## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>")

## ----example, eval=requireNamespace("nnet", quietly=TRUE)---------------------
library(SynthesizerPlus)
set.seed(204)
input <- data.frame(
  age = rnorm(500, 35, 10),
  income = rgamma(500, shape = 4, scale = 1000)
)
logits <- cbind(0, (input$age - 35)/15, log(input$income/4000))
p <- exp(logits - apply(logits, 1L, max))
p <- p/rowSums(p)
classes <- c("bus", "car", "rail")
input$transport <- factor(classes[apply(p, 1, function(q)
  sample.int(3, 1, prob = q))])

fit <- fit_synthesizer(input, nominal_target = "transport", seed = 11)
synthetic <- generate(fit, n = 500, seed = 12)
prop.table(table(synthetic$transport))
fit$pooled$nominal$selection   # AIC of the spline and linear models