Compute the R-squared measure under the accelerated failure time (AFT) models proposed in Chan et. al. (2018) <doi:10.1080/03610918.2016.1177072>.

Implements several basic algorithms for estimating regression parameters for semiparametric accelerated failure time (AFT) model. The main methods are: Jin rank-based method (Jin (2003) <doi:10.1093/biomet/90.2.341>), Heller’s estimating method (Heller (2012) <doi:10.1198/016214506000001257>), Polynomial smoothed Gehan function method (Chung (2013) <doi:10.1007/s11222-012-9333-9>), Buckley-James method (Buckley (1979) <doi:10.2307/2335161>) and Jin`s improved least squares method (Jin (2006) <doi:10.1093/biomet/93.1.147>). This package can be used for modeling right-censored data and for comparing different estimation algorithms.

A collection of model checking methods for semiparametric 
    accelerated failure time (AFT) models under the rank-based approach. For the 
    (computational) efficiency, Gehan's weight is used. It provides functions to 
    verify whether the observed data fit the specific model assumptions such as 
    a functional form of each covariate, a link function, and an omnibus test. 
    The p-value offered in this package is based on the Kolmogorov-type supremum 
    test and the variance of the proposed test statistics is estimated through 
    the re-sampling method. Furthermore, a graphical technique to compare the 
    shape of the observed residual to a number of the approximated realizations 
    is provided. See the following references; A general model-checking 
    procedure for semiparametric accelerated failure time models, Statistics and 
    Computing, 34 (3), 117 <doi:10.1007/s11222-024-10431-7>; Diagnostics for 
    semiparametric accelerated failure time models with R package 'afttest', 
    arXiv, <doi:10.48550/arXiv.2511.09823>.

Tools for downloading and extracting data from the Copernicus "Agrometeorological indicators 
  from 1979 to present derived from reanalysis"
  <https://cds.climate.copernicus.eu/datasets/sis-agrometeorological-indicators?tab=overview> (AgERA5).