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r-trapezoid
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public |
The trapezoid package provides 'dtrapezoid', 'ptrapezoid', 'qtrapezoid', and 'rtrapezoid' functions for the trapezoidal distribution.
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2025-03-25 |
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r-transurv
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A latent, quasi-independent truncation time is assumed to be linked with the observed dependent truncation time, the event time, and an unknown transformation parameter via a structural transformation model. The transformation parameter is chosen to minimize the conditional Kendall's tau (Martin and Betensky, 2005) <doi:10.1198/016214504000001538> or the regression coefficient estimates (Jones and Crowley, 1992) <doi:10.2307/2336782>. The marginal distribution for the truncation time and the event time are completely left unspecified. The methodology is applied to survival curve estimation and regression analysis.
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2025-03-25 |
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r-transport
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Solve optimal transport problems. Compute Wasserstein distances (a.k.a. Kantorovitch, Fortet--Mourier, Mallows, Earth Mover's, or minimal L_p distances), return the corresponding transference plans, and display them graphically. Objects that can be compared include grey-scale images, (weighted) point patterns, and mass vectors.
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2025-03-25 |
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r-tracerer
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'BEAST2' (<https://www.beast2.org>) is a widely used Bayesian phylogenetic tool, that uses DNA/RNA/protein data and many model priors to create a posterior of jointly estimated phylogenies and parameters. 'Tracer' (<https://github.com/beast-dev/tracer/>) is a GUI tool to parse and analyze the files generated by 'BEAST2'. This package provides a way to parse and analyze 'BEAST2' input files without active user input, but using R function calls instead.
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2025-03-25 |
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r-tpmsm
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Estimation of transition probabilities for the illness-death model and or the three-state progressive model.
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2025-03-25 |
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r-tp.idm
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Estimation of transition probabilities for the illness-death model. Both the Aalen-Johansen estimator for a Markov model and a novel non-Markovian estimator by de Una-Alvarez and Meira-Machado (2015) <doi:10.1111/biom.12288>, see also Balboa and de Una-Alvarez (2018) <doi:10.18637/jss.v083.i10>, are included.
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2025-03-25 |
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r-touch
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R implementation of the software tools developed in the H-CUP (Healthcare Cost and Utilization Project) <https://www.hcup-us.ahrq.gov> and AHRQ (Agency for Healthcare Research and Quality) <https://www.ahrq.gov>. It currently contains functions for mapping ICD-9 codes to the AHRQ comorbidity measures and translating ICD-9 (resp. ICD-10) codes to ICD-10 (resp. ICD-9) codes based on GEM (General Equivalence Mappings) from CMS (Centers for Medicare and Medicaid Services).
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2025-03-25 |
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r-topmodel
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Set of hydrological functions including an R implementation of the hydrological model TOPMODEL, which is based on the 1995 FORTRAN version by Keith Beven. From version 0.7.0, the package is put into maintenance mode.
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2025-03-25 |
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r-topicmodels
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Provides an interface to the C code for Latent Dirichlet Allocation (LDA) models and Correlated Topics Models (CTM) by David M. Blei and co-authors and the C++ code for fitting LDA models using Gibbs sampling by Xuan-Hieu Phan and co-authors.
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2025-03-25 |
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r-tokenizers.bpe
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Unsupervised text tokenizer focused on computational efficiency. Wraps the 'YouTokenToMe' library <https://github.com/VKCOM/YouTokenToMe> which is an implementation of fast Byte Pair Encoding (BPE) <https://aclanthology.org/P16-1162/>.
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2025-03-25 |
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r-tokenbrowser
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Create browsers for reading full texts from a token list format. Information obtained from text analyses (e.g., topic modeling, word scaling) can be used to annotate the texts.
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2025-03-25 |
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r-tmvnsim
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Importance sampling from the truncated multivariate normal using the GHK (Geweke-Hajivassiliou-Keane) simulator. Unlike Gibbs sampling which can get stuck in one truncation sub-region depending on initial values, this package allows truncation based on disjoint regions that are created by truncation of absolute values. The GHK algorithm uses simple Cholesky transformation followed by recursive simulation of univariate truncated normals hence there are also no convergence issues. Importance sample is returned along with sampling weights, based on which, one can calculate integrals over truncated regions for multivariate normals.
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2025-03-25 |
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r-tmg
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Random number generation of truncated multivariate Gaussian distributions using Hamiltonian Monte Carlo. The truncation is defined using linear and/or quadratic polynomials.
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2025-03-25 |
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r-tmcn
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A Text mining toolkit for Chinese, which includes facilities for Chinese string processing, Chinese NLP supporting, encoding detecting and converting. Moreover, it provides some functions to support 'tm' package in Chinese.
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2025-03-25 |
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r-tmb
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With this tool, a user should be able to quickly implement complex random effect models through simple C++ templates. The package combines 'CppAD' (C++ automatic differentiation), 'Eigen' (templated matrix-vector library) and 'CHOLMOD' (sparse matrix routines available from R) to obtain an efficient implementation of the applied Laplace approximation with exact derivatives. Key features are: Automatic sparseness detection, parallelism through 'BLAS' and parallel user templates.
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2025-03-25 |
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r-tis
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Functions and S3 classes for time indexes and time indexed series, which are compatible with FAME frequencies.
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2025-03-25 |
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r-tinflex
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A universal non-uniform random number generator for quite arbitrary distributions with piecewise twice differentiable densities.
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2025-03-25 |
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r-timsac
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Functions for statistical analysis, prediction and control of time series based mainly on Akaike and Nakagawa (1988) <ISBN 978-90-277-2786-2>.
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2025-03-25 |
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r-timetools
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Objects to manipulate sequential and seasonal time series. Sequential time series based on time instants and time durations are handled. Both can be regularly or unevenly spaced (overlapping durations are allowed). Only POSIX* format are used for dates and times. The following classes are provided : 'POSIXcti', 'POSIXctp', 'TimeIntervalDataFrame', 'TimeInstantDataFrame', 'SubtimeDataFrame' ; methods to switch from a class to another and to modify the time support of series (hourly time series to daily time series for instance) are also defined. Tools provided can be used for instance to handle environmental monitoring data (not always produced on a regular time base).
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2025-03-25 |
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r-timereg
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Programs for Martinussen and Scheike (2006), `Dynamic Regression Models for Survival Data', Springer Verlag. Plus more recent developments. Additive survival model, semiparametric proportional odds model, fast cumulative residuals, excess risk models and more. Flexible competing risks regression including GOF-tests. Two-stage frailty modelling. PLS for the additive risk model. Lasso in the 'ahaz' package.
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2025-03-25 |
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r-timechange
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Efficient routines for manipulation of date-time objects while accounting for time-zones and daylight saving times. The package includes utilities for updating of date-time components (year, month, day etc.), modification of time-zones, rounding of date-times, period addition and subtraction etc. Parts of the 'CCTZ' source code, released under the Apache 2.0 License, are included in this package. See <https://github.com/google/cctz> for more details.
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2025-03-25 |
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r-tiff
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Functions to read, write and display bitmap images stored in the TIFF format. It can read and write both files and in-memory raw vectors, including native image representation.
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2025-03-25 |
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r-threearmedtrials
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Design and analyze three-arm non-inferiority or superiority trials which follow a gold-standard design, i.e. trials with an experimental treatment, an active, and a placebo control. Method for the following distributions are implemented: Poisson (Mielke and Munk (2009) <arXiv:0912.4169>), negative binomial (Muetze et al. (2016) <doi:10.1002/sim.6738>), normal (Pigeot et al. (2003) <doi:10.1002/sim.1450>; Hasler et al. (2009) <doi:10.1002/sim.3052>), binary (Friede and Kieser (2007) <doi:10.1002/sim.2543>), nonparametric (Muetze et al. (2017) <doi:10.1002/sim.7176>), exponential (Mielke and Munk (2009) <arXiv:0912.4169>).
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2025-03-25 |
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r-thgenetics
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A step-up test for genetic rare variants in a gene or in a pathway. The method determines an optimal grouping of rare variants analytically. The method has been described in Hoffmann TJ, Marini NJ, and Witte JS (2010) <doi:10.1371/journal.pone.0013584>.
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2025-03-25 |
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r-tgcd
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Deconvolving thermoluminescence glow curves according to various kinetic models (first-order, second-order, general-order, and mixed-order) using a modified Levenberg-Marquardt algorithm (More, 1978) <DOI:10.1007/BFb0067700>. It provides the possibility of setting constraints or fixing any of parameters. It offers an interactive way to initialize parameters by clicking with a mouse on a plot at positions where peak maxima should be located. The optimal estimate is obtained by "trial-and-error". It also provides routines for simulating first-order, second-order, and general-order glow peaks.
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2025-03-25 |
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r-tfmpvalue
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In putative Transcription Factor Binding Sites (TFBSs) identification from sequence/alignments, we are interested in the significance of certain match score. TFMPvalue provides the accurate calculation of P-value with score threshold for Position Weight Matrices, or the score with given P-value. It is an interface to code originally made available by Helene Touzet and Jean-Stephane Varre, 2007, Algorithms Mol Biol:2, 15. <doi:10.1186/1748-7188-2-15>.
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2025-03-25 |
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r-tfcox
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In Cox's proportional hazard model, covariates are modeled as linear function and may not be flexible. This package implements additive trend filtering Cox proportional hazards model as proposed in Jiacheng Wu & Daniela Witten (2019) "Flexible and Interpretable Models for Survival Data", Journal of Computational and Graphical Statistics, <DOI:10.1080/10618600.2019.1592758>. The fitted functions are piecewise polynomial with adaptively chosen knots.
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2025-03-25 |
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r-texttinyr
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It offers functions for splitting, parsing, tokenizing and creating a vocabulary for big text data files. Moreover, it includes functions for building a document-term matrix and extracting information from those (term-associations, most frequent terms). It also embodies functions for calculating token statistics (collocations, look-up tables, string dissimilarities) and functions to work with sparse matrices. Lastly, it includes functions for Word Vector Representations (i.e. 'GloVe', 'fasttext') and incorporates functions for the calculation of (pairwise) text document dissimilarities. The source code is based on 'C++11' and exported in R through the 'Rcpp', 'RcppArmadillo' and 'BH' packages.
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2025-03-25 |
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r-textreg
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Function for sparse regression on raw text, regressing a labeling vector onto a feature space consisting of all possible phrases.
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2025-03-25 |
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r-rmecabko
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An 'Rcpp' interface for Eunjeon project <http://eunjeon.blogspot.com/>. The 'mecab-ko' and 'mecab-ko-dic' is based on a C++ library, and part-of-speech tagging with them is useful when the spacing of source Korean text is not correct. This package provides part-of-speech tagging and tokenization function for Korean text.
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2025-03-25 |
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r-rgdal
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Provides bindings to the 'Geospatial' Data Abstraction Library ('GDAL') (>= 1.11.4) and access to projection/transformation operations from the 'PROJ' library. Please note that 'rgdal' will be retired by the end of 2023, plan transition to sf/stars/'terra' functions using 'GDAL' and 'PROJ' at your earliest convenience. Use is made of classes defined in the 'sp' package. Raster and vector map data can be imported into R, and raster and vector 'sp' objects exported. The 'GDAL' and 'PROJ' libraries are external to the package, and, when installing the package from source, must be correctly installed first; it is important that 'GDAL' < 3 be matched with 'PROJ' < 6. From 'rgdal' 1.5-8, installed with to 'GDAL' >=3, 'PROJ' >=6 and 'sp' >= 1.4, coordinate reference systems use 'WKT2_2019' strings, not 'PROJ' strings. 'Windows' and 'macOS' binaries (including 'GDAL', 'PROJ' and their dependencies) are provided on 'CRAN'.
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2025-03-25 |
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r-rootwishart
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Functions for hypothesis testing in single and double Wishart settings, based on Roy's largest root. This test statistic is especially useful in multivariate analysis. The computations are based on results by Chiani (2014) <DOI:10.1016/j.jmva.2014.04.002> and Chiani (2016) <DOI:10.1016/j.jmva.2015.10.007>. They use the fact that the CDF is related to the Pfaffian of a matrix that can be computed in a finite number of iterations. This package takes advantage of the Boost and Eigen C++ libraries to perform multi-precision linear algebra.
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2025-03-25 |
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r-rootsolve
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Routines to find the root of nonlinear functions, and to perform steady-state and equilibrium analysis of ordinary differential equations (ODE). Includes routines that: (1) generate gradient and jacobian matrices (full and banded), (2) find roots of non-linear equations by the 'Newton-Raphson' method, (3) estimate steady-state conditions of a system of (differential) equations in full, banded or sparse form, using the 'Newton-Raphson' method, or by dynamically running, (4) solve the steady-state conditions for uni-and multicomponent 1-D, 2-D, and 3-D partial differential equations, that have been converted to ordinary differential equations by numerical differencing (using the method-of-lines approach). Includes fortran code.
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2025-03-25 |
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r-rollregres
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Methods for fast rolling and expanding linear regression models. That is, series of linear regression models estimated on either an expanding window of data or a moving window of data. The methods use rank-one updates and downdates of the upper triangular matrix from a QR decomposition (see Dongarra, Moler, Bunch, and Stewart (1979) <doi:10.1137/1.9781611971811>).
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2025-03-25 |
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r-rodeo
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Provides an R6 class and several utility methods to facilitate the implementation of models based on ordinary differential equations. The heart of the package is a code generator that creates compiled 'Fortran' (or 'R') code which can be passed to a numerical solver. There is direct support for solvers contained in packages 'deSolve' and 'rootSolve'.
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2025-03-25 |
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r-rodbcext
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An extension for RODBC package adding support for parameterized queries.
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2025-03-25 |
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r-rococo
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Provides the robust gamma rank correlation coefficient as introduced by Bodenhofer, Krone, and Klawonn (2013) <DOI:10.1016/j.ins.2012.11.026> along with a permutation-based rank correlation test. The rank correlation coefficient and the test are explicitly designed for dealing with noisy numerical data.
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2025-03-25 |
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r-robustreg
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Linear regression functions using Huber and bisquare psi functions. Optimal weights are calculated using IRLS algorithm.
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2025-03-25 |
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r-robustgasp
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Robust parameter estimation and prediction of Gaussian stochastic process emulators. It allows for robust parameter estimation and prediction using Gaussian stochastic process emulator. It also implements the parallel partial Gaussian stochastic process emulator for computer model with massive outputs See the reference: Mengyang Gu and Jim Berger, 2016, Annals of Applied Statistics; Mengyang Gu, Xiaojing Wang and Jim Berger, 2018, Annals of Statistics.
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2025-03-25 |
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r-robustgam
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This package provides robust estimation for generalized additive models. It implements a fast and stable algorithm in Wong, Yao and Lee (2013). The implementation also contains three automatic selection methods for smoothing parameter. They are designed to be robust to outliers. For more details, see Wong, Yao and Lee (2013).
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2025-03-25 |
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r-robustetm
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Testing homogeneity for generalized exponential tilt model. This package includes a collection of functions for (1) implementing methods for testing homogeneity for generalized exponential tilt model; and (2) implementing existing methods under comparison.
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2025-03-25 |
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r-robustblme
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Bayesian robust fitting of linear mixed effects models through weighted likelihood equations and approximate Bayesian computation as proposed by Ruli et al. (2017) <arXiv:1706.01752>.
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2025-03-25 |
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r-robustaft
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R functions for the computation of the truncated maximum likelihood and the robust accelerated failure time regression for gaussian and log-Weibull case.
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2025-03-25 |
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r-robfitcongraph
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Contains a single function named robFitConGraph() which includes two algorithms for robust estimation of scatter matrices subject to zero-constraints in its inverse. The methodology is described in Vogel & Tyler (2014) <doi:10.1093/biomet/asu041>. See robFitConGraph() function documentation for further details.
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2025-03-25 |
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r-robfilter
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Implementations for several robust procedures that allow for (online) extraction of the signal of univariate or multivariate time series by applying robust regression techniques to a moving time window are provided. Included are univariate filtering procedures based on repeated-median regression as well as hybrid and trimmed filters derived from it; see Schettlinger et al. (2006) <doi:10.1515/BMT.2006.010>. The adaptive online repeated median by Schettlinger et al. (2010) <doi:10.1002/acs.1105> and the slope comparing adaptive repeated median by Borowski and Fried (2013) <doi:10.1007/s11222-013-9391-7> choose the width of the moving time window adaptively. Multivariate versions are also provided; see Borowski et al. (2009) <doi:10.1080/03610910802514972> for a multivariate online adaptive repeated median and Borowski (2012) <doi:10.17877/DE290R-14393> for a multivariate slope comparing adaptive repeated median. Furthermore, a repeated-median based filter with automatic outlier replacement and shift detection is provided; see Fried (2004) <doi:10.1080/10485250410001656444>.
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2025-03-25 |
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r-robeth
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Locations problems, M-estimates of coefficients and scale in linear regression, Weights for bounded influence regression, Covariance matrix of the coefficient estimates, Asymptotic relative efficiency of regression M-estimates, Robust testing in linear models, High breakdown point regression, M-estimates of covariance matrices, M-estimates for discrete generalized linear models.
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2025-03-25 |
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r-robcp
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Provides robust methods to detect change-points in uni- or multivariate time series. They can cope with corrupted data and heavy tails. Focus is on the detection of abrupt changes in location, but changes scale or dependence structure can be detected as well. This package provides tests for change detection in uni- and multivariate time series based on Huberized versions of CUSUM tests proposed in Duerre and Fried (2019) <arXiv:1905.06201>, and tests for change detection in univariate time series based on 2-sample U-statistics or 2-sample U-quantiles as proposed by Dehling et al. (2015) <DOI:10.1007/978-1-4939-3076-0_12> and Dehling, Fried and Wendler (2020) <DOI:10.1093/biomet/asaa004>. Furthermore, the packages provides tests on changes in the scale or the correlation as proposed in Gerstenberger, Vogel and Wendler (2020) <DOI:10.1080/01621459.2019.1629938>, Dehling et al. (2017) <DOI:10.1017/S026646661600044X>, and Wied et al. (2014) <DOI:10.1016/j.csda.2013.03.005>.
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2025-03-25 |
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r-rnomni
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Inverse normal transformation (INT) based genetic association testing. These tests are recommend for continuous traits with non-normally distributed residuals. INT-based tests robustly control the type I error in settings where standard linear regression does not, as when the residual distribution exhibits excess skew or kurtosis. Moreover, INT-based tests outperform standard linear regression in terms of power. These tests may be classified into two types. In direct INT (D-INT), the phenotype is itself transformed. In indirect INT (I-INT), phenotypic residuals are transformed. The omnibus test (O-INT) adaptively combines D-INT and I-INT into a single robust and statistically powerful approach. See McCaw ZR, Lane JM, Saxena R, Redline S, Lin X. "Operating characteristics of the rank-based inverse normal transformation for quantitative trait analysis in genome-wide association studies" <doi:10.1111/biom.13214>.
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2025-03-25 |
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r-rnifti
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Provides very fast read and write access to images stored in the NIfTI-1, NIfTI-2 and ANALYZE-7.5 formats, with seamless synchronisation of in-memory image objects between compiled C and interpreted R code. Also provides a simple image viewer, and a C/C++ API that can be used by other packages. Not to be confused with 'RNiftyReg', which performs image registration and applies spatial transformations.
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2025-03-25 |
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r-rngwell19937
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Long period linear random number generator WELL19937a by F. Panneton, P. L'Ecuyer and M. Matsumoto. The initialization algorithm allows to seed the generator with a numeric vector of an arbitrary length and uses MRG32k5a by P. L'Ecuyer to achieve good quality of the initialization. The output function may be set to provide numbers from the interval (0,1) with 53 (the default) or 32 random bits. WELL19937a is of similar type as Mersenne Twister and has the same period. WELL19937a is slightly slower than Mersenne Twister, but has better equidistribution and "bit-mixing" properties and faster recovery from states with prevailing zeros than Mersenne Twister. All WELL generators with orders 512, 1024, 19937 and 44497 can be found in randtoolbox package.
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2025-03-25 |
