This package provides tools for using genetic markers, stable isotope data, and habitat suitability data to calculate posterior probabilities of breeding origin of migrating birds.

Enables chat completion and text annotation with local and OpenAI <https://openai.com/> language models, supporting batch processing, multiple annotators, and consistent output formats.

Computes intervention in prediction measure for assessing variable importance for random forests. See details at I. Epifanio (2017) <DOI:10.1186/s12859-017-1650-8>.

Fast extrapolation of univariate and multivariate time features using K-Nearest Neighbors. The compact set of hyper-parameters is tuned via grid or random search.

k Nearest Neighbors with variable selection, combine grid search and forward selection to achieve variable selection in order to improve k Nearest Neighbors predictive performance.

Computation of various Markovian models for categorical data including homogeneous Markov chains of any order, MTD models, Hidden Markov models, and Double Chain Markov Models.

This package provides functionality for Bayesian analysis of replication studies using power prior approaches (Pawel et al., 2023) <doi:10.1007/s11749-023-00888-5>.

This package contains logic for computing the statistical association of variable groups, i.e., gene sets, with respect to the principal components of genomic data.

An extension of the Fisher Scoring Algorithm to combine PLS regression with GLM estimation in the multivariate context. Covariates can also be grouped in themes.

This package provides the spatial sign correlation and the two-stage spatial sign correlation as well as a one-sample test for the correlation coefficient.

This package implements the Sliding Window Discrete Fourier Transform (SWDFT). Also provides statistical methods based on the SWDFT, and graphical tools to display the outputs.

This package provides tools for visibility analysis in geospatial data. It offers functionality to perform isovist calculations, using arbitrary geometries as both viewpoints and occluders.

The goal of the rbrsa package is to provide automated access to banking sector data from the Turkish Banking Regulation and Supervision Agency (BRSA, known as BDDK in Turkish). The package retrieves tables from two distinct publication portals maintained by the BRSA: The Monthly Bulletin Portal <https://www.bddk.org.tr/bultenaylik> and The FinTurk Data System <https://www.bddk.org.tr/BultenFinturk>.

This package performs penalized quantile regression with LASSO, elastic net, SCAD and MCP penalty functions including group penalties. In addition, offers a group penalty that provides consistent variable selection across quantiles. Provides a function that automatically generates lambdas and evaluates different models with cross validation or BIC, including a large p version of BIC. Below URL provides a link to a work in progress vignette.

An R interface to Weka (Version 3.9.3). Weka is a collection of machine learning algorithms for data mining tasks written in Java, containing tools for data pre-processing, classification, regression, clustering, association rules, and visualization. Package RWeka contains the interface code, the Weka jar is in a separate package RWekajars'. For more information on Weka see <https://www.cs.waikato.ac.nz/ml/weka/>.

Maximum likelihood estimation for univariate reducible stochastic differential equation models. Discrete, possibly noisy observations, not necessarily evenly spaced in time. Can fit multiple individuals/units with global and local parameters, by fixed-effects or mixed-effects methods. Ref.: Garcia, O. (2019) "Estimating reducible stochastic differential equations by conversion to a least-squares problem", Computational Statistics 34(1): 23-46, <doi:10.1007/s00180-018-0837-4>.

This package contains functions for simulating the linear fractional stable motion according to the algorithm developed by Mazur and Otryakhin <doi:10.32614/RJ-2020-008> based on the method from Stoev and Taqqu (2004) <doi:10.1142/S0218348X04002379>, as well as functions for estimation of parameters of these processes introduced by Mazur, Otryakhin and Podolskij (2018) <arXiv:1802.06373>, and also different related quantities.

The atSNP package performs affinity tests of motif matches with the SNP (single nucleotide polymorphism) or the reference genomes and SNP-led changes in motif matches.

This package provides a package to analyze oligonucleotide arrays (expression/SNP/tiling/exon) at probe-level. It currently supports Affymetrix (CEL files) and NimbleGen arrays (XYS files).

This package provides useful functions to edit ggplot object (e.g., setting fonts for theme and layers, adding rounded rectangle as background for each of the legends).

Designed to enable simultaneous substitution in strings in a safe fashion. Safe means it does not rely on placeholders (which can cause errors in same length matches).

This package provides methods and functions for fitting maximum likelihood models in R. This package modifies and extends the mle classes in the stats4 package.

This package provides functions for latent class analysis, short time Fourier transform, fuzzy clustering, support vector machines, shortest path computation, bagged clustering, naive Bayes classifier, and more.

This package provides fast and memory efficient methods for truncated singular and eigenvalue decompositions, as well as for principal component analysis of large sparse or dense matrices.