predSimNormsSelectWithRounding: Predict and simulate value from n normal models with...

In kcha193/simarioV2: Discrete-time Dynamic Micro-simulation Framework for R

Predict and simulate value from n normal models with truncation/rounding to ensure simulated values stay within their category bounds.

Description

A function based on PredSimNormsSelect with the modification that if any simulated values are outside the binbreaks for the group, the simulated values are changed to be equal to the boundary value. Use when all the catToCont models for a variable are normal.

Usage

predSimNormsSelectWithRounding(
  x.cat,
  models,
  cont.binbreaks,
  envir = parent.frame()
)

Arguments

x.cat	a categorical vector
models	a list of models with length equal to the number of categories in x.cat
cont.binbreaks	the binbreaks of the categorical variable
envir	environment in which to evaluate model variables.

Value

a continuous vector that when binned by cont.bonbreaks will be the same as x.cat

kcha193/simarioV2 documentation built on April 8, 2024, 4:51 p.m.