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r-assotester
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R package with statistical tests and methods for genetic association studies with emphasis on rare variants and binary (dichotomous) traits
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2025-04-22 |
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r-assist
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A comprehensive package for fitting various non-parametric/semi-parametric linear/nonlinear fixed/mixed smoothing spline models.
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2025-04-22 |
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r-assa
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Functions to model and decompose time series into principal components using singular spectrum analysis (de Carvalho and Rua (2017) <doi:10.1016/j.ijforecast.2015.09.004>; de Carvalho et al (2012) <doi:10.1016/j.econlet.2011.09.007>).
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2025-04-22 |
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r-aspect
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Contains various functions for optimal scaling. One function performs optimal scaling by maximizing an aspect (i.e. a target function such as the sum of eigenvalues, sum of squared correlations, squared multiple correlations, etc.) of the corresponding correlation matrix. Another function performs implements the LINEALS approach for optimal scaling by minimization of an aspect based on pairwise correlations and correlation ratios. The resulting correlation matrix and category scores can be used for further multivariate methods such as structural equation models.
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2025-04-22 |
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r-aspbay
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This package allows to make inference on the properties of causal genetic variants in linkage disequilibrium with genotyped markers. In a first step, we select a subset of variants using a score statistic for affected sib-pairs. In a second step, on the selected subset, we make inference on causal genetic variants in the considered region.
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2025-04-22 |
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r-ash
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David Scott's ASH routines ported from S-PLUS to R.
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2025-04-22 |
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r-arules
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Provides the infrastructure for representing, manipulating and analyzing transaction data and patterns (frequent itemsets and association rules). Also provides C implementations of the association mining algorithms Apriori and Eclat.
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2025-04-22 |
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r-artp2
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Pathway and gene level association test using raw data or summary statistics.
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2025-04-22 |
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r-artp
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For calculating gene and pathway p-values using the Adaptive Rank Truncated Product test.
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2025-04-22 |
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r-ars
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Adaptive Rejection Sampling, Original version.
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2025-04-22 |
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r-arrapply
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High performance variant of apply() for a fixed set of functions. Considerable speedup is a trade-off for universality, user defined functions cannot be used with this package. However, 21 most currently employed functions are available for usage. They can be divided in three types: reducing functions (like mean(), sum() etc., giving a scalar when applied to a vector), mapping function (like normalise(), cumsum() etc., giving a vector of the same length as the input vector) and finally, vector reducing function (like diff() which produces result vector of a length different from the length of input vector). Optional or mandatory additional arguments required by some functions (e.g. norm type for norm() or normalise() functions) can be passed as named arguments in '...'.
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2025-04-22 |
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r-arrangements
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Fast generators and iterators for permutations, combinations and partitions. The iterators allow users to generate arrangements in a memory efficient manner and the generated arrangements are in lexicographical (dictionary) order. Permutations and combinations can be drawn with/without replacement and support multisets. It has been demonstrated that 'arrangements' outperforms most of the existing packages of similar kind. Some benchmarks could be found at <https://randy3k.github.io/arrangements/articles/benchmark.html>.
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2025-04-22 |
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r-armspp
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An efficient 'Rcpp' implementation of the Adaptive Rejection Metropolis Sampling (ARMS) algorithm proposed by Gilks, W. R., Best, N. G. and Tan, K. K. C. (1995) <doi:10.2307/2986138>. This allows for sampling from a univariate target probability distribution specified by its (potentially unnormalised) log density.
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2025-04-22 |
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r-aricode
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Implements an efficient O(n) algorithm based on bucket-sorting for fast computation of standard clustering comparison measures. Available measures include adjusted Rand index (ARI), normalized information distance (NID), normalized mutual information (NMI), adjusted mutual information (AMI), normalized variation information (NVI) and entropy, as described in Vinh et al (2009) <doi:10.1145/1553374.1553511>.
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2025-04-22 |
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r-argon2
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Utilities for secure password hashing via the argon2 algorithm. It is a relatively new hashing algorithm and is believed to be very secure. The 'argon2' implementation included in the package is the reference implementation. The package also includes some utilities that should be useful for digest authentication, including a wrapper of 'blake2b'. For similar R packages, see sodium and 'bcrypt'. See <https://en.wikipedia.org/wiki/Argon2> or <https://eprint.iacr.org/2015/430.pdf> for more information.
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2025-04-22 |
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r-aqr
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This R extension provides methods to use a standalone ActiveQuant Master Server from within R. Currently available features include fetching and storing historical data, receiving and sending live data. Several utility methods for simple data transformations are included, too. For support requests, please join the mailing list at https://r-forge.r-project.org/mail/?group_id=1518
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2025-04-22 |
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r-apple
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Approximate Path for Penalized Likelihood Estimators for Generalized Linear Models penalized by LASSO or MCP
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2025-04-22 |
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r-apml0
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Fit linear, logistic and Cox models regularized with L0, lasso (L1), elastic-net (L1 and L2), or net (L1 and Laplacian) penalty, and their adaptive forms, such as adaptive lasso / elastic-net and net adjusting for signs of linked coefficients. It solves L0 penalty problem by simultaneously selecting regularization parameters and the number of non-zero coefficients. This augmented and penalized minimization method provides an approximation solution to the L0 penalty problem, but runs as fast as L1 regularization problem. The package uses one-step coordinate descent algorithm and runs extremely fast by taking into account the sparsity structure of coefficients. It could deal with very high dimensional data and has superior selection performance.
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2025-04-22 |
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r-apcluster
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Implements Affinity Propagation clustering introduced by Frey and Dueck (2007) <DOI:10.1126/science.1136800>. The algorithms are largely analogous to the 'Matlab' code published by Frey and Dueck. The package further provides leveraged affinity propagation and an algorithm for exemplar-based agglomerative clustering that can also be used to join clusters obtained from affinity propagation. Various plotting functions are available for analyzing clustering results.
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2025-04-22 |
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r-anytime
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Convert input in any one of character, integer, numeric, factor, or ordered type into 'POSIXct' (or 'Date') objects, using one of a number of predefined formats, and relying on Boost facilities for date and time parsing.
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2025-04-22 |
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r-antiword
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Wraps the 'AntiWord' utility to extract text from Microsoft Word documents. The utility only supports the old 'doc' format, not the new xml based 'docx' format. Use the 'xml2' package to read the latter.
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2025-04-22 |
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r-anmc
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Computationally efficient method to estimate orthant probabilities of high-dimensional Gaussian vectors. Further implements a function to compute conservative estimates of excursion sets under Gaussian random field priors.
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2025-04-22 |
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r-anacoda
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Is a collection of models to analyze genome scale codon data using a Bayesian framework. Provides visualization routines and checkpointing for model fittings. Currently published models to analyze gene data for selection on codon usage based on Ribosome Overhead Cost (ROC) are: ROC (Gilchrist et al. (2015) <doi:10.1093/gbe/evv087>), and ROC with phi (Wallace & Drummond (2013) <doi:10.1093/molbev/mst051>). In addition 'AnaCoDa' contains three currently unpublished models. The FONSE (First order approximation On NonSense Error) model analyzes gene data for selection on codon usage against of nonsense error rates. The PA (PAusing time) and PANSE (PAusing time + NonSense Error) models use ribosome footprinting data to analyze estimate ribosome pausing times with and without nonsense error rate from ribosome footprinting data.
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2025-04-22 |
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r-amore
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This package was born to release the TAO robust neural network algorithm to the R users. It has grown and I think it can be of interest for the users wanting to implement their own training algorithms as well as for those others whose needs lye only in the "user space".
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2025-04-22 |
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r-ameco
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Annual macro-economic database provided by the European Commission.
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2025-04-22 |
