Description Usage Arguments Value References Examples
Function to implement the horseshoe shrinkage prior in integrated survival and binary regression
1 2 | aftprobiths(ct, z, X, burn = 1000, nmc = 5000, thin = 1,
alpha = 0.05, Xtest = NULL, cttest = NULL, ztest = NULL)
|
ct |
survival response, a n*2 matrix with first column as response and second column as right censored indicator, 1 is event time and 0 is right censored. |
z |
binary response, a n*1 vector with numeric values 0 or 1. |
X |
Matrix of covariates, dimension n*p. |
burn |
Number of burn-in MCMC samples. Default is 1000. |
nmc |
Number of posterior draws to be saved. Default is 5000. |
thin |
Thinning parameter of the chain. Default is 1 (no thinning). |
alpha |
Level for the credible intervals. For example, alpha = 0.05 results in 95% credible intervals. |
Xtest |
test design matrix. |
cttest |
test survival response. |
ztest |
test binary response. |
Beta.sHat |
Posterior mean of β for survival model, a p by 1 vector. |
Beta.bHat |
Posterior mean of β for binary model, a p by 1 vector. |
LeftCI.s |
The left bounds of the credible intervals for Beta.sHat. |
RightCI.s |
The right bounds of the credible intervals for Beta.sHat. |
LeftCI.b |
The left bounds of the credible intervals for Beta.bHat. |
RightCI.b |
The right bounds of the credible intervals for Beta.bHat. |
Beta.sMedian |
Posterior median of beta for survival model, a p by 1 vector. |
Beta.bMedian |
Posterior median of beta for binary model, a p by 1 vector. |
SigmaHat |
Posterior mean of variance covariance matrix. |
LambdaHat |
Posterior mean of λ, a p*1 vector. |
TauHat |
Posterior mean of τ, a 2*1 vector. |
Beta.sSamples |
Posterior samples of β for survival model. |
Beta.bSamples |
Posterior samples of β for binary model. |
LambdaSamples |
Posterior samples of λ. |
TauSamples |
Posterior samples of τ. |
SigmaSamples |
Posterior samples of variance covariance matrix. |
DIC.s |
DIC for survival model. |
DIC.b |
DIC for binary model. |
SurvivalHat |
Predictive survival probability. |
LogTimeHat |
Predictive log time. |
Maity, A. K., Carroll, R. J., and Mallick, B. K. (2018), Integration of Survival and Binary Data for Variable Selection and Prediction: A Bayesian Approach.
1 | ## Not run: #
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.