Learn R Programming

jomo (version 1.3-1)

jomo1.MCMCchain: JM Imputation of single level data - A tool to check convergence of the MCMC

Description

This function is similar to jomo1, but it returns the values of all the parameters in the model at each step of the MCMC instead of the imputations. It is useful to check the convergence of the MCMC sampler.

Usage

jomo1.MCMCchain(Y, X=NULL, beta.start=NULL, l1cov.start=NULL, l1cov.prior=NULL,
nburn=500, output=1, out.iter=10)

Arguments

Y
a data.frame where columns related to continuous variables are numeric and columns related to binary/categorical variables are factors.
X
A data frame, or matrix, with covariates of the joint imputation model. Rows correspond to different observations, while columns are different variables. Missing values are not allowed in these variables. In case we want an intercept, a column of 1 is nee
beta.start
Starting value for beta, the vector(s) of fixed effects. Rows index different covariates and columns index different outcomes. For each n-category variable we define n-1 latent normals. The default is a matrix of zeros.
l1cov.start
Starting value for the covariance matrix. Dimension of this square matrix is equal to the number of outcomes (continuous plus latent normals) in the imputation model. The default is the identity matrix.
l1cov.prior
Scale matrix for the inverse-Wishart prior for the covariance matrix. The default is the identity matrix.
nburn
Number of iterations. Default is 100.
output
When set to any value different from 1 (default), no output is shown on screen at the end of the process.
out.iter
When set to K, every K iterations a message "Iteration number N*K completed" is printed on screen. Default is 10.

Value

  • A list with three elements is returned: the final imputed dataset (finimp) and three 3-dimensional matrices, containing all the values for beta (collectbeta) and omega (collectomega).

Examples

Run this code
# Using sldata:

data(sldata)
attach(sldata)

#We define all the inputs:

Y=data.frame(measure,age)
nburn=as.integer(200);

# Then we run the function:

imp<-jomo1.MCMCchain(Y,nburn=nburn)

#We can check the convergence of the first element of beta:

plot(c(1:nburn),imp$collectbeta[1,1,1:nburn],type="l")

#Or similarly we can check the convergence of any element of omega:

plot(c(1:nburn),imp$collectomega[1,2,1:nburn],type="l")

Run the code above in your browser using DataLab