DPcaterpillar: Caterpillar Plots for Random Effects

In DPpackage: Bayesian Nonparametric Modeling in R

Description

This generic function produces Caterpillar Plots for Random Effects from DPrandom objects.

Usage

DPcaterpillar(object, midpoint="mean", hpd=TRUE , ask=TRUE, 
              nfigr=1, nfigc=1, ...)

Arguments

object	DPrandom object from which random effects estimates can be extracted.
midpoint	variable indicating whether the mean or median of the posterior distribution of random effects should be considered as "midpoint" in the caterpillar plot.
hpd	logical variable indicating whether the hpd (TRUE) or pd (FALSE) of random effects should be considered in the caterpillar plot.
ask	logical variable indicating whether the caterpillar plots should be display gradually (TRUE) or not (FALSE).
nfigr	integer variable indicating the number of caterpillar plots by row.
nfigc	integer variable indicating the number of caterpillar plots by column.
...	further arguments passed to or from other methods.

Author(s)

Alejandro Jara <[e-mail]>

Examples

## Not run: 
    # School Girls Data Example

      data(schoolgirls)
      attach(schoolgirls)

    # Prior information
    # Prior information

      tinv<-diag(10,2)
      prior<-list(alpha=1,nu0=4.01,tau1=0.001,tau2=0.001,
      tinv=tinv,mub=rep(0,2),Sb=diag(1000,2))

    # Initial state
      state <- NULL

    # MCMC parameters

      nburn<-5000
      nsave<-25000
      nskip<-20
      ndisplay<-1000
      mcmc <- list(nburn=nburn,nsave=nsave,nskip=nskip,
                   ndisplay=ndisplay)

    # Fit the model
    
      fit1<-DPlmm(fixed=height~1,random=~age|child,prior=prior,
                  mcmc=mcmc,state=state,status=TRUE)
      fit1


    # Extract random effects
    
      DPcaterpillar(DPrandom(fit1))

## End(Not run)

DPpackage documentation built on May 1, 2019, 10:23 p.m.