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r-stem
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Estimation of the parameters of a spatio-temporal model using the EM algorithm, estimation of the parameter standard errors using a spatio-temporal parametric bootstrap, spatial mapping.
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2023-06-16 |
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r-ssh.utils
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This package provides utility functions for system command execution, both locally and remotely using ssh/scp. The command output is captured and provided to the caller. This functionality is intended to streamline calling shell commands from R, retrieving and using their output, while instrumenting the calls with appropriate error handling. NOTE: this first version is limited to unix with local and remote systems running bash as the default shell.
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2023-06-16 |
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r-fishical
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FisHiCal integrates Hi-C and FISH data, offering a modular and easy-to-use tool for chromosomal spatial analysis.
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2023-06-16 |
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r-tableplot
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Description:
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2023-06-16 |
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r-synbreeddata
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Data sets for the 'synbreed' package with three data sets from cattle, maize and mice to illustrate the functions in the 'synbreed' R package. All data sets are stored in the gpData format introduced in the 'synbreed' package. This research was funded by the German Federal Ministry of Education and Research (BMBF) within the AgroClustEr Synbreed - Synergistic plant and animal breeding (FKZ 0315528A).
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2023-06-16 |
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r-subniche
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Complementary indexes calculation to the Outlying Mean Index analysis to explore niche shift of a community and biological constraint within an Euclidean space, with graphical displays.
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2023-06-16 |
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r-stagedchoicesplinemix
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Analyzing a mixture of two-stage logistic regressions with fixed candidate knots. See Bruch, E., F. Feinberg, K. Lee (in press)<DOI:10.1073/pnas.1522494113>.
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2023-06-16 |
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r-tarifx
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A collection of various utility and convenience functions.
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2023-06-16 |
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r-fastclime
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Provides a method of recovering the precision matrix efficiently and solving for the dantzig selector by applying the parametric simplex method. The computation is based on a linear optimization solver. It also contains a generic LP solver and a parameterized LP solver using parametric simplex method.
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2023-06-16 |
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r-yakmor
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This is a simple wrapper for the yakmo K-Means library (developed by Naoki Yoshinaga, see http://www.tkl.iis.u-tokyo.ac.jp/~ynaga/yakmo/). It performs fast and robust (orthogonal) K-Means.
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2023-06-16 |
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r-xptr
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There is limited native support for external pointers in the R interface. This package provides some basic tools to verify, create and modify 'externalptr' objects.
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2023-06-16 |
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r-fasteraster
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If there is a need to recognise edges on a raster image or a bitmap or any kind of a matrix, one can find packages that does only 90 degrees vectorization. Typically the nature of artefact images is linear and can be vectorized in much more efficient way than draw a series of 90 degrees lines. The fasteraster package does recognition of lines using only one pass. It also allows to calculate mass and the mass centers for the recognized zones or polygons.
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2023-06-16 |
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r-fastcmprsk
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In competing risks regression, the proportional subdistribution hazards (PSH) model is popular for its direct assessment of covariate effects on the cumulative incidence function. This package allows for both penalized and unpenalized PSH regression in linear time using a novel forward-backward scan. Penalties include Ridge, Lease Absolute Shrinkage and Selection Operator (LASSO), Smoothly Clipped Absolute Deviation (SCAD), Minimax Concave Plus (MCP), and elastic net.
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2023-06-16 |
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r-extweibquant
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It implements the subjectively censored Weibull MLE and censored Weibull mixture methods for the lower quantile estimation. Quantile estimates from these two methods are robust to model misspecification in the lower tail. It also includes functions to evaluation the standard error of the resulting quantile estimates. Also, the methods here can be used to fit the Weibull or Weibull mixture for the Type-I or Type-II right censored data.
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2023-06-16 |
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r-fastlzerospikeinference
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Estimate spike times from calcium imaging data using an L0 penalty.
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2023-06-16 |
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r-factorqr
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Package to fit Bayesian quantile regression models that assume a factor structure for at least part of the design matrix.
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2023-06-16 |
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r-xtensor
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The 'xtensor' C++ library for numerical analysis with multi-dimensional array expressions is provided as a header-only C++14 library. It offers an extensible expression system enabling lazy broadcasting; an API following the idioms of the C++ standard library; and tools to manipulate array expressions and build upon 'xtensor'.
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2023-06-16 |
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r-wicket
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Utilities to generate bounding boxes from 'WKT' (Well-Known Text) objects and R data types, validate 'WKT' objects and convert object types from the 'sp' package into 'WKT' representations.
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2023-06-16 |
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r-fasthcs
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The FastHCS algorithm of Schmitt and Vakili (2015) for high-dimensional, robust PCA modelling and associated outlier detection and diagnostic tools.
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2023-06-16 |
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r-wingui
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Helps for interfacing with the operating system particularly for Windows.
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2023-06-16 |
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r-xyz
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High dimensional interaction search by brute force requires a quadratic computational cost in the number of variables. The xyz algorithm provably finds strong interactions in almost linear time. For details of the algorithm see: G. Thanei, N. Meinshausen and R. Shah (2016). The xyz algorithm for fast interaction search in high-dimensional data <https://arxiv.org/pdf/1610.05108v1.pdf>.
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2023-06-16 |
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r-fastadaboost
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Implements Adaboost based on C++ backend code. This is blazingly fast and especially useful for large, in memory data sets. The package uses decision trees as weak classifiers. Once the classifiers have been trained, they can be used to predict new data. Currently, we support only binary classification tasks. The package implements the Adaboost.M1 algorithm and the real Adaboost(SAMME.R) algorithm.
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2023-06-16 |
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r-whopgenome
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Provides very fast access to whole genome, population scale variation data from VCF files and sequence data from FASTA-formatted files. It also reads in alignments from FASTA, Phylip, MAF and other file formats. Provides easy-to-use interfaces to genome annotation from UCSC and Bioconductor and gene ontology data from AmiGO and is capable to read, modify and write PLINK .PED-format pedigree files.
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2023-06-16 |
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r-ezglm
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This package implements a simplified version of least squares, and logistic regression for efficiently selecting the significant non-additive interactions between two variables.
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2023-06-16 |
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r-pp3
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Exploratory projection pursuit is a method to discovers structure in multivariate data. At heart this package uses a projection index to evaluate how interesting a specific three-dimensional projection of multivariate data (with more than three dimensions) is. Typically, the main structure finding algorithm starts at a random projection and then iteratively changes the projection direction to move to a more interesting one. In other words, the projection index is maximised over the projection direction to find the most interesting projection. This maximum is, though, a local maximum. So, this code has the ability to restart the algorithm from many different starting positions automatically. Routines exist to plot a density estimate of projection indices over the runs, this enables the user to obtain an idea of the distribution of the projection indices, and, hence, which ones might be interesting. Individual projection solutions, including those identified as interesting, can be extracted and plotted individually. The package can make use of the mclapply() function to execute multiple runs in parallel to speed up index discovery. Projection pursuit is similar to independent component analysis. This package uses a projection index that maximises an entropy measure to look for projections that exhibit non-normality, and operates on sphered data. Hence, information from this package is different from that obtained from principal components analysis, but the rationale behind both methods is similar. Nason, G. P. (1995) <doi:10.2307/2986135>.
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2023-06-16 |
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r-pliable
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Fits a pliable lasso model. For details see Tibshirani and Friedman (2018) <arXiv:1712.00484>.
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2023-06-16 |
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r-planor
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Automatic generation of regular factorial designs, including fractional designs, orthogonal block designs, row-column designs and split-plots.
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2023-06-16 |
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r-permallows
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Includes functions to work with the Mallows and Generalized Mallows Models. The considered distances are Kendall's-tau, Cayley, Hamming and Ulam and it includes functions for making inference, sampling and learning such distributions, some of which are novel in the literature. As a by-product, PerMallows also includes operations for permutations, paying special attention to those related with the Kendall's-tau, Cayley, Ulam and Hamming distances. It is also possible to generate random permutations at a given distance, or with a given number of inversions, or cycles, or fixed points or even with a given length on LIS (longest increasing subsequence).
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2023-06-16 |
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r-perccal
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Contains functions which allow the user to compute confidence intervals quickly using the double bootstrap-based percentile calibrated ('perc-cal') method for linear regression coefficients. 'perccal_interval()' is the primary user-facing function within this package.
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2023-06-16 |
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r-pivotalr
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Provides an R interface for the Pivotal Data stack running on 'PostgreSQL', 'Greenplum' or 'Apache HAWQ (incubating)' databases with parallel and distributed computation ability for big data processing. 'PivotalR' provides an R interface to various database operations on tables or views. These operations are almost the same as the corresponding native R operations. Thus users of R do not need to learn 'SQL' when they operate on objects in the database. It also provides a wrapper for 'Apache MADlib (incubating)', which is an open- source library for parallel and scalable in-database analytics.
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2023-06-16 |
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r-phylomeasures
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Given a phylogenetic tree T and an assemblage S of species represented as a subset of tips in T, we want to compute a measure of the diversity of the species in S with respect to T. The current package offers efficient algorithms that can process large phylogenetic data for several such measures. Most importantly, the package includes algorithms for computing efficiently the standardized versions of phylogenetic measures and their p-values, which are essential for null model comparisons. Among other functions, the package provides efficient computation of richness-standardized versions for indices such as the net relatedness index (NRI), nearest taxon index (NTI), phylogenetic diversity index (PDI), and the corresponding indices of two-sample measures. The package also introduces a new single-sample measure, the Core Ancestor Cost (CAC); the package provides functions for computing the value and the standardised index of the CAC and, more than that, there is an extra function available that can compute exactly any statistical moment of the measure. The package supports computations under different null models, including abundance-weighted models.
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2023-06-16 |
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r-ph2hetero
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Implementation of Jones (2007) <doi:10.1016/j.cct.2007.02.008> , Tournoux-Facon (2011) <doi:10.1002/sim.4148> and Parashar (2016) <doi:10.1002/pst.1742> designs.
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2023-06-16 |
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r-pts2polys
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Various applications in invasive species biology, conservation biology, epidemiology and elsewhere involve sampling of sets of 2D points from a posterior distribution. The number of such point sets may be large, say 1000 or 10000. This package facilitates visualisation of such output by constructing seven nested polygons representing the location and variability of the point sets. This can be used, for example, to visualise the range boundary of a species, and uncertainty in the location of that boundary.
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2023-06-16 |
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r-power
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Functions for the computation of power and level tables for hypothesis tests, in Latex format, functions to build explanatory graphs for studying power of test statistics.
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2023-06-16 |
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r-phyloland
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Phyloland package models a space colonization process mapped onto a phylogeny, it aims at estimating limited dispersal and ecological competitive exclusion in a Bayesian MCMC statistical phylogeographic framework (please refer to phyloland-package help for details.)
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2023-06-16 |
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r-permdep
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Implementations of permutation approach to hypothesis testing for quasi-independence of truncation time and failure time. The implemented approaches are powerful against non-monotone alternatives and thereby offer protection against erroneous assumptions of quasi-independence. The proposed tests use either a conditional or an unconditional method to evaluate the permutation p-value. The conditional method was first developed in Tsai (1980) <doi:10.2307/2336059> and Efron and Petrosian (1992) <doi:10.1086/171931>. The unconditional method provides a valid approximation to the conditional method, yet computationally simpler and does not hold fixed the size of each risk sets. Users also have an option to carry out the proposed permutation tests in a parallel computing fashion.
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2023-06-16 |
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r-polyfreqs
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Implements a Gibbs sampling algorithm to perform Bayesian inference on biallelic SNP frequencies, genotypes and heterozygosity (observed and expected) in a population of autopolyploids. See the published paper in Molecular Ecology Resources: Blischak et al. (2016) <doi:10.1111/1755-0998.12493>.
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2023-06-16 |
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r-pgbart
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The Particle Gibbs sampler and Gibbs/Metropolis-Hastings sampler were implemented to fit Bayesian additive regression tree model. Construction of the model (training) and prediction for a new data set (testing) can be separated. Our reference papers are: Lakshminarayanan B, Roy D, Teh Y W. Particle Gibbs for Bayesian additive regression trees[C], Artificial Intelligence and Statistics. 2015: 553-561, <http://proceedings.mlr.press/v38/lakshminarayanan15.pdf> and Chipman, H., George, E., and McCulloch R. (2010) Bayesian Additive Regression Trees. The Annals of Applied Statistics, 4,1, 266-298, <doi:10.1214/09-aoas285>.
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2023-06-16 |
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r-phmm
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Fits proportional hazards model incorporating random effects using an EM algorithm using Markov Chain Monte Carlo at E-step. Vaida and Xu (2000) <DOI:10.1002/1097-0258(20001230)19:24%3C3309::AID-SIM825%3E3.0.CO;2-9>.
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2023-06-16 |
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r-ptsuite
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Various estimation methods for the shape parameter of Pareto distributed data. This package contains functions for various estimation methods such as maximum likelihood (Newman, 2005)<doi:10.1016/j.cities.2012.03.001>, Hill's estimator (Hill, 1975)<doi:10.1214/aos/1176343247>, least squares (Zaher et al., 2014)<doi:10.9734/BJMCS/2014/10890>, method of moments (Rytgaard, 1990)<doi:10.2143/AST.20.2.2005443>, percentiles (Bhatti et al., 2018)<doi:10.1371/journal.pone.0196456>, and weighted least squares (Nair et al., 2019) to estimate the shape parameter of Pareto distributed data. It also provides both a heuristic method (Hubert et al., 2013)<doi:10.1016/j.csda.2012.07.011> and a goodness of fit test (Gulati and Shapiro, 2008)<doi:10.1007/978-0-8176-4619-6> for testing for Pareto data as well as a method for generating Pareto distributed data.
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2023-06-16 |
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r-pet
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Implementation of different analytic/direct and iterative reconstruction methods of radon transformed data such as PET data. It also offer the possibility to simulate PET data.
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2023-06-16 |
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r-profdpm
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This package facilitates profile inference (inference at the posterior mode) for a class of product partition models (PPM). The Dirichlet process mixture is currently the only available member of this class. These methods search for the maximum posterior (MAP) estimate for the data partition in a PPM.
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2023-06-16 |
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r-nestedcohort
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Estimate hazard ratios, survival curves and attributable risks for cohorts with missing covariates, using Cox models or Kaplan-Meier estimated for strata. This handles studies nested within cohorts, such as case-cohort studies with stratified sampling. See http://www.r-project.org/doc/Rnews/Rnews_2008-1.pdf
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2023-06-16 |
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r-mopsocd
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A multi-objective optimization solver based on particle swarm optimization with crowding distance.
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2023-06-16 |
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r-minval
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For a given set of stoichiometric reactions, this package evaluates the mass and charge balance, extracts all reactants, products, orphan metabolites, metabolite names and compartments. Also are included some options to characterize and write models in TSV and SBML formats.
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2023-06-16 |
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r-metabel
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A package for meta-analysis of genome-wide association scans between quantitative or binary traits and SNPs
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2023-06-16 |
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r-mcsm
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mcsm contains a collection of functions that allows the reenactment of the R programs used in the book EnteR Monte Carlo Methods without further programming. Programs being available as well, they can be modified by the user to conduct one's own simulations.
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2023-06-16 |
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r-marl
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Functions provided allow data simulation; construction of weighted relative likelihood functions; clustering and principal component analysis based on weighted relative likelihood functions.
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2023-06-16 |
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r-leap
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Advances in sequencing technology now allow researchers to capture the expression profiles of individual cells. Several algorithms have been developed to attempt to account for these effects by determining a cell's so-called `pseudotime', or relative biological state of transition. By applying these algorithms to single-cell sequencing data, we can sort cells into their pseudotemporal ordering based on gene expression. LEAP (Lag-based Expression Association for Pseudotime-series) then applies a time-series inspired lag-based correlation analysis to reveal linearly dependent genetic associations.
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2023-06-16 |
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r-nodeharvest
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Node harvest is a simple interpretable tree-like estimator for high-dimensional regression and classification. A few nodes are selected from an initially large ensemble of nodes, each associated with a positive weight. New observations can fall into one or several nodes and predictions are the weighted average response across all these groups. The package offers visualization of the estimator. Predictions can return the nodes a new observation fell into, along with the mean response of training observations in each node, offering a simple explanation of the prediction.
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2023-06-16 |
