Nothing
## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
# define reporting and removal functions
get.models <- function(pattern){
# get the list of models according to the pattern specified
#browser()
model.list <- mget( ls(envir=globalenv())[grepl(pattern,ls(envir=globalenv()))], envir=globalenv())
model.list
}
make.report <- function(model.list){
# make a little report
report <- plyr::ldply(model.list, function(x){
#browser()
data.frame(#version=x$version,
date = as.Date(x$date),
model.id = x$model.info$model.id,
s.a.pool =-1+nrow(x$fit.setup$pooldata),
t.p.pool =-1+ncol(x$fit.setup$pooldata),
logL.cond = x$model.info$logL.cond,
np = x$model.info$np,
AICc = x$model.info$AICc,
gof.chisq = round(x$gof$chisq,1),
gof.df = x$gof$chisq.df,
gof.p = round(x$gof$chisq.p,3),
Nhat = round(x$est$real$N),
Nhat.se = round(x$se $real$N))
})
report
}
remove.models <- function(model.list){
rm(list=names(model.list), envir=globalenv())
}
## -----------------------------------------------------------------------------
test.data.csv <- textConnection("
160 , 127 , 72 , 82 , 3592
24 , 66 , 13 , 10 , 532
7960 , 9720 , 6264 , 7934 , 0 ")
test.data <- as.matrix(read.csv(test.data.csv, header=FALSE, strip.white=TRUE))
test.data
## -----------------------------------------------------------------------------
library(SPAS)
mod..1 <- SPAS.fit.model(test.data,
model.id="No restrictions",
row.pool.in=1:2, col.pool.in=1:4)
SPAS.print.model(mod..1)
## -----------------------------------------------------------------------------
mod..2 <- SPAS.fit.model(test.data,
model.id="Pool last two columns",
row.pool.in=c(1,2), col.pool.in=c(1,2,34,34))
SPAS.print.model(mod..2)
## -----------------------------------------------------------------------------
mod..3 <- SPAS.fit.model(test.data,
model.id="Pool last two columns",
row.pool.in=c(1,2), col.pool.in=c(12,22,34,34))
SPAS.print.model(mod..3)
## ----echo=FALSE---------------------------------------------------------------
model.list <- get.models("^mod\\.\\.")
make.report(model.list)
remove.models(model.list)
## -----------------------------------------------------------------------------
mod..3 <- SPAS.fit.model(test.data,
model.id="Physical pooling to single row",
row.pool.in=c(1,1), col.pool.in=1:4)
SPAS.print.model(mod..3)
## -----------------------------------------------------------------------------
mod..3a <- SPAS.fit.model(test.data,
model.id="Logical pooling to single row",
row.pool.in=c(1,1), col.pool.in=1:4, row.physical.pool=FALSE)
SPAS.print.model(mod..3a)
## -----------------------------------------------------------------------------
# do physcial complete pooling
mod..4 <- SPAS.fit.model(test.data,
model.id="Physical pooling all rows and last two columns",
row.pool.in=c(1,1), col.pool.in=c(12,12,34,34))
SPAS.print.model(mod..4)
## -----------------------------------------------------------------------------
# do physcial complete pooling
mod..5 <- SPAS.fit.model(test.data,
model.id="Physical complete pooling",
row.pool.in=c(1,1), col.pool.in=c(1,1,1,1))
SPAS.print.model(mod..5)
## ----echo=FALSE---------------------------------------------------------------
model.list <- get.models("^mod\\.\\.")
make.report(model.list)
remove.models(model.list)
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