This package provides an interface to the European Central Bank's Data Portal API, allowing for programmatic retrieval of a vast quantity of statistical data.

Computes relative importance of main and interaction effects. Also, sum of the modified generalized weights is computed. Ibrahim et al. (2022) <doi:10.1134/S1064229322080051>.

Offers procedures to support financial-economic time series modelling and enhanced procedures for computing the investment performance indices of Bacon (2004) <DOI:10.1002/9781119206309>.

Functions, data sets, analyses and examples from the book `An Introduction to Applied Multivariate Analysis with R (Brian S. Everitt and Torsten Hothorn, Springer, 2011).

This package provides functions to create, connect, update and query HSQL databases embedded in Open Document Databases files, as OpenOffice and LibreOffice do.

This package provides a set of functions for reading and writing PC-Axis files, used by different statistical organizations around the globe for data dissemination.

This package predicts the gene-gene interaction network and identifies the direct transcriptional targets of the perturbation using an ODE (Ordinary Differential Equation) based method.

This package supports the analysis of count data exhibiting autoregressive properties, using the Autoregressive Conditional Poisson model (ACP(p,q)) proposed by Heinen (2003).

This is a package for computation and visualization of the empirical attainment function (EAF) for the analysis of random sets in multi-criterion optimization.

This package provides cover-tree and kd-tree fast k-nearest neighbor search algorithms. Related applications including KNN classification, regression and information measures are implemented.

This package provides tools for Independent Component Analysis (ICA) using various algorithms: FastICA, Information-Maximization (Infomax), and Joint Approximate Diagonalization of Eigenmatrices (JADE).

Construct time series for Germany's municipalities (Gemeinden) and districts (Kreise) using a annual crosswalk constructed by the Federal Office for Building and Regional Planning (BBSR).

This package provides select, insert, update, upsert, and delete database operations. Supports PostgreSQL', MySQL', SQLite', and more, and plays nicely with the DBI package.

The goal of dlr is to provide a friendly wrapper around the common pattern of downloading a file if that file does not already exist locally.

Statistical inference for the regression coefficients in high-dimensional linear models with hidden confounders. The Doubly Debiased Lasso method was proposed in <arXiv:2004.03758>.

Count regression models for underdispersed small counts (lambda < 20) based on the three-parameter exponentially weighted Poisson distribution of Ridout & Besbeas (2004) <DOI:10.1191/1471082X04st064oa>.

This package provides tools to set up, train, store, load, investigate and analyze generative neural networks. In particular, functionality for generative moment matching networks is provided.

This package provides functions for calculating the hazard discrimination summary and its standard errors, as described in Liang and Heagerty (2016) <doi:10.1111/biom.12628>.

This package provides a spatial smoothing algorithm based on convolutions of finite rectangular kernels that provides sharp resolution in the presence of high levels of noise.

This package provides a collection of function to solve multiple criteria optimization problems using genetic algorithms (NSGA-II). Also included is a collection of test functions.

In short, this package is a locator for cool, refreshing beverages. It will find and return the nearest location where you can get a cold one.

This package provides functions/methods to accompany the book Quantitative Risk Management: Concepts, Techniques and Tools by Alexander J. McNeil, Ruediger Frey, and Paul Embrechts.

Utilities for training and evaluating text predictors based on Stupid Back-Off N-gram models (Brants et al., 2007, <https://www.aclweb.org/anthology/D07-1090/>).

This package provides routines for Maximum likelihood, Kalman filtering and smoothing, and Bayesian analysis of Normal linear State Space models, also known as Dynamic Linear Models.