")
unitarea2 <- tabs$tab1
totunit <- tabs$tab2
setkeyv(totunit, "ONEUNIT")
totunit <- totunit[unitarea2, nomatch=0]
if (totals) {
totunit <- getpse(totunit, areavar=areavar, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
} else {
totunit <- getpse(totunit, esttype=esttype,
nhatcol="ybar", nhatcol.var="ybar.var")
}
}
###################################################################################
## GENERATE OUTPUT TABLES
###################################################################################
message("getting output...")
estnm <- "est"
tabs <- est.outtabs(esttype=esttype, sumunits=sumunits, areavar=areavar,
unitvar=unitvar, unitvars=unitvars, unit_totest=unit_totest,
unit_rowest=unit_rowest, unit_colest=unit_colest, unit_grpest=unit_grpest,
rowvar=rowvar, colvar=colvar, uniquerow=uniquerow, uniquecol=uniquecol,
rowgrp=rowgrp, rowgrpnm=rowgrpnm, rowunit=rowunit, totunit=totunit,
allin1=allin1, savedata=savedata, addtitle=addtitle, title.ref=title.ref,
title.rowvar=title.rowvar, title.colvar=title.colvar, title.rowgrp=title.rowgrp,
title.unitvar=title.unitvar, title.estpse=title.estpse, title.est=title.est,
title.pse=title.pse, rawdata=rawdata, rawonly=rawonly, outfn.estpse=outfn.estpse,
outfolder=outfolder, outfn.date=outfn.date, overwrite=overwrite_layer,
estnm=estnm, estround=estround, pseround=pseround, divideby=divideby,
returntitle=returntitle, estnull=estnull, psenull=psenull, raw.keep0=raw.keep0)
est2return <- tabs$tabest
pse2return <- tabs$tabpse
if (!is.null(est2return)) {
returnlst$est <- setDF(est2return)
}
if (!is.null(pse2return)) {
returnlst$pse <- setDF(pse2return)
}
if (returntitle) {
returnlst$titlelst <- alltitlelst
}
if (rawdata) {
rawdat <- tabs$rawdat
rawdat$domdat <- setDF(cdomdat)
if (savedata) {
if (!is.null(title.estpse)) {
title.raw <- paste(title.estpse, title.ref)
} else {
title.raw <- paste(title.est, title.ref, sep="; ")
}
for (i in 1:length(rawdat)) {
tabnm <- names(rawdat[i])
rawtab <- rawdat[[i]]
outfn.rawtab <- paste0(outfn.rawdat, "_", tabnm)
if (tabnm %in% c("plotsampcnt", "condsampcnt", "stratcombinelut")) {
write2csv(rawtab, outfolder=rawfolder, outfilenm=outfn.rawtab,
outfn.date=outfn.date, overwrite=overwrite_layer)
} else if (is.data.frame(rawtab)) {
if (raw_fmt != "csv") {
out_layer <- tabnm
} else {
out_layer <- outfn.rawtab
}
datExportData(rawtab,
savedata_opts=list(outfolder=rawfolder,
out_fmt=raw_fmt,
out_dsn=raw_dsn,
out_layer=out_layer,
overwrite_layer=overwrite_layer,
append_layer=append_layer,
add_layer=TRUE))
}
}
}
rawdat$module <- "WF"
rawdat$esttype <- esttype
rawdat$WFmethod <- ifelse(strata, "PS", "HT")
if (!is.null(rowvar)) rawdat$rowvar <- rowvar
if (!is.null(colvar)) rawdat$colvar <- colvar
rawdat$areaunits <- areaunits
returnlst$raw <- rawdat
}
if ("STATECD" %in% names(pltcondf)) {
returnlst$statecd <- sort(unique(pltcondf$STATECD))
}
if ("INVYR" %in% names(pltcondf)) {
returnlst$invyr <- sort(unique(pltcondf$INVYR))
}
return(returnlst)
}
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