| creg {longit} | R Documentation |
Bayesian multivariate regression with unstructured covariance matrix for high dimensional longitudinal data.
Description
Multivariate Regression with unstructured covariance matrix in longitudinal datasetup with high dimensional.
Usage
creg(m, n, chains, n.adapt, data)
Arguments
m |
Starting number of column from where repeated observations begin |
n |
Ending number of columns till where the repeated observations ends |
chains |
Number of MCMC chains to be performed |
n.adapt |
Number of iterations to be performed |
data |
High dimensional longitudinal data |
Value
Results of posterior means and standard deviation.
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)
creg(m=4,n=7,chains=4,n.adapt=100,data=repdata)
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