# dlanalysis: dlanalysis In dlbayes: Use Dirichlet Laplace Prior to Solve Linear Regression Problem and Do Variable Selection

## Description

This is a function that analyse the MCMC sampling result by computing the posterior mean, median and credible intervals

## Usage

 `1` ```dlanalysis(dlresult, alpha = 0.05) ```

## Arguments

 `dlresult` Posterior samples of beta. A large matrix (nmc/thin)*p `alpha` Level for the credible intervals. For example,the default is alpha = 0.05 means 95% credible intervals

## Value

 `betamean` Posterior mean of beta, a p*1 vector. `LeftCI` The left bounds of the credible intervals. `RightCI` The right bounds of the credible intervals. `betamedian` Posterior median of Beta, a p*1 vector.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```p=50 n=5 #generate x x=matrix(rnorm(n*p),nrow=n) #generate beta beta=c(rep(0,10),runif(n=5,min=-1,max=1),rep(0,10),runif(n=5,min=-1,max=1),rep(0,p-30)) #generate y y=x%*%beta+rnorm(n) hyper=dlhyper(x,y) dlresult=dl(x,y,hyper=hyper) da=dlanalysis(dlresult,alpha=0.05) da\$betamean da\$betamedian da\$LeftCI da\$RightCI ```

dlbayes documentation built on May 2, 2019, 8:28 a.m.