Permutation based Kolmogorov-Smirnov test for paired samples. The test was proposed by Wang W.S., Amsler C. and Schmidt, P. (2025) <doi:10.1007/s00181-025-02779-0>.

Generates chronological and ordered p-plots for data vectors or vectors of p-values. The p-plot visualizes the evolution of the p-value of a significance test across the sampled data. It allows for assessing the consistency of the observed effects, for detecting the presence of potential moderator variables, and for estimating the influence of outlier values on the observed results. For non-significant findings, it can diagnose patterns indicative of underpowered study designs. The p-plot can thus either back the binary accept-vs-reject decision of common null-hypothesis significance tests, or it can qualify this decision and stimulate additional empirical work to arrive at more robust and replicable statistical inferences.

Linear and nonlinear regression
        methods based on Partial Least Squares and Penalization
        Techniques. Model parameters are selected via cross-validation,
        and confidence intervals ans tests for the regression
        coefficients can be conducted via jackknifing. 
        The method is described and applied to simulated and experimental 
        data in Kraemer et al. (2008) <doi:10.1016/j.chemolab.2008.06.009>.

Implements data processing described in <doi:10.1126/sciadv.abk3283>
    to align modern differentially private data with formatting of older US Census
    data releases. The primary goal is to read in Census Privacy Protected Microdata
    Files data in a reproducible way. This includes tools for aggregating to relevant
    levels of geography by creating geographic identifiers which match the US Census
    Bureau's numbering. Additionally, there are tools for grouping race numeric
    identifiers into categories, consistent with OMB (Office of Management and Budget)
    classifications. Functions exist for downloading and linking to existing
    sources of privacy protected microdata.