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r-interatrix
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public |
Chi-square tests are computed with corrections.
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2023-06-16 |
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r-import
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This is an alternative mechanism for importing objects from packages. The syntax allows for importing multiple objects from a package with a single command in an expressive way. The import package bridges some of the gap between using library (or require) and direct (single-object) imports. Furthermore the imported objects are not placed in the current environment. It is also possible to import objects from stand-alone .R files. For more information, refer to the package vignette.
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2023-06-16 |
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r-imgur
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A complete API client for the image hosting service Imgur.com, including the an imgur graphics device, enabling the easy upload and sharing of plots.
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2023-06-16 |
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r-imfdata
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public |
Search, extract and formulate IMF's datasets.
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2023-06-16 |
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r-ibmsunburst
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Generates Personality Insights sunburst diagrams based on 'IBM Watson' Personality Insights service output.
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2023-06-16 |
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r-ibelief
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public |
Some basic functions to implement belief functions including: transformation between belief functions using the method introduced by Philippe Smets (arXiv:1304.1122 [cs.AI]), evidence combination, evidence discounting, decision-making, and constructing masses. Currently, thirteen combination rules and five decision rules are supported. It can also be used to generate different types of random masses when working on belief combination and conflict management.
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2023-06-16 |
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r-hues
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Creating effective colour palettes for figures is challenging. This package generates and plot palettes of optimally distinct colours in perceptually uniform colour space, based on 'iwanthue' <http://tools.medialab.sciences-po.fr/iwanthue/>. This is done through k-means clustering of CIE Lab colour space, according to user-selected constraints on hue, chroma, and lightness.
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2023-06-16 |
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r-hkex.api
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A set of functions helps to retrieve data from HKEX (Hong Kong Stock Exchange), see <https://www.hkex.com.hk/> for more information. In addition, a function generates insert SQL statements from a dataframe.
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2023-06-16 |
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r-hett
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public |
Functions for the fitting and summarizing of heteroscedastic t-regression.
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2023-06-16 |
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r-heritability
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Implements marker-based estimation of heritability when observations on genetically identical replicates are available. These can be either observations on individual plants or plot-level data in a field trial. Heritability can then be estimated using a mixed model for the individual plant or plot data. For comparison, also mixed-model based estimation using genotypic means and estimation of repeatability with ANOVA are implemented. For illustration the package contains several datasets for the model species Arabidopsis thaliana.
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2023-06-16 |
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r-hdci
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Fits regression models on high dimensional data to estimate coefficients and use bootstrap method to obtain confidence intervals. Choices for regression models are Lasso, Lasso+OLS, Lasso partial ridge, Lasso+OLS partial ridge.
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2023-06-16 |
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r-gwrpvr
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Computes the sample probability value (p-value) for the estimated coefficient from a standard genome-wide univariate regression. It computes the exact finite-sample p-value under the assumption that the measured phenotype (the dependent variable in the regression) has a known Bernoulli-normal mixture distribution. Finite-sample genome-wide regression p-values (Gwrpv) with a non-normally distributed phenotype (Gregory Connor and Michael O'Neill, bioRxiv 204727 <doi:10.1101/204727>).
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2023-06-16 |
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r-gtx
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public |
Assorted tools for genetic association analyses. The current focus is on implementing (either exactly or approximately) regression analyses using summary statistics instead of using subject-specific data. So far, functions exist to support multi-SNP risk score analyses, multi-SNP conditional regression analyses, and multi-phenotype analyses, using summary statistics. There are helper functions for reading and manipulating subject-specific genotype data, which provide a platform for calculating the summary statistics, or for using R to conduct other analyses not supported by specific GWAS analysis tools.
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2023-06-16 |
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r-growthmodels
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A compilation of nonlinear growth models used in many areas
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2023-06-16 |
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r-gridsvg
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Functions to export graphics drawn with package grid to SVG format. Additional functions provide access to SVG features that are not available in standard R graphics, such as hyperlinks, animation, filters, masks, clipping paths, and gradient and pattern fills.
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2023-06-16 |
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r-graphfactor
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A Network Implementation of Fuzzy Sets: Build Network Objects from Multivariate Flat Files. For more information on fuzzy sets, refer to: Zadeh, L.A. (1964) <DOI:10.1016/S0019-9958(65)90241-X>.
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2023-06-16 |
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r-grader
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After being given the location of your students' submissions and a test file, the function runs each .R file, and evaluates the results from all the given tests. Results are neatly returned in a data frame that has a row for each student, and a column for each test.
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2023-06-16 |
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r-glmx
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public |
Extended techniques for generalized linear models (GLMs), especially for binary responses, including parametric links and heteroskedastic latent variables.
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2023-06-16 |
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r-glmnetutils
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public |
Provides a formula interface for the 'glmnet' package for elasticnet regression, a method for cross-validating the alpha parameter, and other quality-of-life tools.
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2023-06-16 |
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r-glarma
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public |
Functions are provided for estimation, testing, diagnostic checking and forecasting of generalized linear autoregressive moving average (GLARMA) models for discrete valued time series with regression variables. These are a class of observation driven non-linear non-Gaussian state space models. The state vector consists of a linear regression component plus an observation driven component consisting of an autoregressive-moving average (ARMA) filter of past predictive residuals. Currently three distributions (Poisson, negative binomial and binomial) can be used for the response series. Three options (Pearson, score-type and unscaled) for the residuals in the observation driven component are available. Estimation is via maximum likelihood (conditional on initializing values for the ARMA process) optimized using Fisher scoring or Newton Raphson iterative methods. Likelihood ratio and Wald tests for the observation driven component allow testing for serial dependence in generalized linear model settings. Graphical diagnostics including model fits, autocorrelation functions and probability integral transform residuals are included in the package. Several standard data sets are included in the package.
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2023-06-16 |
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r-ghs
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Draw posterior samples to estimate the precision matrix for multivariate Gaussian data. Posterior means of the samples is the graphical horseshoe estimate by Li, Bhadra and Craig(2017) <arXiv:1707.06661>. The function uses matrix decomposition and variable change from the Bayesian graphical lasso by Wang(2012) <doi:10.1214/12-BA729>, and the variable augmentation for sampling under the horseshoe prior by Makalic and Schmidt(2016) <arXiv:1508.03884>. Structure of the graphical horseshoe function was inspired by the Bayesian graphical lasso function using blocked sampling, authored by Wang(2012) <doi:10.1214/12-BA729>.
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2023-06-16 |
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r-geosapi
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Provides an R interface to the GeoServer REST API, allowing to upload and publish data in a GeoServer web-application and expose data to OGC Web-Services. The package currently supports all CRUD (Create,Read,Update,Delete) operations on GeoServer workspaces, namespaces, datastores (stores of vector data), featuretypes, layers, styles, as well as vector data upload operations. For more information about the GeoServer REST API, see <http://docs.geoserver.org/stable/en/user/rest/>.
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2023-06-16 |
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r-geometa
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Provides facilities to handle reading and writing of geographic metadata defined with OGC/ISO 19115, 11119 and 19110 geographic information metadata standards, and encoded using the ISO 19139 (XML) standard. It includes also a facility to check the validity of ISO 19139 XML encoded metadata.
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2023-06-16 |
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r-genord
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A gaussian copula based procedure for generating samples from discrete random variables with prescribed correlation matrix and marginal distributions.
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2023-06-16 |
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r-genetics
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Classes and methods for handling genetic data. Includes classes to represent genotypes and haplotypes at single markers up to multiple markers on multiple chromosomes. Function include allele frequencies, flagging homo/heterozygotes, flagging carriers of certain alleles, estimating and testing for Hardy-Weinberg disequilibrium, estimating and testing for linkage disequilibrium, ...
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2023-06-16 |
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r-gdadata
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Datasets used in the book 'Graphical Data Analysis with R' (Antony Unwin, CRC Press 2015).
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2023-06-16 |
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r-geem
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GEE estimation of the parameters in mean structures with possible correlation between the outcomes. User-specified mean link and variance functions are allowed, along with observation weighting. The 'M' in the name 'geeM' is meant to emphasize the use of the Matrix package, which allows for an implementation based fully in R.
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2023-06-16 |
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r-gcai.bias
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Many inherited biases and effects exists in RNA-seq due to both biological and technical effects. We observed the biological variance of testing target transcripts can influence the yield of sequencing reads, which might indicate a resource competition existing in RNA-seq. We developed this package to capture the bias depending on local sequence and perform the correction of this type of bias by borrowing information from spike-in measurement.
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2023-06-16 |
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r-laplacesdemon
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Provides a complete environment for Bayesian inference using a variety of different samplers (see ?LaplacesDemon for an overview). The README describes the history of the package development process.
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2023-06-16 |
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r-landpred
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This package includes functions for landmark prediction of a survival outcome incorporating covariate and short-term event information. For more information about landmark prediction please see: Parast, Layla, Su-Chun Cheng, and Tianxi Cai. Incorporating short-term outcome information to predict long-term survival with discrete markers. Biometrical Journal 53.2 (2011): 294-307.
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2023-06-16 |
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r-lambda4
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Currently the package includes 14 methods for calculating internal consistency reliability but is still growing. The package allows users access to whichever reliability estimator is deemed most appropriate for their situation.
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2023-06-16 |
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r-labelvector
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Labels are a common construct in statistical software providing a human readable description of a variable. While variable names are succinct, quick to type, and follow a language's naming conventions, labels may be more illustrative and may use plain text and spaces. R does not provide native support for labels. Some packages, however, have made this feature available. Most notably, the 'Hmisc' package provides labelling methods for a number of different object. Due to design decisions, these methods are not all exported, and so are unavailable for use in package development. The 'labelVector' package supports labels for atomic vectors in a light-weight design that is suitable for use in other packages.
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2023-06-16 |
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r-kofnga
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Provides a function that uses a genetic algorithm to search for a subset of size k from the integers 1:n, such that a user-supplied objective function is minimized at that subset. The selection step is done by tournament selection based on ranks, and elitism may be used to retain a portion of the best solutions from one generation to the next. Population objective function values may optionally be evaluated in parallel.
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2023-06-16 |
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r-klustr
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Used to create dynamic, interactive 'D3.js' based parallel coordinates and principal component plots in 'R'. The plots make visualizing k-means or other clusters simple and informative.
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2023-06-16 |
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r-kinship2
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Routines to handle family data with a pedigree object (2014, <doi: 10.1159/000363105>). The initial purpose was to create correlation structures that describe family relationships such as kinship and identity-by-descent, which can be used to model family data in mixed effects models, such as in the coxme function. Also includes a tool for pedigree drawing which is focused on producing compact layouts without intervention. Recent additions include utilities to trim the pedigree object with various criteria, and kinship for the X chromosome.
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2023-06-16 |
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r-itop
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Infers a topology of relationships between different datasets, such as multi-omics and phenotypic data recorded on the same samples. We based this methodology on the RV coefficient (Robert & Escoufier, 1976, <doi:10.2307/2347233>), a measure of matrix correlation, which we have extended for partial matrix correlations and binary data (Aben et al., 2018, <doi:10.1101/293993>).
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2023-06-16 |
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r-isopat
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The function calculates the isotopic pattern (fine structures) for a given chemical formula.
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2023-06-16 |
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r-iqlearn
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public |
Estimate an optimal dynamic treatment regime using Interactive Q-learning.
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2023-06-16 |
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r-ipcwswitch
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Contains functions for formatting clinical trials data and implementing inverse probability of censoring weights to handle treatment switches when estimating causal treatment effect in randomized clinical trials.
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2023-06-16 |
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r-inum
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Enum-type representation of vectors and representation of intervals, including a method of coercing variables in data frames.
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2023-06-16 |
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r-influence.sem
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A set of tools for evaluating several measures of case influence for structural equation models.
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2023-06-16 |
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r-inflection
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Implementation of methods Extremum Surface Estimator (ESE) and Extremum Distance Estimator (EDE) to identify the inflection point of a curve . Christopoulos, DT (2014) <arXiv:1206.5478v2 [math.NA]> . Christopoulos, DT (2016) <https://veltech.edu.in/wp-content/uploads/2016/04/Paper-04-2016.pdf> . Christopoulos, DT (2016) <doi:10.2139/ssrn.3043076> .
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2023-06-16 |
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r-ineq
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Inequality, concentration, and poverty measures. Lorenz curves (empirical and theoretical).
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2023-06-16 |
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r-indtestpp
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Several parametric and non-parametric tests and measures to check independence between two or more (homogeneous or nonhomogeneous) point processes in time are provided. Tools for simulating point processes in one dimension with different types of dependence are also implemented.
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2023-06-16 |
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r-imputer
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Multivariate Expectation-Maximization (EM) based imputation framework that offers several different algorithms. These include regularisation methods like Lasso and Ridge regression, tree-based models and dimensionality reduction methods like PCA and PLS.
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2023-06-16 |
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r-iemiscdata
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Miscellaneous data sets [Engineering Economics, Environmental/ Water Resources Engineering, US Presidential Elections].
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2023-06-16 |
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r-icsw
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Provides the necessary tools to estimate average treatment effects with an instrumental variable by re-weighting observations using a model of compliance.
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2023-06-16 |
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r-icods
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Sieve semiparametric likelihood methods for analyzing interval-censored failure time data from an outcome-dependent sampling (ODS) design and from a case-cohort design. Zhou, Q., Cai, J., and Zhou, H. (2018) <doi:10.1111/biom.12744>; Zhou, Q., Zhou, H., and Cai, J. (2017) <doi:10.1093/biomet/asw067>.
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2023-06-16 |
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r-hydrostats
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Calculates a suite of hydrologic indices for daily time series data that are widely used in hydrology and stream ecology.
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2023-06-16 |
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r-humanformat
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Format quantities of time or bytes into human-friendly strings.
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2023-06-16 |
