This package provides a test for the well-specification of the linear instrumental variable model. The test is based on trying to predict the residuals of a two-stage least-squares regression using a random forest. Details can be found in Scheidegger, Londschien and Bühlmann (2025) "A residual prediction test for the well-specification of linear instrumental variable models" <doi:10.48550/arXiv.2506.12771>.

This package provides a tool for undergraduate and graduate courses in open-channel hydraulics. Provides functions for computing normal and critical depths, steady-state water surface profiles (e.g. backwater curves) and unsteady flow computations (e.g. flood wave routing) as described in Koohafkan MC, Younis BA (2015). "Open-channel computation with R." The R Journal, 7(2), 249â 262. <doi: 10.32614/RJ-2015-034>.

Minimally adjust the values of numerical records in a data.frame, such that each record satisfies a predefined set of equality and/or inequality constraints. The constraints can be defined using the validate package. The core algorithms have recently been moved to the lintools package, refer to lintools for a more basic interface and access to a version of the algorithm that works with sparse matrices.

Tools to access data from the data web service of the OeNB, https://www.oenb.at/en/Statistics/User-Defined-Tables/webservice.html.

This package provides functions and an RStudio add-in that search a BibTeX or BibLaTeX file to create and insert formatted Markdown citations into the current document.

This package provides a general framework for high-dimensional undirected graph estimation. It integrates data preprocessing, neighborhood screening, graph estimation, and model selection techniques into a pipeline.

Wrapper around the Canadian Mortgage and Housing Corporation (CMHC) web interface. It enables programmatic and reproducible access to a wide variety of housing data from CMHC.

This package provides functions to manage databases: select, update, insert, and delete records, list tables, backup tables as CSV files, and import CSV files as tables.

The DYMO package provides tools for multi-feature time-series forecasting using a Dynamic Mode Decomposition (DMD) model combined with conformal predictive sampling for uncertainty quantification.

This package provides functions for performing (external) multidimensional unfolding. Restrictions (fixed coordinates or model restrictions) are available for both row and column coordinates in all combinations.

This package provides function to apply "Group sequential enrichment design incorporating subgroup selection" (GSED) method proposed by Magnusson and Turnbull (2013) <doi:10.1002/sim.5738>.

Search and download Swiss data and metadata from the I14Y interoperability platform of Switzerland using its public APIs <https://www.i14y.admin.ch/api/index.html>.

This package provides instrumental variable estimation of treatment effects when both the endogenous treatment and its instrument are binary. Applicable to both binary and continuous outcomes.

This package contains 128 palettes from Color Lisa. All palettes are based on masterpieces from the worlds greatest artists. For more information, see <http://colorlisa.com/>.

This package provides functions for performing and visualizing Local Fisher Discriminant Analysis(LFDA), Kernel Fisher Discriminant Analysis(KLFDA), and Semi-supervised Local Fisher Discriminant Analysis(SELF).

Perform missing value imputation for biological data using the random forest algorithm, the imputation aim to keep the original mean and standard deviation consistent after imputation.

Noninferiority tests for difference in failure rates at a prespecified control rate or prespecified time. For details, see Fay and Follmann, 2016 <DOI:10.1177/1740774516654861>.

Enables the creation of object pools, which make it less computationally expensive to fetch a new object. Currently the only supported pooled objects are DBI connections.

Estimates QAPE using bootstrap procedures. The residual, parametric and double bootstrap is used. The test of normality using Cholesky decomposition is added. Y pop is defined.

Computes the sBIC for various singular model collections including: binomial mixtures, factor analysis models, Gaussian mixtures, latent forests, latent class analyses, and reduced rank regressions.

Interface to TensorFlow IO', Datasets and filesystem extensions maintained by `TensorFlow SIG-IO` <https://github.com/tensorflow/community/blob/master/sigs/io/CHARTER.md>.

Access data from Land Registry Open Data <http://landregistry.data.gov.uk/> through SPARQL queries. uklr supports the house price index, transaction and price paid data.

This package provides an easy to calculate local variable importance measure based on Ceteris Paribus profile and global variable importance measure based on Partial Dependence Profiles.

Estimation, lag selection, diagnostic testing, forecasting, causality analysis, forecast error variance decomposition and impulse response functions of VAR models and estimation of SVAR and SVEC models.