| mvncovar1 {longit} | R Documentation |
Bayesian multivariate regression with independent covariance matrix for high dimensional longitudinal data.
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
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data(repdata)
mvncovar1(m=4,n=7,time="Age",group="Gender",chains=10,iter=100,repdata)
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