## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", eval = TRUE ) ## ----data--------------------------------------------------------------------- library(smfa) data("ricephil", package = "sfaR") ricephil$group <- cut( ricephil$AREA, breaks = quantile(ricephil$AREA, probs = c(0, 1/3, 2/3, 1), na.rm = TRUE), labels = c("small", "medium", "large"), include.lowest = TRUE ) table(ricephil$group) #> small medium large #> 125 104 115 ## ----lp----------------------------------------------------------------------- meta_lp <- smfa( formula = log(PROD) ~ log(AREA) + log(LABOR) + log(NPK), data = ricephil, group = "group", S = 1, udist = "hnormal", groupType = "sfacross", metaMethod = "lp" ) summary(meta_lp) ## ----qp----------------------------------------------------------------------- meta_qp <- smfa( formula = log(PROD) ~ log(AREA) + log(LABOR) + log(NPK), data = ricephil, group = "group", S = 1, udist = "hnormal", groupType = "sfacross", metaMethod = "qp" ) summary(meta_qp) ## ----huang-------------------------------------------------------------------- meta_huang <- smfa( formula = log(PROD) ~ log(AREA) + log(LABOR) + log(NPK), data = ricephil, group = "group", S = 1, udist = "hnormal", groupType = "sfacross", metaMethod = "sfa", sfaApproach = "huang" ) summary(meta_huang) ## ----odonnell----------------------------------------------------------------- meta_ordonnell <- smfa( formula = log(PROD) ~ log(AREA) + log(LABOR) + log(NPK), data = ricephil, group = "group", S = 1, udist = "hnormal", groupType = "sfacross", metaMethod = "sfa", sfaApproach = "ordonnell" ) summary(meta_ordonnell) ## ----eff---------------------------------------------------------------------- eff <- efficiencies(meta_lp) head(eff) # Subset for a specific group eff_small <- eff[eff$group == "small", ] summary(eff_small[, c("TE_group_BC", "TE_meta_BC", "MTR_BC")]) ## ----other-------------------------------------------------------------------- coef(meta_qp) # metafrontier coefficients vcov(meta_qp) # variance-covariance matrix logLik(meta_lp) # log-likelihood ic(meta_lp) # AIC, BIC, HQIC nobs(meta_lp) # number of observations fitted(meta_lp) # fitted values residuals(meta_lp) # residuals