sim.train.test: Simulate in-sample and out-of-sample deviance
In joepowers16/rethinking: Statistical Rethinking book package

Description Usage Arguments Details Author(s)

Simulates posterior observations for map and map2stan model fits.

1 2	sim.train.test( N=20 , k=3 , rho=c(0.15,-0.4) , b_sigma=100 , DIC=FALSE , WAIC=FALSE, devbar=FALSE , devbarout=FALSE )

`N`	Number of cases in simulated data
`k`	Number of parameters in model to fit to data
`rho`	Vector of correlations between predictors and outcome, in simulated data
`b_sigma`	Standard deviation of beta-coefficient priors
`DIC`	If `TRUE`, returns DIC
`WAIC`	If `TRUE`, returns WAIC
`devbar`	If `TRUE`, returns the average deviance in-sample
`devbarout`	If `TRUE`, returns average deviance out-of-sample

This function simulates Gaussian data and then fits linear regression models to it, returning the deviance of the fit (training, in-sample) and the deviance on a new sample, computed using the MAP estimates from the training sample.

Richard McElreath

joepowers16/rethinking documentation built on June 2, 2019, 6:52 p.m.