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SCRSELECT (version 1.3-3)

Performs Bayesian Variable Selection on the Covariates in a Semi-Competing Risks Model

Description

Contains four functions used in the DIC-tau_g procedure. SCRSELECT() and SCRSELECTRUN() uses Stochastic Search Variable Selection to select important covariates in the three hazard functions of a semi-competing risks model. These functions perform the Gibbs sampler for variable selection and a Metropolis-Hastings-Green sampler for the number of split points and parameters for the three baseline hazard function. The function SCRSELECT() returns the posterior sample of all quantities sampled in the Gibbs sampler after a burn-in period to a desired file location, while the function SCRSELECTRUN() returns posterior values of important quantities to the DIC-Tau_g procedure in a list. The function DICTAUG() returns a list containing the DIC values for the unique models visited by the DIC-Tau_g grid search. The function ReturnModel() uses SCRSELECTRUN() and DICTAUG() to return a summary of the posterior coefficient vectors for the optimal model along with saving this posterior sample to a desired path location.

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Version

Install

install.packages('SCRSELECT')

Monthly Downloads

23

Version

1.3-3

License

GPL-2

Maintainer

Andrew G Chapple

Last Published

August 23rd, 2017

Functions in SCRSELECT (1.3-3)

DICTAUG

Performs a grid search over the marginal posterior probabilities of inclusion and returns a list of DIC values corresponding to each grid point. This is used in the ReturnModel function.
ReturnModel

Performs the DIC-tau_g procedure and returns the posterior quantities of the optimal model.
SCRSELECT

Performs Bayesian Variable Selection on the covariates in a semi-competing risks model
SCRSELECTRETURN

Performs Bayesian Variable Selection on the covariates in a semi-competing risks model and returns burned in posterior means of parameters. This function is used in the ReturnModel function.