Package: MTAFT 0.1.0

Chuang WAN

MTAFT: Data-Driven Estimation for Multi-Threshold Accelerate Failure Time Model

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.

Authors:Chuang WAN [aut, cre], Hao ZENG [aut], Wei ZHONG [aut], Changliang ZOU [aut]

MTAFT_0.1.0.tar.gz
MTAFT_0.1.0.tar.gz(r-4.5-noble)MTAFT_0.1.0.tar.gz(r-4.4-noble)
MTAFT_0.1.0.tgz(r-4.4-emscripten)MTAFT_0.1.0.tgz(r-4.3-emscripten)
MTAFT.pdf |MTAFT.html
MTAFT/json (API)

# Install 'MTAFT' in R:
install.packages('MTAFT', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.70 score 1 scripts 149 downloads 5 exports 3 dependencies

Last updated 1 years agofrom:0393828830. Checks:OK: 1 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 08 2024
R-4.5-linuxNOTENov 08 2024

Exports:MTAFT_CVMTAFT_ICMTAFT_simdataMTAFT_testTSMCP

Dependencies:grpreglatticeMatrix