Performs an analysis of time-to-event clinical trial data using various "win time" methods, 
  including 'ewt', 'ewtr', 'rmt', 'ewtp', 'rewtp', 'ewtpr', 'rewtpr', 'max', 'wtr', 'rwtr', 'pwt', and 'rpwt'. These methods are used to calculate and compare 
  treatment effects on ordered composite endpoints. The package handles event times, event indicators, and treatment 
  arm indicators and supports calculations on observed and resampled data. Detailed explanations of each method and 
  usage examples are provided in "Use of win time for ordered composite endpoints in clinical trials," by Troendle et al. 
  (2024)<https://pubmed.ncbi.nlm.nih.gov/38417455/>. For more information, see the package documentation or the vignette titled "Introduction to wintime."

Implementation of the weighted iterative proportional fitting (WIPF) procedure for updating/adjusting a N-dimensional array given a weight structure and some target marginals.
   Acknowledgements:
   The author wish to thank Conselleria de Educación, Cultura, Universidades y Empleo (grant CIAICO/2023/031), Ministerio de Ciencia, Innovación y Universidades (grant PID2021-128228NB-I00) and Fundación Mapfre (grant 'Modelización espacial e intra-anual de la mortalidad en España. Una herramienta automática para el cálculo de productos de vida') for supporting this research.

In the course of a genome-wide association study, the situation often arises that some phenotypes are known with greater precision than others.
    It could be that some individuals are known to harbor more micro-environmental variance than others.
    In the case of inbred strains of model organisms, it could be the case that more organisms were observed from some strains than others, so the strains with more organisms have better-estimated means.
    Package 'wISAM' handles this situation by allowing for weighting of each observation according to residual variance.
    Specifically, the 'weight' parameter to the function conduct_scan() takes the precision of each observation (one over the variance).