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afthd (version 1.1.0)

Accelerated Failure Time for High Dimensional Data with MCMC

Description

Functions for Posterior estimates of Accelerated Failure Time(AFT) model with MCMC and Maximum likelihood estimates of AFT model without MCMC for univariate and multivariate analysis in high dimensional gene expression data are available in this 'afthd' package. AFT model with Bayesian framework for multivariate in high dimensional data has been proposed by Prabhash et al.(2016) .

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Version

Install

install.packages('afthd')

Monthly Downloads

489

Version

1.1.0

License

GPL-3

Maintainer

Atanu Bhattacharjee

Last Published

October 1st, 2021

Functions in afthd (1.1.0)

Multivariate estimates of AFT model with log logistic distribution using MCMC.

Head and neck cancer data

Bayesian univariate analysis of AFT model for selected covariates using regularization method.

Bayesian univariate analysis of AFT model with log normal distribution.

Estimates of univariate covariates using Accelerated Failure time (AFT) model without MCMC.

Bayesian multivariate analysis of AFT model for selected covariates using regularization method.

Bayesian multivariate analysis of parametric AFT model with minimum deviance (DIC) among weibull, log normal and log logistic distribution.

Bayesian multivariate analysis of AFT model with log normal distribution.

Univariate estimates of AFT model with log logistic distribution using MCMC.

Estimates of selected univariate covariates(using regularization) in AFT model without MCMC.

Multivariate estimates of AFT model with weibull distribution using MCMC that supports augmented data.

Bayesian multivariate estimates for competing risk gene expression data using AFT model.

Posterior univariate estimates of AFT model with weibull distribution using MCMC.

Posterior multivariate estimates of AFT model with weibull distribution using MCMC.

Bayesian univariate estimates for competing risk gene expression data using AFT model.