An R API wrapper for the 'Hystreet' project <https://hystreet.com>. 'Hystreet' provides pedestrian counts in different cities in Germany.

Up-to-date data from the 'Unicode CLDR Project' (where 'CLDR'
    stands for 'Common Locale Data Repository') are available here as a series
    of easy-to-parse datasets. Several functions are provided for extracting
    key elements from the tabular datasets.

Provides functions to work with 'incidence2' objects, including a
  simplified interface for trend fitting and peak estimation. This package is
  part of the RECON (<https://www.repidemicsconsortium.org/>) toolkit for 
  outbreak analysis (<https://www.reconverse.org/).

Contains data frames and functions used in the book "An Introduction to Acceptance Sampling and SPC with R". This book is available electronically at <https://bookdown.org/>. A physical copy will be published by CRC Press.

Simulate and implement early phase two-stage adaptive dose-finding design for binary and quasi-continuous toxicity endpoints. See Chiuzan et al. (2018) for further reading <DOI:10.1080/19466315.2018.1462727>.

Calculate false ring proportions from data frames of intra annual 
  density fluctuations.

Provides functions to conduct a model-agnostic asymptotic hypothesis test for the identification of interaction effects in black-box machine learning models. The null hypothesis assumes that a given set of covariates does not contribute to interaction effects in the prediction model. The test statistic is based on the difference of variances of partial dependence functions (Friedman (2008) <doi:10.1214/07-AOAS148> and Welchowski (2022) <doi:10.1007/s13253-021-00479-7>) with respect to the original black-box predictions and the predictions under the null hypothesis. The hypothesis test can be applied to any black-box prediction model, and the null hypothesis of the test can be flexibly specified according to the research question of interest. Furthermore, the test is computationally fast to apply as the null distribution does not require resampling or refitting black-box prediction models.