## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----libraries---------------------------------------------------------------- library(SPAS) ## ----loaddata----------------------------------------------------------------- conne.data.csv <- textConnection(" 9 , 21 , 0 , 0 , 0 , 0 , 171 0 , 101 , 22 , 1 , 0 , 0 , 763 0 , 0 , 128 , 49 , 0 , 0 , 934 0 , 0 , 0 , 48 , 12 , 0 , 434 0 , 0 , 0 , 0 , 7 , 0 , 49 0 , 0 , 0 , 0 , 0 , 0 , 4 351, 2736 , 3847 , 1818 , 543 , 191 , 0") conne.data <- as.matrix(read.csv(conne.data.csv, header=FALSE)) ## ----fit1,results="hide"------------------------------------------------------ mod1 <- SPAS::SPAS.fit.model(conne.data, model.id="No restrictions", row.pool.in=1:6, col.pool.in=1:6) ## ----mod1p-------------------------------------------------------------------- SPAS.print.model(mod1) ## ----str1--------------------------------------------------------------------- cat("Names of objects at highest level\n") names(mod1) cat("\n\nNames of estimates (both beta and real)\n") names(mod1$est) cat("\n\nNames of real estimates\n") names(mod1$est$real) ## ----fit2,results="hide"------------------------------------------------------ mod2 <- SPAS.fit.model(conne.data, model.id="Pooling some rows", row.pool.in=c("12","12","3","4","56","56"), col.pool.in=c(1,2,3,4,56,56)) ## ----mod2p-------------------------------------------------------------------- SPAS.print.model(mod2) ## ----mod3,results='hide'------------------------------------------------------ mod3 <- SPAS.fit.model(conne.data, model.id="A single row", row.pool.in=rep(1, nrow(conne.data)-1), col.pool.in=c(1,2,3,4,56,56)) ## ----mod3p-------------------------------------------------------------------- SPAS.print.model(mod3) ## ----mod4,results='hide'------------------------------------------------------ mod4 <- SPAS.fit.model(conne.data, model.id="Pooled Peteren", row.pool.in=rep(1, nrow(conne.data)-1), col.pool.in=rep(1, ncol(conne.data)-1)) ## ----mod4p-------------------------------------------------------------------- SPAS.print.model(mod4) ## ----fit5,results="hide"------------------------------------------------------ mod5 <- SPAS.fit.model(conne.data, model.id="Pooling some rows", row.pool.in=c("12","12","3","4","56","56"), row.physical.pool=FALSE, col.pool.in=c(1,2,3,4,56,56)) ## ----------------------------------------------------------------------------- SPAS.print.model(mod5)