Constructs optimal policy trees which provide a rule-based treatment prescription policy.
 Input is covariate and reward data, where, typically, the rewards will be doubly robust reward estimates.
 This package aims to construct optimal policy trees more quickly than the existing 'policytree' package and
 is intended to be used alongside that package.
 For more details see Cussens, Hatamyar, Shah and Kreif (2025) <doi:10.48550/arXiv.2506.15435>.

Finds the critical sample size ("critical point of stability") for a 
    correlation to stabilize in Schoenbrodt and Perugini's definition of 
    sequential stability (see <doi:10.1016/j.jrp.2013.05.009>).

'FASTQC' is the most widely used tool for evaluating the quality of high throughput sequencing data.  
    It produces, for each sample, an html report and a compressed file containing the raw data. 
    If you have hundreds of samples, you are not going to open up each 'HTML' page. 
    You need some way of looking at these data in aggregate. 
    'fastqcr' Provides helper functions to easily parse, aggregate and analyze 
    'FastQC' reports for large numbers of samples. It provides a convenient solution for building 
    a 'Multi-QC' report, as well as, a 'one-sample' report with result interpretations.

New and faster implementations for quantile quantile plots. 
    The package also includes a function to prune data for quantile quantile 
    plots. This can drastically reduce the running time for large samples, 
    for 100 million samples, you can expect a factor 80X speedup.

Fast estimation algorithms to implement the Quantile Regression with Selection estimator and the multiplicative Bootstrap for inference. This estimator can be used to estimate models that feature sample selection and heterogeneous effects in cross-sectional data. For more details, see Arellano and Bonhomme (2017) <doi:10.3982/ECTA14030> and Pereda-Fernández (2024) <doi:10.48550/arXiv.2402.16693>.

Data sets and utilities to accompany the second edition of
    "Foundations and Applications of Statistics: an Introduction
    using R" (R Pruim, published by AMS, 2017), a text covering
    topics from probability and mathematical statistics at an advanced
    undergraduate level.  R is integrated throughout, and access to all
    the R code in the book is provided via the snippet() function.