It is devoted to Cramer-von Mises goodness-of-fit tests. It implements three statistical methods based on Cramer-von Mises statistics to estimate and test a regression model.

Estimation of Difference-in-Differences (DiD) estimators from de Chaisemartin et al. (2025) <doi:10.48550/arXiv.2405.04465> in Heterogeneous Adoption Designs with Quasi Untreated Groups.

This package provides a graphical user interface (GUI) to the functions implemented in the R package DQAstats'. Publication: Mang et al. (2021) <doi:10.1186/s12911-022-01961-z>.

Simulates and computes the (maximum) likelihood of a dynamical model of island biota assembly through speciation, immigration and extinction. See Valente et al. (2015) <doi:10.1111/ele.12461>.

Builds contingency tables that cross-tabulate multiple categorical variables and also calculates various summary measures. Export to a variety of formats is supported, including: HTML', LaTeX', and Excel'.

Access to data on European Union laws and court decisions made easy with pre-defined SPARQL queries and GET requests. See Ovadek (2021) <doi:10.1080/2474736X.2020.1870150> .

Misc functions programmed by Eduard Szöcs. Provides read_regnie() to read gridded precipitation data from German Weather Service (DWD, see <http://www.dwd.de/> for more information).

This package provides raw and curated data on the codes, classification and conservation status of freshwater fishes in British Columbia. Marine fishes will be added in a future release.

Wrapper around geom_histogram() of ggplot2 to plot the histogram of a numeric vector. This is especially useful, since qplot() was deprecated in ggplot2 3.4.0.

Generates synthetic time series based on various univariate time series models including MAR and ARIMA processes. Kang, Y., Hyndman, R.J., Li, F.(2020) <doi:10.1002/sam.11461>.

This package provides a Shiny app allowing to convert HTML code to R code (e.g. <span>Hello</span> to tags$span("Hello")'), for usage in a Shiny UI.

Curve Fitting of monotonic(sigmoidal) & non-monotonic(J-shaped) dose-response data. Predicting mixture toxicity based on reference models such as concentration addition', independent action', and generalized concentration addition'.

Multivariate functional principal component analysis via fast covariance estimation for multivariate sparse functional data or longitudinal data proposed by Li, Xiao, and Luo (2020) <doi: 10.1002/sta4.245>.

The algorithms implemented here are used to detect the community structure of a network. These algorithms follow different approaches, but are all based on the concept of modularity maximization.

An implementation of the Naive Bayes Classifier (NBC) algorithm used for Verbal Autopsy (VA) built on code from Miasnikof et al (2015) <DOI:10.1186/s12916-015-0521-2>.

This package contains the following 5 nonparametric hypothesis tests: The Sign Test, The 2 Sample Median Test, Miller's Jackknife Procedure, Cochran's Q Test, & The Stuart-Maxwell Test.

Factorize binary matrices into rank-k components using the logistic function in the updating process. See e.g. Tomé et al (2015) <doi:10.1007/s11045-013-0240-9> .

Structured fusion Lasso penalized estimation of multi-state models with the penalty applied to absolute effects and absolute effect differences (i.e., effects on transition-type specific hazard rates).

This package provides tools for the test for the comparison of survival curves, the evaluation of the goodness-of-fit and the predictive capacity of the proportional hazards model.

Estimation of various biodiversity indices and related (dis)similarity measures based on individual-based (abundance) data or sampling-unit-based (incidence) data taken from one or multiple communities/assemblages.

This package provides functionality to fit and simulate from stationary vine copula models for time series, see Nagler et al. (2022) <doi:10.1016/j.jeconom.2021.11.015>.

This package provides pseudo-likelihood methods for empirically analyzing common signaling games in international relations as described in Crisman-Cox and Gibilisco (2019) <doi:10.1017/psrm.2019.58>.

Spatial coverage sampling and random sampling from compact geographical strata created by k-means. See Walvoort et al. (2010) <doi:10.1016/j.cageo.2010.04.005> for details.

Data and functions to support Bayesian and frequentist inference and decision making for the Coursera Specialization "Statistics with R". See <https://github.com/StatsWithR/statsr> for more information.