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r-jrich
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public |
These functions calculate the taxonomic measures presented in Miranda-Esquivel (2016). The package introduces Jack-knife resampling in evolutionary distinctiveness prioritization analysis, as a way to evaluate the support of the ranking in area prioritization, and the persistence of a given area in a conservation analysis. The algorithm is described in: Miranda-Esquivel, D (2016) <DOI:10.1007/978-3-319-22461-9_11>.
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2024-01-16 |
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r-jrc
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public |
An 'httpuv' based bridge between R and 'JavaScript'. Provides an easy way to exchange commands and data between a web page and a currently running R session.
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2024-01-16 |
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r-jquerylib
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public |
Obtain any major version of 'jQuery' (<https://code.jquery.com/>) and use it in any webpage generated by 'htmltools' (e.g. 'shiny', 'htmlwidgets', and 'rmarkdown'). Most R users don't need to use this package directly, but other R packages (e.g. 'shiny', 'rmarkdown', etc.) depend on this package to avoid bundling redundant copies of 'jQuery'.
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2024-01-16 |
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r-jpen
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public |
A Joint PENalty Estimation of Covariance and Inverse Covariance Matrices.
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2024-01-16 |
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r-jose
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public |
Read and write JSON Web Keys (JWK, rfc7517), generate and verify JSON Web Signatures (JWS, rfc7515) and encode/decode JSON Web Tokens (JWT, rfc7519). These standards provide modern signing and encryption formats that are natively supported by browsers via the JavaScript WebCryptoAPI, and used by services like OAuth 2.0, LetsEncrypt, and Github Apps.
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2024-01-16 |
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r-josae
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public |
Implementation of some unit and area level EBLUP estimators as well as the estimators of their MSE also under heteroscedasticity. The package further documents the publications Breidenbach and Astrup (2012) <DOI:10.1007/s10342-012-0596-7>, Breidenbach et al. (2016) <DOI:10.1016/j.rse.2015.07.026> and Breidenbach et al. (2018 in press). The vignette further explains the use of the implemented functions.
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2024-01-16 |
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r-josaplay
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public |
Josa in Korean is often determined by judging the previous word. When writing reports using Rmd, a function that prints the appropriate investigation for each case is helpful. The 'josaplay' package then evaluates the previous word to determine which josa is appropriate.
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2024-01-16 |
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r-jointpm
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public |
Estimate risk caused by two extreme and dependent forcing variables using bivariate extreme value models as described in Zheng, Westra, and Sisson (2013) <doi:10.1016/j.jhydrol.2013.09.054>; Zheng, Westra and Leonard (2014) <doi:10.1002/2013WR014616>; Zheng, Leonard and Westra (2015) <doi:10.2166/hydro.2015.052>.
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2024-01-16 |
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r-jgr
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public |
Java GUI for R - cross-platform, universal and unified Graphical User Interface for R. For full functionality on Windows and Mac OS X JGR requires a start application which depends on your OS.
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2024-01-16 |
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r-jointnmix
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public |
Fits univariate and joint N-mixture models for data on two unmarked site-associated species. Includes functions to estimate latent abundances through empirical Bayes methods.
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2024-01-16 |
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r-joint.cox
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public |
Fit survival data and perform dynamic prediction under joint frailty-copula models for tumour progression and death. Likelihood-based methods are employed for estimating model parameters, where the baseline hazard functions are modeled by the cubic M-spline or the Weibull model. The methods are applicable for meta-analytic data containing individual-patient information from several studies. Survival outcomes need information on both terminal event time (e.g., time-to-death) and non-terminal event time (e.g., time-to-tumour progression). Methodologies were published in Emura et al. (2017) <doi:10.1177/0962280215604510>, Emura et al. (2018) <doi:10.1177/0962280216688032>, Emura et al. (2020) <doi:10.1177/0962280219892295>, Shinohara et al. (2020) <doi:10.1080/03610918.2020.1855449>, Wu et al. (2020) <doi:10.1007/s00180-020-00977-1>, and Emura et al. (2021) <doi:10.1177/09622802211046390>. See also the book of Emura et al. (2019) <doi:10.1007/978-981-13-3516-7>. Survival data from ovarian cancer patients are also available.
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2024-01-16 |
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r-jmvcore
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public |
A framework for creating rich interactive analyses for the jamovi platform (see <https://www.jamovi.org> for more information).
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2024-01-16 |
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r-ivreg
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public |
Instrumental variable estimation for linear models by two-stage least-squares (2SLS) regression or by robust-regression via M-estimation (2SM) or MM-estimation (2SMM). The main ivreg() model-fitting function is designed to provide a workflow as similar as possible to standard lm() regression. A wide range of methods is provided for fitted ivreg model objects, including extensive functionality for computing and graphing regression diagnostics in addition to other standard model tools.
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2024-01-16 |
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r-jmuoutlier
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public |
Performs a permutation test on the difference between two location parameters, a permutation correlation test, a permutation F-test, the Siegel-Tukey test, a ratio mean deviance test. Also performs some graphing techniques, such as for confidence intervals, vector addition, and Fourier analysis; and includes functions related to the Laplace (double exponential) and triangular distributions. Performs power calculations for the binomial test.
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2024-01-16 |
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r-jmisc
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public |
Some handy function in R.
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2024-01-16 |
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r-jmdesign
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public |
Performs power calculations for joint modeling of longitudinal and survival data with k-th order trajectories when the variance-covariance matrix, Sigma_theta, is unknown.
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2024-01-16 |
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r-jmetrik
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public |
The main purpose of this package is to make it easy for userR's to interact with 'jMetrik' an open source application for psychometric analysis. For example it allows useR's to write data frames to file in a format that can be used by 'jMetrik'. It also allows useR's to read *.jmetrik files (e.g. output from an analysis) for follow-up analysis in R. The *.jmetrik format is a flat file that includes a multiline header and the data as comma separated values. The header includes metadata about the file and one row per variable with the following information in each row: variable name, data type, item scoring, special data codes, and variable label.
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2024-01-16 |
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r-jm
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public |
Shared parameter models for the joint modeling of longitudinal and time-to-event data.
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2024-01-16 |
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r-jjb
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public |
Set of common functions used for manipulating colors, detecting and interacting with 'RStudio', modeling, formatting, determining users' operating system, feature scaling, and more!
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2024-01-16 |
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r-jlctree
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public |
Implements the tree-based approach to joint modeling of time-to-event and longitudinal data. This approach looks for a tree-based partitioning such that within each estimated latent class defined by a terminal node, the time-to-event and longitudinal responses display a lack of association. See Zhang and Simonoff (2018) <arXiv:1812.01774>.
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2024-01-16 |
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r-jiebard
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public |
jiebaR is a package for Chinese text segmentation, keyword extraction and speech tagging. This package provides the data files required by jiebaR.
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2024-01-16 |
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r-ivmodel
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public |
Carries out instrumental variable estimation of causal effects, including power analysis, sensitivity analysis, and diagnostics. See Kang, Jiang, Zhao, and Small (2020) <http://pages.cs.wisc.edu/~hyunseung/> for details.
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2024-01-16 |
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r-jgl
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public |
The Joint Graphical Lasso is a generalized method for estimating Gaussian graphical models/ sparse inverse covariance matrices/ biological networks on multiple classes of data. We solve JGL under two penalty functions: The Fused Graphical Lasso (FGL), which employs a fused penalty to encourage inverse covariance matrices to be similar across classes, and the Group Graphical Lasso (GGL), which encourages similar network structure between classes. FGL is recommended over GGL for most applications. Reference: Danaher P, Wang P, Witten DM. (2013) <doi:10.1111/rssb.12033>.
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2024-01-16 |
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r-jeek
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public |
Provides a fast and scalable joint estimator for integrating additional knowledge in learning multiple related sparse Gaussian Graphical Models (JEEK). The JEEK algorithm can be used to fast estimate multiple related precision matrices in a large-scale. For instance, it can identify multiple gene networks from multi-context gene expression datasets. By performing data-driven network inference from high-dimensional and heterogeneous data sets, this tool can help users effectively translate aggregated data into knowledge that take the form of graphs among entities. Please run demo(jeek) to learn the basic functions provided by this package. For further details, please read the original paper: Beilun Wang, Arshdeep Sekhon, Yanjun Qi "A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models" (ICML 2018) <arXiv:1806.00548>.
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2024-01-16 |
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r-jetpack
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public |
Manage project dependencies from your DESCRIPTION file. Create a reproducible virtual environment with minimal additional files in your project. Provides tools to add, remove, and update dependencies as well as install existing dependencies with a single function.
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2024-01-16 |
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r-jdmbs
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public |
Option is a one of the financial derivatives and its pricing is an important problem in practice. The process of stock prices are represented as Geometric Brownian motion [Black (1973) <doi:10.1086/260062>] or jump diffusion processes [Kou (2002) <doi:10.1287/mnsc.48.8.1086.166>]. In this package, algorithms and visualizations are implemented by Monte Carlo method in order to calculate European option price for three equations by Geometric Brownian motion and jump diffusion processes and furthermore a model that presents jumps among companies affect each other.
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2024-01-16 |
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r-jcp
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public |
Procedures for joint detection of changes in both expectation and variance in univariate sequences. Performs a statistical test of the null hypothesis of the absence of change points. In case of rejection performs an algorithm for change point detection. Reference - Bivariate change point detection - joint detection of changes in expectation and variance, Scandinavian Journal of Statistics, DOI 10.1111/sjos.12547.
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2024-01-16 |
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r-itsadug
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public |
GAMM (Generalized Additive Mixed Modeling; Lin & Zhang, 1999) as implemented in the R package 'mgcv' (Wood, S.N., 2006; 2011) is a nonlinear regression analysis which is particularly useful for time course data such as EEG, pupil dilation, gaze data (eye tracking), and articulography recordings, but also for behavioral data such as reaction times and response data. As time course measures are sensitive to autocorrelation problems, GAMMs implements methods to reduce the autocorrelation problems. This package includes functions for the evaluation of GAMM models (e.g., model comparisons, determining regions of significance, inspection of autocorrelational structure in residuals) and interpreting of GAMMs (e.g., visualization of complex interactions, and contrasts).
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2024-01-16 |
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r-janitor
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public |
The main janitor functions can: perfectly format data.frame column names; provide quick counts of variable combinations (i.e., frequency tables and crosstabs); and explore duplicate records. Other janitor functions nicely format the tabulation results. These tabulate-and-report functions approximate popular features of SPSS and Microsoft Excel. This package follows the principles of the "tidyverse" and works well with the pipe function %>%. janitor was built with beginning-to-intermediate R users in mind and is optimized for user-friendliness.
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2024-01-16 |
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r-janeaustenr
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public |
Full texts for Jane Austen's 6 completed novels, ready for text analysis. These novels are "Sense and Sensibility", "Pride and Prejudice", "Mansfield Park", "Emma", "Northanger Abbey", and "Persuasion".
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2024-01-16 |
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r-jaggr
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public |
All the data and functions used to produce the book. We do not expect most people to use the package for any other reason than to get simple access to the 'JAGS' model files, the data, and perhaps run some of the simple examples. The authors of the book are David Lucy (now sadly deceased) and James Curran. It is anticipated that a manuscript will be provided to Taylor and Francis around February 2020, with bibliographic details to follow at that point. Until such time, further information can be obtained by emailing James Curran.
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2024-01-16 |
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r-jacpop
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public |
Uses the Jaccard similarity index to account for population structure in sequencing studies. This method was specifically designed to detect population stratification based on rare variants, hence it will be especially useful in rare variant analysis.
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2024-01-16 |
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r-jaatha
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public |
An estimation method that can use computer simulations to approximate maximum-likelihood estimates even when the likelihood function can not be evaluated directly. It can be applied whenever it is feasible to conduct many simulations, but works best when the data is approximately Poisson distributed. It was originally designed for demographic inference in evolutionary biology (Naduvilezhath et al., 2011 <doi:10.1111/j.1365-294X.2011.05131.x>, Mathew et al., 2013 <doi:10.1002/ece3.722>). It has optional support for conducting coalescent simulation using the 'coala' package.
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2024-01-16 |
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r-ivprobit
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public |
Compute the instrumental variables probit model using the Amemiya's Generalized Least Squares estimators (Amemiya, Takeshi, (1978) <doi: 10.2307/1911443>).
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2024-01-16 |
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r-itsmr
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public |
Provides functions for modeling and forecasting time series data. Forecasting is based on the innovations algorithm. A description of the innovations algorithm can be found in the textbook "Introduction to Time Series and Forecasting" by Peter J. Brockwell and Richard A. Davis. <https://link.springer.com/book/10.1007/b97391>.
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2024-01-16 |
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r-iterativehardthresholding
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public |
Fits large-scale regression models with a penalty that restricts the maximum number of non-zero regression coefficients to a prespecified value. While Chu et al (2020) <doi:10.1093/gigascience/giaa044> describe the basic algorithm, this package uses Cyclops for an efficient implementation.
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2024-01-16 |
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r-isorix
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public |
Building isoscapes using mixed models and inferring the geographic origin of samples based on their isotopic ratios. This package is essentially a simplified interface to several other packages which implements a new statistical framework based on mixed models. It uses 'spaMM' for fitting and predicting isoscapes, and assigning an organism's origin depending on its isotopic ratio. 'IsoriX' also relies heavily on the package 'rasterVis' for plotting the maps produced with 'terra' using 'lattice'.
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2024-01-16 |
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r-itop
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public |
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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2024-01-16 |
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r-islr2
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public |
We provide the collection of data-sets used in the book 'An Introduction to Statistical Learning with Applications in R, Second Edition'. These include many data-sets that we used in the first edition (some with minor changes), and some new datasets.
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2024-01-16 |
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r-itertools2
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public |
A port of Python's excellent itertools module to R for efficient looping.
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2024-01-16 |
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r-itertools
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public |
Various tools for creating iterators, many patterned after functions in the Python itertools module, and others patterned after functions in the 'snow' package.
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2024-01-16 |
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r-iterpc
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public |
Iterator for generating permutations and combinations. They can be either drawn with or without replacement, or with distinct/ non-distinct items (multiset). The generated sequences are in lexicographical order (dictionary order). The algorithms to generate permutations and combinations are memory efficient. These iterative algorithms enable users to process all sequences without putting all results in the memory at the same time. The algorithms are written in C/C++ for faster performance. Note: 'iterpc' is no longer being maintained. Users are recommended to switch to 'arrangements'.
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2024-01-16 |
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r-iterators
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Support for iterators, which allow a programmer to traverse through all the elements of a vector, list, or other collection of data.
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2024-01-16 |
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r-italy
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Provides two record linkage data sets on the Italian Survey on Household and Wealth, 2008 and 2010, a sample survey conducted by the Bank of Italy every two years. The 2010 survey covered 13,702 individuals, while the 2008 survey covered 13,734 individuals. The following categorical variables are included in this data set: year of birth, working status, employment status, branch of activity, town size, geographical area of birth, sex, whether or not Italian national, and highest educational level obtained. Unique identifiers are available to assess the accuracy of one’s method. Please see Steorts (2015) <DOI:10.1214/15-BA965SI> to find more details about the data set.
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2024-01-16 |
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r-iswr
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Data sets and scripts for text examples and exercises in P. Dalgaard (2008), `Introductory Statistics with R', 2nd ed., Springer Verlag, ISBN 978-0387790534.
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2024-01-16 |
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r-isingfit
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This network estimation procedure eLasso, which is based on the Ising model, combines l1-regularized logistic regression with model selection based on the Extended Bayesian Information Criterion (EBIC). EBIC is a fit measure that identifies relevant relationships between variables. The resulting network consists of variables as nodes and relevant relationships as edges. Can deal with binary data.
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2024-01-16 |
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r-istacr
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You can access to open data published in Instituto Canario De Estadistica (ISTAC) APIs at <https://datos.canarias.es/api/estadisticas/>.
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2024-01-16 |
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r-isoweek
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public |
This is an substitute for the %V and %u formats which are not implemented on Windows. In addition, the package offers functions to convert from standard calender format yyyy-mm-dd to and from ISO 8601 week format yyyy-Www-d.
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2024-01-16 |
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r-isotonic.pen
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public |
Given a response y and a one- or two-dimensional predictor, the isotonic regression estimator is calculated with the usual orderings.
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2024-01-16 |
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r-isoplotr
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Plots U-Pb data on Wetherill and Tera-Wasserburg concordia diagrams. Calculates concordia and discordia ages. Performs linear regression of measurements with correlated errors using 'York', 'Titterington', 'Ludwig' and Omnivariant Generalised Least-Squares ('OGLS') approaches. Generates Kernel Density Estimates (KDEs) and Cumulative Age Distributions (CADs). Produces Multidimensional Scaling (MDS) configurations and Shepard plots of multi-sample detrital datasets using the Kolmogorov-Smirnov distance as a dissimilarity measure. Calculates 40Ar/39Ar ages, isochrons, and age spectra. Computes weighted means accounting for overdispersion. Calculates U-Th-He (single grain and central) ages, logratio plots and ternary diagrams. Processes fission track data using the external detector method and LA-ICP-MS, calculates central ages and plots fission track and other data on radial (a.k.a. 'Galbraith') plots. Constructs total Pb-U, Pb-Pb, Th-Pb, K-Ca, Re-Os, Sm-Nd, Lu-Hf, Rb-Sr and 230Th-U isochrons as well as 230Th-U evolution plots.
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2024-01-16 |
