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.

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

Calculate 'ActiGraph' counts from the X, Y, and Z axes of a triaxial 
    accelerometer. This work was inspired by Neishabouri et al. who published the 
    article "Quantification of Acceleration as Activity Counts in 'ActiGraph' Wearables" 
    on February 24, 2022. The link to the article (<https://pubmed.ncbi.nlm.nih.gov/35831446>) 
    and 'python' implementation of this code (<https://github.com/actigraph/agcounts>).