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r-imbalance
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public |
Class imbalance usually damages the performance of classifiers. Thus, it is important to treat data before applying a classifier algorithm. This package includes recent resampling algorithms in the literature: (Barua et al. 2014) <doi:10.1109/tkde.2012.232>; (Das et al. 2015) <doi:10.1109/tkde.2014.2324567>, (Zhang et al. 2014) <doi:10.1016/j.inffus.2013.12.003>; (Gao et al. 2014) <doi:10.1016/j.neucom.2014.02.006>; (Almogahed et al. 2014) <doi:10.1007/s00500-014-1484-5>. It also includes an useful interface to perform oversampling.
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2024-01-16 |
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r-influencer
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public |
Provides functionality to compute various node centrality measures on networks. Included are functions to compute betweenness centrality (by utilizing Madduri and Bader's SNAP library), implementations of constraint and effective network size by Burt (2000) <doi:10.1016/S0191-3085(00)22009-1>; algorithm to identify key players by Borgatti (2006) <doi:10.1007/s10588-006-7084-x>; and the bridging algorithm by Valente and Fujimoto (2010) <doi:10.1016/j.socnet.2010.03.003>. On Unix systems, the betweenness, Key Players, and bridging implementations are parallelized with OpenMP, which may run faster on systems which have OpenMP configured.
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2024-01-16 |
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r-inca
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public |
Specific functions are provided for rounding real weights to integers and performing an integer programming algorithm for calibration problems. They are useful for census-weights adjustments, or for performing linear regression with integer parameters. This research was supported in part by the U.S. Department of Agriculture, National Agriculture Statistics Service. The findings and conclusions in this publication are those of the authors and should not be construed to represent any official USDA, or US Government determination or policy.
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2024-01-16 |
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r-imputets
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public |
Imputation (replacement) of missing values in univariate time series. Offers several imputation functions and missing data plots. Available imputation algorithms include: 'Mean', 'LOCF', 'Interpolation', 'Moving Average', 'Seasonal Decomposition', 'Kalman Smoothing on Structural Time Series models', 'Kalman Smoothing on ARIMA models'. Published in Moritz and Bartz-Beielstein (2017) <doi:10.32614/RJ-2017-009>.
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2024-01-16 |
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r-ijtiff
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public |
General purpose TIFF file I/O for R users. Currently the only such package with read and write support for TIFF files with floating point (real-numbered) pixels, and the only package that can correctly import TIFF files that were saved from 'ImageJ' and write TIFF files than can be correctly read by 'ImageJ' <https://imagej.nih.gov/ij/>. Also supports text image I/O.
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2024-01-16 |
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r-imptree
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public |
Creation of imprecise classification trees. They rely on probability estimation within each node by means of either the imprecise Dirichlet model or the nonparametric predictive inference approach. The splitting variable is selected by the strategy presented in Fink and Crossman (2013) <http://www.sipta.org/isipta13/index.php?id=paper&paper=014.html>, but also the original imprecise information gain of Abellan and Moral (2003) <doi:10.1002/int.10143> is covered.
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2024-01-16 |
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r-ichimoku
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public |
An implementation of 'Ichimoku Kinko Hyo', also commonly known as 'cloud charts'. Static and interactive visualizations with tools for creating, backtesting and development of quantitative 'ichimoku' strategies. As described in Sasaki (1996, ISBN:4925152009), the technique is a refinement on candlestick charting, originating from Japan and now in widespread use in technical analysis worldwide. Translating as 'one-glance equilibrium chart', it allows the price action and market structure of financial securities to be determined 'at-a-glance'. Incorporates an interface with the OANDA fxTrade API <https://developer.oanda.com/> for retrieving historical and live streaming price data for major currencies, metals, commodities, government bonds and stock indices.
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2024-01-16 |
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r-hypervolume
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public |
Estimates the shape and volume of high-dimensional datasets and performs set operations: intersection / overlap, union, unique components, inclusion test, and hole detection. Uses stochastic geometry approach to high-dimensional kernel density estimation, support vector machine delineation, and convex hull generation. Applications include modeling trait and niche hypervolumes and species distribution modeling.
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2024-01-16 |
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r-immigrate
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public |
Based on large margin principle, this package performs feature selection methods: "IM4E"(Iterative Margin-Maximization under Max-Min Entropy Algorithm); "Immigrate"(Iterative Max-Min Entropy Margin-Maximization with Interaction Terms Algorithm); "BIM"(Boosted version of IMMIGRATE algorithm); "Simba"(Iterative Search Margin Based Algorithm); "LFE"(Local Feature Extraction Algorithm). This package also performs prediction for the above feature selection methods.
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2024-01-16 |
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r-hutilscpp
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public |
Provides utility functions that are simply, frequently used, but may require higher performance that what can be obtained from base R. Incidentally provides support for 'reverse geocoding', such as matching a point with its nearest neighbour in another array. Used as a complement to package 'hutils' by sacrificing compilation or installation time for higher running speeds. The name is a portmanteau of the author and 'Rcpp'.
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2024-01-16 |
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r-imagine
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public |
Provides fast application of image filters to data matrices, using R and C++ algorithms.
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2024-01-16 |
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r-igraph
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None |
Routines for simple graphs and network analysis. It can handle large graphs very well and provides functions for generating random and regular graphs, graph visualization, centrality methods and much more.
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2024-01-16 |
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r-ifs
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public |
Iterated Function Systems Estimator as in Iacus and La Torre (2005) <doi:10.1155/JAMDS.2005.33>.
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2024-01-16 |
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r-ifctools
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public |
Provides utility functions to deal with Italian fiscal code ('codice fiscale').
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2024-01-16 |
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r-idpmisc
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public |
Different high-level graphics functions for displaying large datasets, displaying circular data in a very flexible way, finding local maxima, brewing color ramps, drawing nice arrows, zooming 2D-plots, creating figures with differently colored margin and plot region. In addition, the package contains auxiliary functions for data manipulation like omitting observations with irregular values or selecting data by logical vectors, which include NAs. Other functions are especially useful in spectroscopy and analyses of environmental data: robust baseline fitting, finding peaks in spectra, converting humidity measures.
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2024-01-16 |
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r-ieeeround
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public |
A pair of functions for getting and setting the IEEE rounding mode for floating point computations.
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2024-01-16 |
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r-icsnp
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public |
Tools for multivariate nonparametrics, as location tests based on marginal ranks, spatial median and spatial signs computation, Hotelling's T-test, estimates of shape are implemented.
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2024-01-16 |
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r-icranks
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public |
Algorithms to construct simultaneous confidence intervals for the ranks of means mu_1,...,mu_n based on an independent Gaussian sample using multiple testing techniques.
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2024-01-16 |
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r-iccbeta
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public |
A function and vignettes for computing an intraclass correlation described in Aguinis & Culpepper (2015) <doi:10.1177/1094428114563618>. This package quantifies the share of variance in a dependent variable that is attributed to group heterogeneity in slopes.
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2024-01-16 |
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r-icr
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public |
Provides functions to compute and plot Krippendorff's inter-coder reliability coefficient alpha and bootstrapped uncertainty estimates (Krippendorff 2004, ISBN:0761915443). The bootstrap routines are set up to make use of parallel threads where supported.
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2024-01-16 |
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r-icenreg
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public |
Regression models for interval censored data. Currently supports Cox-PH, proportional odds, and accelerated failure time models. Allows for semi and fully parametric models (parametric only for accelerated failure time models) and Bayesian parametric models. Includes functions for easy visual diagnostics of model fits and imputation of censored data.
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2024-01-16 |
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r-icensmis
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public |
We consider studies in which information from error-prone diagnostic tests or self-reports are gathered sequentially to determine the occurrence of a silent event. Using a likelihood-based approach incorporating the proportional hazards assumption, we provide functions to estimate the survival distribution and covariate effects. We also provide functions for power and sample size calculations for this setting. Please refer to Xiangdong Gu, Yunsheng Ma, and Raji Balasubramanian (2015) <doi: 10.1214/15-AOAS810>, Xiangdong Gu and Raji Balasubramanian (2016) <doi: 10.1002/sim.6962>, Xiangdong Gu, Mahlet G Tadesse, Andrea S Foulkes, Yunsheng Ma, and Raji Balasubramanian (2020) <doi: 10.1186/s12911-020-01223-w>.
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2024-01-16 |
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r-ibst
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public |
Fit a full or subsampling bagging survival tree on a mixture of population (susceptible and nonsusceptible) using either a pseudo R2 criterion or an adjusted Logrank criterion. The predictor is evaluated using the Out Of Bag Integrated Brier Score (IBS) and several scores of importance are computed for variable selection. The thresholds values for variable selection are computed using a nonparametric permutation test. See 'Cyprien Mbogning' and 'Philippe Broet' (2016)<doi:10.1186/s12859-016-1090-x> for an overview about the methods implemented in this package.
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2024-01-16 |
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r-ibr
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public |
Multivariate smoothing using iterative bias reduction with kernel, thin plate splines, Duchon splines or low rank splines.
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2024-01-16 |
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r-ibs
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public |
Calculate B-spline basis functions with a given set of knots and order, or a B-spline function with a given set of knots and order and set of de Boor points (coefficients), or the integral of a B-spline function.
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2024-01-16 |
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r-ibmcraftr
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public |
It provides a generic set of tools for initializing a synthetic population with each individual in specific disease states, and making transitions between those disease states according to the rates calculated on each timestep. The new version 1.0.0 has C++ code integration to make the functions run faster. It has also a higher level function to actually run the transitions for the number of timesteps that users specify. Additional functions will follow for changing attributes on demographic, health belief and movement.
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2024-01-16 |
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r-ibm
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public |
Implementation of some (simple) Individual Based Models and methods to create new ones, particularly for population dynamics models (reproduction, mortality and movement). The basic operations for the simulations are implemented in Rcpp for speed.
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2024-01-16 |
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r-ibdreg
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public |
Method to test genetic linkage with covariates by regression methods with response IBD sharing for relative pairs. Account for correlations of IBD statistics and covariates for relative pairs within the same pedigree.
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2024-01-16 |
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r-httpgd
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public |
A graphics device for R that is accessible via network protocols. This package was created to make it easier to embed live R graphics in integrated development environments and other applications. The included 'HTML/JavaScript' client (plot viewer) aims to provide a better overall user experience when dealing with R graphics. The device asynchronously serves graphics via 'HTTP' and 'WebSockets'.
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2024-01-16 |
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r-hts
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public |
Provides methods for analysing and forecasting hierarchical and grouped time series. The available forecast methods include bottom-up, top-down, optimal combination reconciliation (Hyndman et al. 2011) <doi:10.1016/j.csda.2011.03.006>, and trace minimization reconciliation (Wickramasuriya et al. 2018) <doi:10.1080/01621459.2018.1448825>.
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2024-01-16 |
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r-humanleague
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public |
Generates high-entropy integer synthetic populations from marginal and (optionally) seed data using quasirandom sampling, in arbitrary dimensionality (Smith, Lovelace and Birkin (2017) <doi:10.18564/jasss.3550>). The package also provides an implementation of the Iterative Proportional Fitting (IPF) algorithm (Zaloznik (2011) <doi:10.13140/2.1.2480.9923>).
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2024-01-16 |
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r-humaniformat
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public |
Human names are complicated and nonstandard things. Humaniformat, which is based on Anthony Ettinger's 'humanparser' project (https://github.com/ chovy/humanparser) provides functions for parsing human names, making a best- guess attempt to distinguish sub-components such as prefixes, suffixes, middle names and salutations.
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2024-01-16 |
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r-huge
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public |
Provides a general framework for high-dimensional undirected graph estimation. It integrates data preprocessing, neighborhood screening, graph estimation, and model selection techniques into a pipeline. In preprocessing stage, the nonparanormal(npn) transformation is applied to help relax the normality assumption. In the graph estimation stage, the graph structure is estimated by Meinshausen-Buhlmann graph estimation or the graphical lasso, and both methods can be further accelerated by the lossy screening rule preselecting the neighborhood of each variable by correlation thresholding. We target on high-dimensional data analysis usually d >> n, and the computation is memory-optimized using the sparse matrix output. We also provide a computationally efficient approach, correlation thresholding graph estimation. Three regularization/thresholding parameter selection methods are included in this package: (1)stability approach for regularization selection (2) rotation information criterion (3) extended Bayesian information criterion which is only available for the graphical lasso.
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2024-01-16 |
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r-httpuv
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None |
Provides low-level socket and protocol support for handling HTTP and WebSocket requests directly from within R. It is primarily intended as a building block for other packages, rather than making it particularly easy to create complete web applications using httpuv alone. httpuv is built on top of the libuv and http-parser C libraries, both of which were developed by Joyent, Inc. (See LICENSE file for libuv and http-parser license information.)
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2024-01-16 |
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r-hlmdiag
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public |
A suite of diagnostic tools for hierarchical (multilevel) linear models. The tools include not only leverage and traditional deletion diagnostics (Cook's distance, covratio, covtrace, and MDFFITS) but also convenience functions and graphics for residual analysis. Models can be fit using either lmer in the 'lme4' package or lme in the 'nlme' package.
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2024-01-16 |
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r-hrqglas
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public |
A program that conducts group variable selection for quantile and robust mean regression (Sherwood and Li, 2022). The group lasso penalty (Yuan and Lin, 2006) is used for group-wise variable selection. Both of the quantile and mean regression models are based on the Huber loss. Specifically, with the tuning parameter in the Huber loss approaching to 0, the quantile check function can be approximated by the Huber loss for the median and the tilted version of Huber loss at other quantiles. Such approximation provides computational efficiency and stability, and has also been shown to be statistical consistent.
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2024-01-16 |
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r-hsdm
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public |
User-friendly and fast set of functions for estimating parameters of hierarchical Bayesian species distribution models (Latimer and others 2006 <doi:10.1890/04-0609>). Such models allow interpreting the observations (occurrence and abundance of a species) as a result of several hierarchical processes including ecological processes (habitat suitability, spatial dependence and anthropogenic disturbance) and observation processes (species detectability). Hierarchical species distribution models are essential for accurately characterizing the environmental response of species, predicting their probability of occurrence, and assessing uncertainty in the model results.
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2024-01-16 |
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r-htdp
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public |
Provides bindings to the National Geodetic Survey (NGS) Horizontal Time Dependent Positioning (HTDP) utility, v3.2.5, written by Richard Snay, Chris Pearson, and Jarir Saleh of NGS. HTDP is a utility that allows users to transform positional coordinates across time and between spatial reference frames. See <https://www.ngs.noaa.gov/TOOLS/Htdp/Htdp.shtml> for more information.
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2024-01-16 |
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r-hpa
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public |
Multivariate conditional and marginal densities, moments, cumulative distribution functions as well as binary choice and sample selection models based on Hermite polynomial approximation which was proposed and described by A. Gallant and D. W. Nychka (1987) <doi:10.2307/1913241>.
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2024-01-16 |
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r-hqreg
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public |
Efficient algorithms for fitting regularization paths for lasso or elastic-net penalized regression models with Huber loss, quantile loss or squared loss.
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2024-01-16 |
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r-hommel
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public |
Provides methods for closed testing using Simes local tests. In particular, calculates adjusted p-values for Hommel's multiple testing method, and provides lower confidence bounds for true discovery proportions. A robust but more conservative variant of the closed testing procedure that does not require the assumption of Simes inequality is also implemented. The methods have been described in detail in Goeman et al (2016) <arXiv:1611.06739v2>.
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2024-01-16 |
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r-hmmextra0s
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public |
Contains functions for hidden Markov models with observations having extra zeros as defined in the following two publications, Wang, T., Zhuang, J., Obara, K. and Tsuruoka, H. (2016) <doi:10.1111/rssc.12194>; Wang, T., Zhuang, J., Buckby, J., Obara, K. and Tsuruoka, H. (2018) <doi:10.1029/2017JB015360>. The observed response variable is either univariate or bivariate Gaussian conditioning on presence of events, and extra zeros mean that the response variable takes on the value zero if nothing is happening. Hence the response is modelled as a mixture distribution of a Bernoulli variable and a continuous variable. That is, if the Bernoulli variable takes on the value 1, then the response variable is Gaussian, and if the Bernoulli variable takes on the value 0, then the response is zero too. This package includes functions for simulation, parameter estimation, goodness-of-fit, the Viterbi algorithm, and plotting the classified 2-D data. Some of the functions in the package are based on those of the R package 'HiddenMarkov' by David Harte. This updated version has included an example dataset and R code examples to show how to transform the data into the objects needed in the main functions. We have also made changes to increase the speed of some of the functions.
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2024-01-16 |
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r-hkprocess
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public |
Methods to make inference about the Hurst-Kolmogorov (fractional Gaussian noise, fGn) and the AR(1) process. Related time series trend tests are also included.
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2024-01-16 |
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r-hmm.discnp
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public |
Fits hidden Markov models with discrete non-parametric observation distributions to data sets. The observations may be univariate or bivariate. Simulates data from such models. Finds most probable underlying hidden states, the most probable sequences of such states, and the log likelihood of a collection of observations given the parameters of the model. Auxiliary predictors are accommodated in the univariate setting.
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2024-01-16 |
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r-hitandrun
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public |
The "Hit and Run" Markov Chain Monte Carlo method for sampling uniformly from convex shapes defined by linear constraints, and the "Shake and Bake" method for sampling from the boundary of such shapes. Includes specialized functions for sampling normalized weights with arbitrary linear constraints. Tervonen, T., van Valkenhoef, G., Basturk, N., and Postmus, D. (2012) <doi:10.1016/j.ejor.2012.08.026>. van Valkenhoef, G., Tervonen, T., and Postmus, D. (2014) <doi:10.1016/j.ejor.2014.06.036>.
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2024-01-16 |
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r-hmb
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public |
For estimation of a variable of interest using two sources of auxiliary information available in a nested structure. For reference see Saarela et al. (2016)<doi:10.1007/s13595-016-0590-1> and Saarela et al. (2018) <doi:10.3390/rs10111832>.
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2024-01-16 |
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r-hlsm
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public |
Implements Hierarchical Latent Space Network Model (HLSM) for ensemble of networks as described in Sweet, Thomas & Junker (2013). <DOI:10.3102/1076998612458702>.
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2024-01-16 |
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r-hipread
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public |
Read hierarchical fixed width files like those commonly used by many census data providers. Also allows for reading of data in chunks, and reading 'gzipped' files without storing the full file in memory.
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2024-01-16 |
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r-hkevp
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public |
Several procedures for the hierarchical kernel extreme value process of Reich and Shaby (2012) <DOI:10.1214/12-AOAS591>, including simulation, estimation and spatial extrapolation. The spatial latent variable model <DOI:10.1214/11-STS376> is also included.
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2024-01-16 |
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r-highs
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public |
R interface to 'HiGHS', an optimization solver for solving mixed integer optimization problems with quadratic or linear objective and linear constraints.
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2024-01-16 |
