survweibMC: Weibull survival analysis with MCMC

In SurviMChd: High Dimensional Survival Data Analysis with Markov Chain Monte Carlo

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

## Not run: 
##
data(headnneck)
survweibMC(m1=8,n1=12,m2=4,n2=7,chains=2,iter=10,data=headnneck)
##

## End(Not run)

SurviMChd documentation built on May 23, 2021, 5:07 p.m.