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.

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).

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> .

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.

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.

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>.

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'.

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>.

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> .

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.

Helper functions for coding object-oriented programming with a focus on R6. Includes functions for assertions and testing, looping, and re-usable design patterns including Abstract and Decorator classes.

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.

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).

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.

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>.

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.

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.

To provide a high dimensional grouped variable selection approach for detection of whole-genome SNP effects and SNP-SNP interactions, as described in Fang et al. (2017, under review).

This package provides a tidy approach to analysis of biological sequences. All processing and data-storage functions are heavily optimized to allow the fastest and most efficient data storage.