| survweibMC {SurviMChd} | R Documentation |
Weibull survival analysis with MCMC
Description
Survival analysis with weibull distribution by MCMC
Usage
survweibMC(m1, n1, m2, n2, chains, iter, data)
Arguments
m1 |
Starting column number from where variables of high dimensional data will be selected. |
n1 |
Ending column number till where variables of high dimensional data will get selected. |
m2 |
Starting column number from where demographic observations starts |
n2 |
Ending column number of the demographic observations |
chains |
Number of MCMC chains |
iter |
Number of MCMC iterations |
data |
High dimensional data having survival duration as (OS), event information as Death (1 if died, or 0 if alive). |
Value
beta1[1] Posterior estimates of regression coefficients and deviance
Author(s)
Atanu Bhattacharjee and Akash Pawar
References
Kumar, M., Sonker, P. K., Saroj, A., Jain, A., Bhattacharjee, A., & Saroj, R. K. (2020). Parametric survival analysis using R: Illustration with lung cancer data. Cancer Reports, 3(4), e1210.
Khan, S. A. (2018). Exponentiated Weibull regression for time-to-event data. Lifetime data analysis, 24(2), 328-354.
See Also
survexpMC
Examples
##
data(headnneck)
survweibMC(m1=8,n1=12,m2=4,n2=7,chains=2,iter=10,data=headnneck)
##