mvncovar1: Bayesian multivariate regression with independent covariance...

In longit: High Dimensional Longitudinal Data Analysis Using MCMC

Description

Multivariate Regression with independent covariance matrix in longitudinal datasetup with high dimensional.

Usage

mvncovar1(m, n, time, group, chains, iter, data)

Arguments

m	Starting number of column from where repeated observations begin
n	Ending number of columns till where the repeated observations ends
time	Timepoint information on which repeadted observations were taken
group	A categorical variable either 0 or 1. i.e. Gender - 1 male and 0 female
chains	Number of MCMC chains to be performed
iter	Number of iterations to be performed
data	High dimensional longitudinal data

Value

mvncovarout lists posterior omega and sigma values.

Author(s)

Atanu Bhattacharjee, Akash Pawar and Bhrigu Kumar Rajbongshi

References

Bhattacharjee, A. (2020). Bayesian Approaches in Oncology Using R and OpenBUGS. CRC Press.

Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian data analysis. CRC press.

Fitzmaurice, G. M., Laird, N. M., & Ware, J. H. (2012). Applied longitudinal analysis (Vol. 998). John Wiley & Sons.

Examples

##
data(repdata)
mvncovar1(m=4,n=7,time="Age",group="Gender",chains=10,iter=100,repdata)
##

longit documentation built on April 15, 2021, 9:06 a.m.