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MTAFT  

Data-Driven Estimation for Multi-Threshold Accelerate Failure Time Model
View on CRAN: Click here


Download and install MTAFT package within the R console
Install from CRAN:
install.packages("MTAFT")

Install from Github:
library("remotes")
install_github("cran/MTAFT")

Install by package version:
library("remotes")
install_version("MTAFT", "0.1.0")



Attach the package and use:
library("MTAFT")
Maintained by
Chuang WAN
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-11-13
Latest Update: 2023-11-13
Description:
Developed a data-driven estimation framework for the multi-threshold accelerate failure time (MTAFT) model. The MTAFT model features different linear forms in different subdomains, and one of the major challenges is determining the number of threshold effects. The package introduces a data-driven approach that utilizes a Schwarz' information criterion, which demonstrates consistency under mild conditions. Additionally, a cross-validation (CV) criterion with an order-preserved sample-splitting scheme is proposed to achieve consistent estimation, without the need for additional parameters. The package establishes the asymptotic properties of the parameter estimates and includes an efficient score-type test to examine the existence of threshold effects. The methodologies are supported by numerical experiments and theoretical results, showcasing their reliable performance in finite-sample cases.
How to cite:
Chuang WAN (2023). MTAFT: Data-Driven Estimation for Multi-Threshold Accelerate Failure Time Model. R package version 0.1.0, https://cran.r-project.org/web/packages/MTAFT. Accessed 07 Nov. 2024.
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