sandbox/modGBdwm.R

In USDAForestService/FIESTA: Forest Inventory Estimation and Analysis

#' Green-Book module - Generate area estimates.
#' 
#' Generates area estimates by domain (and estimation unit). Calculations are
#' based on Scott et al. 2005 ('the green-book') for mapped forest inventory
#' plots. The non-ratio estimator for estimating area by stratum and domain is
#' used. Plots that are totally nonsampled are excluded from estimation
#' dataset. Next, an adjustment factor is calculated by strata to adjust for
#' nonsampled (nonresponse) conditions that have proportion less than 1. The
#' attribute is the proportion of the plot which is divided by the adjustment
#' factor, and averaged by stratum. Strata means are combined using the strata
#' weights and then expanded to area using the total land area in the
#' population.
#' 
#' 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 GBpopdat List. Population data objects returned from modGBpop().
#' @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 modGBpop() if GBpopdat 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
#' @examples
#' \donttest{
#' GBpopdat <- modGBpop(
#' popTabs = list(cond = FIESTA::WYcond,  
#'                tree = FIESTA::WYtree,        
#'                seed = FIESTA::WYseed),      
#' popTabIDs = list(cond = "PLT_CN"),            
#' pltassgn = FIESTA::WYpltassgn,  
#' pltassgnid = "CN",        
#' pjoinid = "PLT_CN",         
#' unitarea = FIESTA::WYunitarea,
#' unitvar = "ESTN_UNIT",        
#' strata = TRUE,           
#' stratalut = WYstratalut,    
#' strata_opts = strata_options(getwt = TRUE)   
#' )
#' 
#' forest_area <- modGBarea(
#' GBpopdat = GBpopdat, 
#' landarea = "FOREST",  
#' sumunits = TRUE,      
#' )
#' str(forest_area, max.level = 1)
#' 
#' forest_area_by_forest_type <- modGBarea(
#' GBpopdat = GBpopdat,        
#' landarea = "FOREST",       
#' rowvar = "FORTYPCD",        
#' sumunits = TRUE            
#' )
#' str(forest_area_by_forest_type, max.level = 1)
#' }
modGBdwm <- function(GBpopdat,
                     dwmtype = "CWD",
                     dwmvar = "VOLCF", 
                     peracre = FALSE,
                     landarea = "FOREST", 
                     pcfilter = NULL, 
                     rowvar = NULL, 
                     colvar = NULL, 
                     sumunits = TRUE, 
                     returntitle = FALSE, 
                     savedata = FALSE, 
                     newvars_opts = NULL,
                     table_opts = NULL, 
                     title_opts = NULL, 
                     savedata_opts = NULL, 
                     ...){

  ###################################################################################
  ## DESCRIPTION: 
  ## Generates acre estimates by domain (and estimation unit)
  ###################################################################################

  
  ## CHECK GUI - IF NO ARGUMENTS SPECIFIED, ASSUME GUI=TRUE
  #if (nargs() == 0 && is.null(GBpopdat)) gui <- TRUE
  gui <- FALSE 
  
  ## 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" 
  popType <- "DWM"
  nonresp <- FALSE
  substrvar <- NULL
  parameters <- FALSE
  returnlst <- list()
  rawdata <- TRUE
  
  ## Set global variables
  ONEUNIT=n.total=n.strata=strwt=TOTAL=rawfolder <- NULL
  #estvar <- "CONDPROP_ADJ"
  
  ##################################################################
  ## CHECK PARAMETER NAMES
  ##################################################################
  
  ## Check input parameters
  input.params <- names(as.list(match.call()))[-1]
  formallst <- c(names(formals(modGBarea)),
		names(formals(modGBpop))) 
  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("pltcondx", "cuniqueid", "condid", 
             "unitarea", "unitvar", "stratalut", "strvar",
             "plotsampcnt", "condsampcnt")
  GBpopdat <- pcheck.object(GBpopdat, "GBpopdat", list.items=list.items)
  if (is.null(GBpopdat)) return(NULL)
  pltidsadj <- GBpopdat$pltidsadj
  pltcondx <- GBpopdat$pltcondx
  pltcondflds <- GBpopdat$pltcondflds
  cuniqueid <- GBpopdat$cuniqueid
  condid <- GBpopdat$condid
  ACI <- GBpopdat$ACI
  pltassgnx <- GBpopdat$pltassgnx
  unitarea <- GBpopdat$unitarea
  areavar <- GBpopdat$areavar
  areaunits <- GBpopdat$areaunits
  unitvar <- GBpopdat$unitvar
  unitvars <- GBpopdat$unitvars
  strata <- GBpopdat$strata
  stratalut <- GBpopdat$stratalut
  strvar <- GBpopdat$strvar
  expcondtab <- GBpopdat$expcondtab
  plotsampcnt <- GBpopdat$plotsampcnt
  condsampcnt <- GBpopdat$condsampcnt
  states <- GBpopdat$states
  invyrs <- GBpopdat$invyrs
  stratcombinelut <- GBpopdat$stratcombinelut
  strwtvar <- GBpopdat$strwtvar
  adj <- GBpopdat$adj
  strunitvars <- c(unitvar, strvar)
  strata <- GBpopdat$strata
  popdatindb <- GBpopdat$popdatindb
  pop_fmt <- GBpopdat$pop_fmt
  pop_dsn <- GBpopdat$pop_dsn
  pop_schema <- GBpopdat$pop_schema
  popconn <- GBpopdat$popconn
  dbqueries <- GBpopdat$dbqueries
  dbqueriesWITH <- GBpopdat$dbqueriesWITH
  areawt <- GBpopdat$areawt
  areawt2 <- GBpopdat$areawt2
  adjcase <- GBpopdat$adjcase

  if (popdatindb) {
    if (is.null(popconn) || !DBI::dbIsValid(popconn)) {
      if (!is.null(pop_dsn)) {
        if (pop_fmt == "sqlite") {
          popconn <- DBtestSQLite(pop_dsn, dbconnopen = TRUE)
        }
      } else {
        stop("invalid database connection")
      }
    }
    pltcondxWITHqry <- dbqueriesWITH$pltcondxWITH
    pltcondxadjWITHqry <- dbqueriesWITH$pltcondxadjWITH
  } else {
    pltcondxWITHqry=pltcondxadjWITHqry <- NULL
  }
  

  ########################################
  ## 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 adwmtype
  ########################################
  dwmtypelst <- c("CWD", "FWD_LG", "FWD_MD", "FWD_SM")
  dwmtype <- pcheck.varchar(var2check=dwmtype, varnm="dwmtype", 
                            checklst=dwmtypelst, caption="DWM type", stopifnull=TRUE)
  
  dwmvarlst <- c("VOLCF", "DRYBIO", "CARBON")
  dwmvar <- pcheck.varchar(var2check=dwmvar, varnm="dwmvar", 
                           checklst=dwmvarlst, caption="DWM variable", stopifnull=TRUE)
  
  
  adjvar <- paste0("ADJ_FACTOR_", dwmtype)
  estvar_unadj <- paste0(dwmtype, "_", dwmvar, "_UNADJ")
  estvar.name <- paste0(dwmtype, "_", dwmvar, "_ADJ")
  
  ## Define estimation units for response
  estunits <- ifelse(dwmvar == "VOLCF", "cubic feet", 
                     ifelse(dwmvar %in% c("DRYBIO", "CARBON"), "pounds"))
  
  dwmadjcase <- estvar.name
  
  

  ###################################################################################
  ## Check parameter inputs and plot/condition filters
  ###################################################################################
  estdat <- 
    check.estdata(esttype = esttype, 
                  popType = popType,
                  popdatindb = popdatindb, 
                  popconn = popconn, pop_schema = pop_schema,
                  pltcondflds = pltcondflds,
                  total = totals,
                  pop_fmt = pop_fmt, pop_dsn = pop_dsn, 
                  sumunits = sumunits, 
                  landarea = landarea,
                  ACI = ACI, 
                  pcfilter = pcfilter,
                  allin1 = allin1, divideby = divideby,
                  estround = estround, pseround = pseround,
                  addtitle = addtitle, returntitle = returntitle, 
                  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)
  esttype <- estdat$esttype
  sumunits <- estdat$sumunits
  totals <- estdat$totals
  landarea <- estdat$landarea
  allin1 <- estdat$allin1
  divideby <- estdat$divideby
  estround <- estdat$estround
  pseround <- estdat$pseround
  addtitle <- estdat$addtitle
  returntitle <- estdat$returntitle
  rawonly <- estdat$rawonly
  savedata <- estdat$savedata
  outfolder <- estdat$outfolder
  overwrite_layer <- estdat$overwrite_layer
  append_layer = estdat$append_layer
  rawfolder <- estdat$rawfolder
  raw_fmt <- estdat$raw_fmt
  raw_dsn <- estdat$raw_dsn
  pcwhereqry <- estdat$where.qry
  SCHEMA. <- estdat$SCHEMA.


  ###################################################################################
  ### Check row and column data
  ###################################################################################
  withqry <- pltcondxWITHqry
  rowcolinfo <- 
    check.rowcol(esttype = esttype, 
                 popType = popType,
                 popdatindb = popdatindb,
                 popconn = popconn, SCHEMA. = SCHEMA.,
                 pltcondx = pltcondx,
                 pltcondflds = pltcondflds,
                 withqry = withqry,
                 cuniqueid = cuniqueid, condid = condid,
                 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, 
                 row.classify = row.classify, col.classify = col.classify,
                 title.rowvar = title.rowvar, title.colvar = title.colvar, 
                 rowlut = rowlut, collut = collut, 
                 rowgrp = rowgrp, rowgrpnm = rowgrpnm, 
                 rowgrpord = rowgrpord, title.rowgrp = NULL,
                 landarea = landarea, states = states, 
                 #cvars2keep = "COND_STATUS_CD",
                 #whereqry = pcwhereqry,
                 gui = gui)
  uniquerow <- rowcolinfo$uniquerow
  uniquecol <- rowcolinfo$uniquecol
  bydomainlst <- rowcolinfo$domainlst
  rowvar <- rowcolinfo$rowvar
  colvar <- rowcolinfo$colvar
  rowvarnm <- rowcolinfo$rowvarnm
  colvarnm <- rowcolinfo$colvarnm
  row.orderby <- rowcolinfo$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
  classifyrow <- rowcolinfo$classifyrow
  classifycol <- rowcolinfo$classifycol
  #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 condition-level domain data
  ###################################################################################
  conddat <- 
    check.cond(areawt = estvar_unadj,
               areawt2 = NULL,
               adj = adj,
               adjcase = dwmadjcase,
               cuniqueid = cuniqueid, 
               condid = condid,
               rowvar = rowvar, 
               colvar = colvar, 
               pcdomainlst = unique(c(bydomainlst, "TOTAL")),
               popdatindb = popdatindb,
               popconn = popconn,
               pltcondx = pltcondx,
               pltidsadj = pltidsadj,
               pltcondxadjWITHqry = pltcondxadjWITHqry,
               pcwhereqry = pcwhereqry,
               classifyrow = classifyrow,
               classifycol = classifycol)
  if (is.null(conddat)) stop(NULL)
  cdomdat <- conddat$cdomdat
  cdomdatqry <- conddat$cdomdatqry
  estnm <- conddat$estnm
  rowvar <- conddat$rowvar
  colvar <- conddat$colvar
  grpvar <- conddat$grpvar


  ###################################################################################
  ### 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
  ###################################################################################
  estdat <- 
    getGBestimates(esttype = esttype,
                   domdatn = cdomdat,
                   uniqueid = cuniqueid,
                   estvarn.name = estnm,
                   rowvar = rowvar, colvar = colvar, 
                   grpvar = grpvar,
                   pltassgnx = pltassgnx,
                   unitarea = unitarea,
                   unitvar = unitvar,
                   areavar = areavar,
                   stratalut = stratalut,
                   strvar = strvar,
                   totals = totals,
                   sumunits = sumunits,
                   uniquerow = uniquerow,
                   uniquecol = uniquecol,
                   row.orderby = row.orderby,
                   col.orderby = col.orderby,
                   row.add0 = row.add0,
                   col.add0 = col.add0)
 
  if (is.null(estdat)) stop()
  unit_totest <- estdat$unit_totest
  unit_rowest <- estdat$unit_rowest
  unit_colest <- estdat$unit_colest
  unit_grpest <- estdat$unit_grpest
  rowunit <- estdat$rowunit
  totunit <- estdat$totunit
  unitvar <- estdat$unitvar
  

  ###################################################################################
  ## 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 = rowvarnm, colvar = colvarnm, 
                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) {
    ## Add total number of plots in population to unit_totest and totest (if sumunits=TRUE)
    UNITStot <- sort(unique(unit_totest[[unitvar]]))
    NBRPLTtot <- stratalut[stratalut[[unitvar]] %in% UNITStot, list(NBRPLT = sum(n.strata, na.rm=TRUE)), 
	                  by=unitvars]

	  if ("unit_totest" %in% names(tabs$rawdat)) {
	    tabs$rawdat$unit_totest <- merge(tabs$rawdat$unit_totest, NBRPLTtot, by=unitvars)
	  }
	  if (sumunits && "totest" %in% names(tabs$rawdat)) {
	    tabs$rawdat$totest <- data.frame(tabs$rawdat$totest, NBRPLT = sum(NBRPLTtot$NBRPLT))
	  }

    rawdat <- tabs$rawdat
    rawdat$domdat <- setDF(cdomdat)
    rawdat$domdatqry <- cdomdatqry
    if (savedata) {
      if (!is.null(title.estpse)) {
        title.raw <- paste(title.estpse, title.ref)
      } else {
        title.raw <- paste(title.est, title.ref, sep="; ")
      }
      for (i in 1:length(rawdat)) {
        tabnm <- names(rawdat[i])
        rawtab <- rawdat[[i]]
        outfn.rawtab <- paste0(outfn.rawdat, "_", tabnm) 
        if (tabnm %in% c("plotsampcnt", "condsampcnt", "stratcombinelut")) {
          write2csv(rawtab, outfolder=rawfolder, outfilenm=outfn.rawtab, 
			        outfn.date=outfn.date, overwrite=overwrite_layer)
        } else if (is.data.frame(rawtab)) {
          if (raw_fmt != "csv") {
            out_layer <- tabnm 
          } else {
            out_layer <- outfn.rawtab
          }
          datExportData(rawtab, 
                savedata_opts = list(outfolder = rawfolder, 
                                     out_fmt = raw_fmt, 
                                     out_dsn = raw_dsn, 
                                     out_layer = out_layer,
                                     overwrite_layer = overwrite_layer,
                                     append_layer = append_layer,
                                     add_layer = TRUE))
        }
      }
    }
    rawdat$module <- "GB"
    rawdat$esttype <- esttype
    rawdat$popType <- popType
    rawdat$GBmethod <- ifelse(strata, "PS", "HT")
    if (!is.null(rowvar)) rawdat$rowvar <- rowvar
    if (!is.null(colvar)) rawdat$colvar <- colvar
    rawdat$areaunits <- areaunits
    returnlst$raw <- rawdat
  }
  returnlst$statecd <- sort(pcheck.states(states, statereturn = "VALUE"))
  returnlst$states <- states
  returnlst$invyr <- sort(unique(unlist(invyrs)))


  return(returnlst)
}