This package provides R6 classes, methods and utilities to construct, analyze, summarize, and visualize regression models.

This package provides an R interface to a C implementation of Fast Iterative Filtering (FIF) for decomposing a univariate signal into intrinsic mode functions (IMFs) and a residual. The package uses Fast Fourier Transform library FFTW, if found. If not, it provides instructions to install it for your OS. This is recommended, as R's internal fft(), while avoiding external FFT dependencies, is two orders of magnitude slower. See vignette Installing FFTW for RFIF for RFIF installation instructions.

Conversion between attitude representations: DCM, Euler angles, Quaternions, and Euler vectors. Plus conversion between 2 Euler angle set types (xyx, yzy, zxz, xzx, yxy, zyz, xyz, yzx, zxy, xzy, yxz, zyx). Fully vectorized code, with warnings/errors for Euler angles (singularity, out of range, invalid angle order), DCM (orthogonality, not proper, exceeded tolerance to unity determinant) and Euler vectors(not unity). Also quaternion and other useful functions. Based on SpinCalc by John Fuller and SpinConv by Paolo de Leva.

This package provides tools for regression-based Boolean rule inference in artificial intelligence studies. The package fits ridge regression models on conjunction expansions and composes interpretable rule sets. Parallel execution is supported for multi-CPU environments.

Load data from Yandex Direct API V5 <https://yandex.ru/dev/direct/doc/dg/concepts/about-docpage> into R. Provide function for load lists of campaings, ads, keywords and other objects from Yandex Direct account. Also you can load statistic from API Reports Service <https://yandex.ru/dev/direct/doc/reports/reports-docpage>. And allows keyword bids management.

This package provides tools for the analysis of reverse-phase protein arrays (RPPAs), which are also known as tissue lysate arrays or simply lysate arrays'. The package's primary purpose is to input a set of quantification files representing dilution series of samples and control points taken from scanned RPPA slides and determine a relative log concentration value for each valid dilution series present in each slide and provide graphical visualization of the input and output data and their relationships. Other optional features include generation of quality control scores for judging the quality of the input data, spatial adjustment of sample points based on controls added to the slides, and various types of normalization of calculated values across a set of slides. The package was derived from a previous package named SuperCurve. For a detailed description of data inputs and outputs, usage information, and a list of related papers describing methods used in the package please review the vignette Guide_to_RPPASPACE'. RPPA SPACE: an R package for normalization and quantitation of Reverse-Phase Protein Array data'. Bioinformatics Nov 15;38(22):5131-5133. <doi: 10.1093/bioinformatics/btac665>.

This package performs goodness of fits tests for both high and low-dimensional linear models. It can test for a variety of model misspecifications including nonlinearity and heteroscedasticity. In addition one can test the significance of potentially large groups of variables, and also produce p-values for the significance of individual variables in high-dimensional linear regression.

Show physics, math and engineering students how an ODE solver is made and how effective R classes can be for the construction of the equations that describe natural phenomena. Inspiration for this work comes from the book on "Computer Simulations in Physics" by Harvey Gould, Jan Tobochnik, and Wolfgang Christian. Book link: <http://www.compadre.org/osp/items/detail.cfm?ID=7375>.

Radioactive doses estimation using individual chromosomal aberrations information. See Higueras M, Puig P, Ainsbury E, Rothkamm K. (2015) <doi:10.1088/0952-4746/35/3/557>.

Computes linear Bayesian spectral estimates from multirate data for second-order stationary time series. Provides credible intervals and methods for plotting various spectral estimates. Please see the paper `Should we sample a time series more frequently? (doi below) for a full description of and motivation for the methodology.

This package provides a high-performance interface for calculating string similarities and distances, leveraging the efficient library RapidFuzz <https://github.com/rapidfuzz/rapidfuzz-cpp>. This package integrates the C++ implementation, allowing R users to access cutting-edge algorithms for fuzzy matching and text analysis. Supported metrics include Levenshtein, Damerau-Levenshtein, Hamming, Jaro, Jaro-Winkler, Longest Common Subsequence (LCS), Optimal String Alignment (OSA), Indel, Prefix, and Postfix distances and similarities, as well as multiple fuzzy matching ratios.

Mixture Composer (Biernacki (2015) <https://inria.hal.science/hal-01253393v1>) is a project to perform clustering using mixture models with heterogeneous data and partially missing data. Mixture models are fitted using a SEM algorithm. It includes 8 models for real, categorical, counting, functional and ranking data.

Fit statistical models based on the Dawid-Skene model - Dawid and Skene (1979) <doi:10.2307/2346806> - to repeated categorical rating data. Full Bayesian inference for these models is supported through the Stan modelling language. rater also allows the user to extract and plot key parameters of these models.

External jars required for package RKEA.

Convert digital images to spatially referenced SpatRaster objects, as defined by the terra package, using coordinates from supported spatial input classes. Supported inputs include numeric coordinate vectors and objects from the sf', terra and stars packages. The main function is an S3 generic, allowing other packages to extend support to additional spatial classes.

This package provides a method for performing joint registration and functional principal component analysis for curves (functional data) that are generated from exponential family distributions. This mainly implements the algorithms described in Wrobel et al. (2019) <doi:10.1111/biom.12963> and further adapts them to potentially incomplete curves where (some) curves are not observed from the beginning and/or until the end of the common domain. Curve registration can be used to better understand patterns in functional data by separating curves into phase and amplitude variability. This software handles both binary and continuous functional data, and is especially applicable in accelerometry and wearable technology.

This web client interfaces Unpaywall <https://unpaywall.org/products/api>, formerly oaDOI, a service finding free full-texts of academic papers by linking DOIs with open access journals and repositories. It provides unified access to various data sources for open access full-text links including Crossref and the Directory of Open Access Journals (DOAJ). API usage is free and no registration is required.

The ropenblas package (<https://prdm0.github.io/ropenblas/>) is useful for users of any GNU/Linux distribution. It will be possible to download, compile and link the OpenBLAS library (<https://www.openblas.net/>) with the R language, always by the same procedure, regardless of the GNU/Linux distribution used. With the ropenblas package it is possible to download, compile and link the latest version of the OpenBLAS library even the repositories of the GNU/Linux distribution used do not include the latest versions of OpenBLAS'. If of interest, older versions of the OpenBLAS library may be considered. Linking R with an optimized version of BLAS (<https://netlib.org/blas/>) may improve the computational performance of R code. The OpenBLAS library is an optimized implementation of BLAS that can be easily linked to R with the ropenblas package.

This package provides templates and a working example for runtime Single Instruction Multiple Data ('SIMD') dispatch in C code used by R packages. Packages can stage scalar and architecture-specific kernel objects during configuration, then select a compiled and CPU-supported implementation at runtime through guarded function pointers. The package also vendors the header-only SIMDe library for downstream packages through the LinkingTo field.

Plots the Receiver Operating Characteristics Surface for high-throughput class-skewed data, calculates the Volume under the Surface (VUS) and the FDR-Controlled Area Under the Curve (FCAUC), and conducts tests to compare two ROC surfaces. Computes eROC curve and the corresponding AUC for imperfect reference standard.

For a given suit, if you add up the number of cards that you hold, plus the number that has been played so far, you can easily determine the number that remains in the combined hands of your three opponents. You can also determine the ("special") card of highest rank of the remaining cards for that suit. At some point, you notice that a certain opponent discards that special card. What can you infer about his holding in that suit? A series of simulation studies are reported here that allows a quantitative inference based on the conditional probability, given that the opponent has the special card. The same procedure is also used for the conditional probability, given that the opponent does not have the special card.

REDUCE is a portable general-purpose computer algebra system supporting scalar, vector, matrix and tensor algebra, symbolic differential and integral calculus, arbitrary precision numerical calculations and output in LaTeX format. REDUCE is based on Lisp and is available on the two dialects Portable Standard Lisp ('PSL') and Codemist Standard Lisp ('CSL'). The redcas package provides an interface for executing arbitrary REDUCE code interactively from R', returning output as character vectors. R code and REDUCE code can be interspersed. It also provides a specialized function for calling the REDUCE feature for solving systems of equations, returning the output as an R object designed for the purpose. A further specialized function uses REDUCE features to generate LaTeX output and post-processes this for direct use in LaTeX documents, e.g. using Sweave'.

Some heavily used base R functions are reconstructed to also be compliant to data.table objects. Also, some general helper functions that could be of interest for working with data.table objects are included.

An easy way to analyze international large-scale assessments and surveys in education or any other dataset that includes replicated weights (Balanced Repeated Replication (BRR) weights, Jackknife replicate weights,...) while also allowing for analysis with multiply imputed variables (plausible values). It supports the estimation of univariate statistics (e.g. mean, variance, standard deviation, quantiles), frequencies, correlation, linear regression and any other model already implemented in R that takes a data frame and weights as parameters. It also includes options to prepare the results for publication, following the table formatting standards of the Organization for Economic Cooperation and Development (OECD).