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r-ordinalclust
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Ordinal data classification, clustering and co-clustering using model-based approach with the Bos distribution for ordinal data (Christophe Biernacki and Julien Jacques (2016) <doi:10.1007/s11222-015-9585-2>).
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2023-06-16 |
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r-nseval
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Facilities to capture, inspect, manipulate, and create lazy values (promises), "..." lists, and active calls.
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2023-06-16 |
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r-nets
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Sparse VAR estimation based on LASSO.
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2023-06-16 |
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r-negenes
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Estimating the number of essential genes in a genome on the basis of data from a random transposon mutagenesis experiment, through the use of a Gibbs sampler. Lamichhane et al. (2003) <doi:10.1073/pnas.1231432100>.
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2023-06-16 |
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r-npst
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Package 'npst' generalizes Hewitt's (1971) test for seasonality and Rogerson's (1996) extension based on Monte-Carlo simulation.
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2023-06-16 |
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r-not
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Provides efficient implementation of the Narrowest-Over-Threshold methodology for detecting an unknown number of change-points occurring at unknown locations in one-dimensional data following deterministic signal + noise model, see R. Baranowski, Y. Chen and P. Fryzlewicz (2019) <doi:10.1111/rssb.12322>. Currently implemented scenarios are: piecewise-constant signal, piecewise-constant signal with a heavy-tailed noise, piecewise-linear signal, piecewise-quadratic signal, piecewise-constant signal and with piecewise-constant variance of the noise.
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2023-06-16 |
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r-nopaco
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A non-parametric test for multi-observer concordance and differences between concordances in (un)balanced data.
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2023-06-16 |
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r-ncdf4
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Provides a high-level R interface to data files written using Unidata's netCDF library (version 4 or earlier), which are binary data files that are portable across platforms and include metadata information in addition to the data sets. Using this package, netCDF files (either version 4 or "classic" version 3) can be opened and data sets read in easily. It is also easy to create new netCDF dimensions, variables, and files, in either version 3 or 4 format, and manipulate existing netCDF files. This package replaces the former ncdf package, which only worked with netcdf version 3 files. For various reasons the names of the functions have had to be changed from the names in the ncdf package. The old ncdf package is still available at the URL given below, if you need to have backward compatibility. It should be possible to have both the ncdf and ncdf4 packages installed simultaneously without a problem. However, the ncdf package does not provide an interface for netcdf version 4 files.
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2023-06-16 |
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r-pbv
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Computes probabilities of the bivariate normal distribution in a vectorized R function (Drezner & Wesolowsky, 1990, <doi:10.1080/00949659008811236>).
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2023-06-16 |
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r-pan
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It provides functions and examples for maximum likelihood estimation for generalized linear mixed models and Gibbs sampler for multivariate linear mixed models with incomplete data, as described in Schafer JL (1997) "Imputation of missing covariates under a multivariate linear mixed model". Technical report 97-04, Dept. of Statistics, The Pennsylvania State University.
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2023-06-16 |
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r-noncompliance
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A finite-population significance test of the 'sharp' causal null hypothesis that treatment exposure X has no effect on final outcome Y, within the principal stratum of Compliers. A generalized likelihood ratio test statistic is used, and the resulting p-value is exact. Currently, it is assumed that there are only Compliers and Never Takers in the population.
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2023-06-16 |
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r-nmfgpu4r
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Wrapper package for the nmfgpu library, which implements several Non-negative Matrix Factorization (NMF) algorithms for CUDA platforms. By using the acceleration of GPGPU computing, the NMF can be used for real-world problems inside the R environment. All CUDA devices starting with Kepler architecture are supported by the library.
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2023-06-16 |
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r-ncvreg
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Fits regularization paths for linear regression, GLM, and Cox regression models using lasso or nonconvex penalties, in particular the minimax concave penalty (MCP) and smoothly clipped absolute deviation (SCAD) penalty, with options for additional L2 penalties (the "elastic net" idea). Utilities for carrying out cross-validation as well as post-fitting visualization, summarization, inference, and prediction are also provided.
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2023-06-16 |
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r-pcirt
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Estimates the multidimensional polytomous Rasch model (Rasch, 1961) with conditional maximum likelihood estimation.
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2023-06-16 |
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r-pawls
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Efficient algorithms for fitting weighted least squares regression with \eqn{L_{1}}{L1} regularization on both the coefficients and weight vectors, which is able to perform simultaneous variable selection and outliers detection efficiently.
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2023-06-16 |
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r-parglm
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Provides a parallel estimation method for generalized linear models without compiling with a multithreaded LAPACK or BLAS.
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2023-06-16 |
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r-overlap
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Provides functions to fit kernel density functions to data on temporal activity patterns of animals; estimate coefficients of overlapping of densities for two species; and calculate bootstrap estimates of confidence intervals.
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2023-06-16 |
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r-ore
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Provides an alternative to R's built-in functionality for handling regular expressions, based on the Onigmo library. Offers first-class compiled regex objects, partial matching and function-based substitutions, amongst other features.
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2023-06-16 |
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r-openmpcontroller
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The OpenMPController package provides a function omp_set_num_threads() to set the number of OpenMP threads to be used. This may be useful, for example, when linking against a vendor optimised BLAS/LAPACK library (e.g. the AMD Core Math Library), since the defaults used by those libraries may not be highly performant.
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2023-06-16 |
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r-onion
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Quaternions and Octonions are four- and eight- dimensional extensions of the complex numbers. They are normed division algebras over the real numbers and find applications in spatial rotations (quaternions) and string theory and relativity (octonions). The quaternions are noncommutative and the octonions nonassociative. See RKS Hankin 2006, Rnews Volume 6/2: 49-51, and the package vignette, for more details.
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2023-06-16 |
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r-neariso
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Implements a path algorithm for Near-Isotonic Regression. For more details see the help files.
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2023-06-16 |
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r-pdc
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Permutation Distribution Clustering is a clustering method for time series. Dissimilarity of time series is formalized as the divergence between their permutation distributions. The permutation distribution was proposed as measure of the complexity of a time series.
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2023-06-16 |
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r-ormdr
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Odds ratio based multifactor-dimensionality reduction method for detecting gene-gene interactions
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2023-06-16 |
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r-orca
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Implements orbit counting using a fast combinatorial approach. Counts orbits of nodes and edges from edge matrix or data frame, or a graph object from the graph package.
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2023-06-16 |
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r-obliclus
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This package conducts factor rotation techniques which intentd to identify a simple and well-clustered structure in a factor loading matrix.
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2023-06-16 |
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r-np
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Nonparametric (and semiparametric) kernel methods that seamlessly handle a mix of continuous, unordered, and ordered factor data types. We would like to gratefully acknowledge support from the Natural Sciences and Engineering Research Council of Canada (NSERC, <http://www.nserc-crsng.gc.ca>), the Social Sciences and Humanities Research Council of Canada (SSHRC, <http://www.sshrc-crsh.gc.ca>), and the Shared Hierarchical Academic Research Computing Network (SHARCNET, <http://www.sharcnet.ca>).
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2023-06-16 |
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r-norm
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Analysis of multivariate normal datasets with missing values
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2023-06-16 |
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r-nonpmodelcheck
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Provides tests of significance for covariates (or groups of covariates) in a fully nonparametric regression model and a variable (or group) selection procedure based on False Discovery Rate. In addition, it provides a function for local polynomial regression for any number of dimensions, using a bandwidth specified by the user or automatically chosen by cross validation or an adaptive procedure.
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2023-06-16 |
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r-osdesign
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The osDesign serves for planning an observational study. Currently, functionality is focused on the two-phase and case-control designs. Functions in this packages provides Monte Carlo based evaluation of operating characteristics such as powers for estimators of the components of a logistic regression model.
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2023-06-16 |
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r-onlinevar
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Functions for recursive online fitting of time-adaptive lasso vector auto regression. A recursive coordinate descent algorithm is used to estimate sparse vector auto regressive models and exponential forgetting is applied to allow model changes. Details can be found in Jakob W. Messner and Pierre Pinson (2018). "Online adaptive LASSO estimation in Vector Auto Regressive models for wind power forecasting in high dimension". International Journal of Forecasting, in press. <doi:10.1016/j.ijforecast.2018.02.001>.
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2023-06-16 |
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r-offlinechange
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Detect the number and locations of change points. The locations can be either exact or in terms of ranges, depending on the available computational resource. The method is based on Jie Ding, Yu Xiang, Lu Shen, Vahid Tarokh (2016) <arXiv:1605.00346v2>.
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2023-06-16 |
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r-numosl
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Package for optimizing regular numeric problems in optically stimulated luminescence dating, such as: equivalent dose calculation, dose rate determination, growth curve fitting, decay curve decomposition, statistical age model optimization, and statistical plot visualization.
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2023-06-16 |
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r-netchain
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In networks, treatments may spill over from the treated individual to his or her social contacts and outcomes may be contagious over time. Under this setting, causal inference on the collective outcome observed over all network is often of interest. We use chain graph models approximating the projection of the full longitudinal data onto the observed data to identify the causal effect of the intervention on the whole outcome. Justification of such approximation is demonstrated in Ogburn et al. (2018) <arXiv:1812.04990>.
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2023-06-16 |
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r-parmigene
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The package provides a parallel estimation of the mutual information based on entropy estimates from k-nearest neighbors distances and algorithms for the reconstruction of gene regulatory networks.
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2023-06-16 |
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r-opthedging
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Estimation of value and hedging strategy of call and put options, based on optimal hedging and Monte Carlo method, from Chapter 3 of 'Statistical Methods for Financial Engineering', by Bruno Remillard, CRC Press, (2013).
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2023-06-16 |
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r-optgs
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Functions to find near-optimal multi-stage designs for continuous outcomes.
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2023-06-16 |
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r-onehot
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Quickly create numeric matrices for machine learning algorithms that require them. It converts factor columns into onehot vectors.
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2023-06-16 |
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r-olctools
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'Open Location Codes' <http://openlocationcode.com/> are a Google-created standard for identifying geographic locations. 'olctools' provides utilities for validating, encoding and decoding entries that follow this standard.
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2023-06-16 |
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r-officer
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Access and manipulate 'Microsoft Word' and 'Microsoft PowerPoint' documents from R. The package focuses on tabular and graphical reporting from R; it also provides two functions that let users get document content into data objects. A set of functions lets add and remove images, tables and paragraphs of text in new or existing documents. When working with 'PowerPoint' presentations, slides can be added or removed; shapes inside slides can also be added or removed. When working with 'Word' documents, a cursor can be used to help insert or delete content at a specific location in the document. The package does not require any installation of Microsoft products to be able to write Microsoft files.
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2023-06-16 |
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r-oem
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Solves penalized least squares problems for big tall data using the orthogonalizing EM algorithm of Xiong et al. (2016) <doi:10.1080/00401706.2015.1054436>. The main fitting function is oem() and the functions cv.oem() and xval.oem() are for cross validation, the latter being an accelerated cross validation function for linear models. The big.oem() function allows for out of memory fitting.
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2023-06-16 |
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r-nvennr
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Provides an interface for the nVenn algorithm (Perez-Silva et al. 2018) <DOI:10.1093/bioinformatics/bty109>. This algorithm works for any number of sets, and usually yields pleasing and informative Venn diagrams with proportionality information. However, representing more than six sets takes a long time and is hard to interpret, unless many of the regions are empty. If you cannot make sense of the result, you may want to consider 'UpSetR' <https://cran.r-project.org/package=UpSetR/README.html>.
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2023-06-16 |
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r-nprocregression
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Implements several nonparametric regression approaches for the inclusion of covariate information on the receiver operating characteristic (ROC) framework.
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2023-06-16 |
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r-pander
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Contains some functions catching all messages, 'stdout' and other useful information while evaluating R code and other helpers to return user specified text elements (like: header, paragraph, table, image, lists etc.) in 'pandoc' markdown or several type of R objects similarly automatically transformed to markdown format. Also capable of exporting/converting (the resulting) complex 'pandoc' documents to e.g. HTML, 'PDF', 'docx' or 'odt'. This latter reporting feature is supported in brew syntax or with a custom reference class with a smarty caching 'backend'.
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2023-06-16 |
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r-opart
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A reference implementation of standard optimal partitioning algorithm in C using square-error loss and Poisson loss functions as described by Robert Maidstone (2016) <doi:10.1007/s11222-016-9636-3>, Toby Hocking (2016) <doi:10.1007/s11222-016-9636-3>, Guillem Rigaill (2016) <doi:10.1007/s11222-016-9636-3>, Paul Fearnhead (2016) <doi:10.1007/s11222-016-9636-3>. It scales quadratically with number of data points in terms of time-complexity.
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2023-06-16 |
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r-nortestarma
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Tests the goodness-of-fit to the Normal distribution for the errors of an ARMA model.
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2023-06-16 |
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r-nimble
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A system for writing hierarchical statistical models largely compatible with 'BUGS' and 'JAGS', writing nimbleFunctions to operate models and do basic R-style math, and compiling both models and nimbleFunctions via custom-generated C++. 'NIMBLE' includes default methods for MCMC, particle filtering, Monte Carlo Expectation Maximization, and some other tools. The nimbleFunction system makes it easy to do things like implement new MCMC samplers from R, customize the assignment of samplers to different parts of a model from R, and compile the new samplers automatically via C++ alongside the samplers 'NIMBLE' provides. 'NIMBLE' extends the 'BUGS'/'JAGS' language by making it extensible: New distributions and functions can be added, including as calls to external compiled code. Although most people think of MCMC as the main goal of the 'BUGS'/'JAGS' language for writing models, one can use 'NIMBLE' for writing arbitrary other kinds of model-generic algorithms as well. A full User Manual is available at <https://r-nimble.org>.
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2023-06-16 |
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r-pbsmodelling
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Provides software to facilitate the design, testing, and operation of computer models. It focuses particularly on tools that make it easy to construct and edit a customized graphical user interface ('GUI'). Although our simplified 'GUI' language depends heavily on the R interface to the 'Tcl/Tk' package, a user does not need to know 'Tcl/Tk'. Examples illustrate models built with other R packages, including 'PBSmapping', 'PBSddesolve', and 'BRugs'. A complete user's guide 'PBSmodelling-UG.pdf' shows how to use this package effectively.
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2023-06-16 |
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r-pbsddesolve
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Routines for solving systems of delay differential equations by interfacing numerical routines written by Simon N. Wood , with contributions by Benjamin J. Cairns. These numerical routines first appeared in Simon Wood's 'solv95' program. This package includes a vignette and a complete user's guide. 'PBSddesolve' originally appeared on CRAN under the name 'ddesolve'. That version is no longer supported. The current name emphasizes a close association with other PBS packages, particularly 'PBSmodelling'.
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2023-06-16 |
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r-orsk
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Convert odds ratio to relative risk in cohort studies with partial data information (Wang (2013) <doi:10.18637/jss.v055.i05>).
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2023-06-16 |
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r-npsimex
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This package contains a collection of functions to to perform nonparametric deconvolution using simulation extrapolation (SIMEX). We propose an estimator that adopts the SIMEX idea but bypasses the simulation step in the original SIMEX algorithm. There is no bandwidth parameter and the estimate is determined by appropriately selecting "design points". See details in: Wang, X.F., Sun, J. and Fan, Z. (2011). Deconvolution density estimation with heteroscedastic errors using SIMEX.
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2023-06-16 |
