post_bmr {tboot} | R Documentation |
Function post_bmr
Description
Simulates the joint posterior based upon a dataset and specified marginal posterior distribution of the mean of selected variables.
Usage
post_bmr(nsims, weights_bmr)
Arguments
nsims |
The number of posterior simulations to draw. |
weights_bmr |
An object of class 'tweights_bmr' created using the 'tweights_bmr' function. |
Value
A matrix of simulations from the posterior.
See Also
Examples
#Use winsorized marginal to keep marginal simulation within feasible bootstrap region
winsor=function(marginalSims,y) {
l=min(y)
u=max(y)
ifelse(marginalSims<l,l,ifelse(marginalSims>u,u, marginalSims))
}
#Create an example marginal posterior
marginal = list(Sepal.Length=winsor(rnorm(10000,mean=5.8, sd=.2),iris$Sepal.Length),
Sepal.Width=winsor(rnorm(10000,mean=3,sd=.2), iris$Sepal.Width),
Petal.Length=winsor(rnorm(10000,mean=3.7,sd=.2), iris$Petal.Length)
)
#simulate
w = tweights_bmr(dataset = iris, marginal = marginal, silent = TRUE)
post_sims = post_bmr(1000, weights = w)
[Package tboot version 0.2.1 Index]