Maintainer: Sy Han (Steven) Chiou  <schiou@d.umn.edu>

Maintainer: Sy Han (Steven) Chiou  <schiou@utdallas.edu>
Description: A collection of methods for both the rank-based estimates and least
Details of the rank-based estimation can be found in
For the least-square estimation, the estimating equation is
solved with Generalized Estimating Equations (GEE).
Details on the least-squares estimation can be found in
Imports: MASS, BB, survival, geepack, parallel, methods

Authors@R: c(person("Sy Han", "Chiou", email = "schiou@utdallas.edu", role = c("aut", "cre")),
person("Sangwook", "Kang", role = "aut"),
Description: A collection of methods for both the rank-based estimates and least-square estimates
to the Accelerated Failure Time (AFT) model.
For rank-based estimation, it provides approaches that include the computationally
efficient Gehan's weight and the general's weight such as the logrank weight.
For the least-square estimation, the estimating equation is solved with
Moreover, in multivariate cases, the dependence working correlation structure
Imports: methods, parallel, geepack, survival, BB, MASS
Maintainer: Sy Han Chiou <schiou@utdallas.edu>

Description: A collection of methods for both the rank-based estimates and least-square estimates to the Accelerated Failure Time (AFT) model. For rank-based estimation, it provides approaches that include the computationally efficient Gehan's weight and the general's weight such as the logrank weight. Details of the rank-based estimation can be found in Chiou et al. (2014) <doi:10.1007/s11222-013-9388-2> and Chiou et al. (2015) <doi:10.1002/sim.6415>. For the least-square estimation, the estimating equation is solved with generalized estimating equations (GEE). Moreover, in multivariate cases, the dependence working correlation structure can be specified in GEE's setting. Details on the least-squares estimation can be found in Chiou et al. (2014) <doi:10.1007/s10985-014-9292-x>.

Title: 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)