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r-distributions3
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Tools to create and manipulate probability distributions using S3. Generics random(), pdf(), cdf() and quantile() provide replacements for base R's r/d/p/q style functions. Functions and arguments have been named carefully to minimize confusion for students in intro stats courses. The documentation for each distribution contains detailed mathematical notes.
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2023-06-16 |
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r-dostats
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A small package containing helper utilities for creating function for computing statistics.
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2023-06-16 |
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r-dockerfiler
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Build a Dockerfile straight from your R session. 'dockerfiler' allows you to create step by step a Dockerfile, and provide convenient tools to wrap R code inside this Dockerfile.
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2023-06-16 |
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r-dobson
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Example datasets from the book "An Introduction to Generalised Linear Models" (Year: 2018, ISBN:9781138741515) by Dobson and Barnett.
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2023-06-16 |
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r-dr
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Functions, methods, and datasets for fitting dimension reduction regression, using slicing (methods SAVE and SIR), Principal Hessian Directions (phd, using residuals and the response), and an iterative IRE. Partial methods, that condition on categorical predictors are also available. A variety of tests, and stepwise deletion of predictors, is also included. Also included is code for computing permutation tests of dimension. Adding additional methods of estimating dimension is straightforward. For documentation, see the vignette in the package. With version 3.0.4, the arguments for dr.step have been modified.
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2023-06-16 |
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r-doublecone
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Performs hypothesis tests concerning a regression function in a least-squares model, where the null is a parametric function, and the alternative is the union of large-dimensional convex polyhedral cones. See Bodhisattva Sen and Mary C Meyer (2016) <doi:10.1111/rssb.12178> for more details.
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2023-06-16 |
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r-dominanceanalysis
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Dominance analysis is a method that allows to compare the relative importance of predictors in multiple regression models: ordinary least squares, generalized linear models and hierarchical linear models. The main principles and methods of dominance analysis are described in Budescu, D. V. (1993) <doi:10.1037/0033-2909.114.3.542> and Azen, R., & Budescu, D. V. (2003) <doi:10.1037/1082-989X.8.2.129> for ordinary least squares regression. Subsequently, the extensions for multivariate regression, logistic regression and hierarchical linear models were described in Azen, R., & Budescu, D. V. (2006) <doi:10.3102/10769986031002157>, Azen, R., & Traxel, N. (2009) <doi:10.3102/1076998609332754> and Luo, W., & Azen, R. (2013) <doi:10.3102/1076998612458319>, respectively.
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2023-06-16 |
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r-do
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Flexibly convert data between long and wide format using just two functions: reshape_toLong() and reshape_toWide().
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2023-06-16 |
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r-dmrnet
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Model selection algorithms for regression and classification, where the predictors can be numerical and categorical and the number of regressors exceeds the number of observations. The selected model consists of a subset of numerical regressors and partitions of levels of factors. Aleksandra Maj-Kańska, Piotr Pokarowski and Agnieszka Prochenka (2015) <doi:10.1214/15-EJS1050>. Piotr Pokarowski and Jan Mielniczuk (2015) <http://www.jmlr.org/papers/volume16/pokarowski15a/pokarowski15a.pdf>.
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2023-06-16 |
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r-dprint
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Provides a generalized method for printing tabular data within the R environment in order to make the process of presenting high quality tabular output seamless for the user. Output is directed to the R graphics device so that tables can be exported to any file format supported by the graphics device. Utilizes a formula interface to specify the contents of tables often found in manuscripts or business reports. In addition, formula interface provides inline formatting of the numeric cells of a table and renaming column labels.
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2023-06-16 |
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r-dne
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The DnE package involves functions to analyse the distribution of a set of given data. The basic idea of the analysis is chi-squared test. Functions which have the form as "is.xxdistribution" are used to analyse whether the data obeys the xxdistrbution. If you do not know which distribution to judge, use function is.dt().
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2023-06-16 |
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r-edci
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Detection of edge points in images based on the difference of two asymmetric M-kernel estimators. Linear and circular regression clustering based on redescending M-estimators. Detection of linear edges in images.
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2023-06-16 |
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r-ebglmnet
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Provides empirical Bayesian lasso and elastic net algorithms for variable selection and effect estimation. Key features include sparse variable selection and effect estimation via generalized linear regression models, high dimensionality with p>>n, and significance test for nonzero effects. This package outperforms other popular methods such as lasso and elastic net methods in terms of power of detection, false discovery rate, and power of detecting grouping effects.
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2023-06-16 |
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r-arulescba
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Provides a function to build an association rule-based classifier for data frames, and to classify incoming data frames using such a classifier.
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2023-06-16 |
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r-domino
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A wrapper on top of the 'Domino Command-Line Client'. It lets you run 'Domino' commands (e.g., "run", "upload", "download") directly from your R environment. Under the hood, it uses R's system function to run the 'Domino' executable, which must be installed as a prerequisite. 'Domino' is a service that makes it easy to run your code on scalable hardware, with integrated version control and collaboration features designed for analytical workflows (see <http://www.dominodatalab.com> for more information).
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2023-06-16 |
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r-dmt
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Probabilistic dependency modeling toolkit.
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2023-06-16 |
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r-ecodist
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Dissimilarity-based analysis functions including ordination and Mantel test functions, intended for use with spatial and community data.
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2023-06-16 |
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r-dragular
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Move elements between containers in 'Shiny' without explicitly using 'JavaScript'. It can be used to build custom inputs or to change the positions of user interface elements like plots or tables.
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2023-06-16 |
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r-dotdot
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Use '..' on the right hand side of the ':=' operator as a shorthand for the left hand side, so that 'var := f(..) + ..' is equivalent to 'var <- f(var) + var'. This permits the user to be explicit about growing an object or overwriting it using its previous value, avoids repeating a variable name, and saves keystrokes, time, visual space and cognitive load.
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2023-06-16 |
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r-distdrawr
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Download data from the FlorKart database of the floristic field mapping in Germany in a convenient way. The database incorporates distribution data for plants in Germany on the basis of quadrants on a topographical map with a resolution of 1 : 25000 (TK 25). The data is owned and provided by the German Federal Agency for Nature Conservation (BfN) and the Network Phytodiversity in Germany (NetPhyD). For further information please visit <http://www.floraweb.de/pflanzenarten/hintergrundtexte_florkart_organisation.html>. The author of this package is in no way associated with the BfN or NetPhyD.
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2023-06-16 |
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r-edesign
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An implementation of maximum entropy sampling for spatial data is provided. An exact branch-and-bound algorithm as well as greedy and dual greedy heuristics are included.
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2023-06-16 |
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r-ecosolver
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R interface to the Embedded COnic Solver (ECOS), an efficient and robust C library for convex problems. Conic and equality constraints can be specified in addition to integer and boolean variable constraints for mixed-integer problems. This R interface is inspired by the python interface and has similar calling conventions.
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2023-06-16 |
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r-eco
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Implements the Bayesian and likelihood methods proposed in Imai, Lu, and Strauss (2008 <DOI: 10.1093/pan/mpm017>) and (2011 <DOI:10.18637/jss.v042.i05>) for ecological inference in 2 by 2 tables as well as the method of bounds introduced by Duncan and Davis (1953). The package fits both parametric and nonparametric models using either the Expectation-Maximization algorithms (for likelihood models) or the Markov chain Monte Carlo algorithms (for Bayesian models). For all models, the individual-level data can be directly incorporated into the estimation whenever such data are available. Along with in-sample and out-of-sample predictions, the package also provides a functionality which allows one to quantify the effect of data aggregation on parameter estimation and hypothesis testing under the parametric likelihood models.
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2023-06-16 |
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r-eben
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Provides the Empirical Bayesian Elastic Net for handling multicollinearity in generalized linear regression models. As a special case of the 'EBglmnet' package (also available on CRAN), this package encourages a grouping effects to select relevant variables and estimate the corresponding non-zero effects.
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2023-06-16 |
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r-dynamichazard
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Contains functions that lets you fit dynamic hazard models using state space models. The first implemented model is described in Fahrmeir (1992) <doi:10.1080/01621459.1992.10475232> and Fahrmeir (1994) <doi:10.1093/biomet/81.2.317>. Extensions hereof are available where the Extended Kalman filter is replaced by an unscented Kalman filter and other options including particle filters. The implemented particle filters support more general state space models.
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2023-06-16 |
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r-dtd
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Provides fast methods to work with Merton's distance to default model introduced in Merton (1974) <doi:10.1111/j.1540-6261.1974.tb03058.x>. The methods includes simulation and estimation of the parameters.
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2023-06-16 |
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r-driftbursthypothesis
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Calculates the T-Statistic for the drift burst hypothesis from the working paper Christensen, Oomen and Reno (2018) <DOI:10.2139/ssrn.2842535>. The authors' MATLAB code is available upon request, see: <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2842535>.
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2023-06-16 |
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r-blockmodeling
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This is primarily meant as an implementation of generalized blockmodeling for valued networks. In addition, measures of similarity or dissimilarity based on structural equivalence and regular equivalence (REGE algorithms) can be computed and partitioned matrices can be plotted: Žiberna (2007)<doi:10.1016/j.socnet.2006.04.002>, Žiberna (2008)<doi:10.1080/00222500701790207>, Žiberna (2014)<doi:10.1016/j.socnet.2014.04.002>.
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2023-06-16 |
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r-docusignr
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Connect to the 'DocuSign' Rest API <https://www.docusign.com/p/RESTAPIGuide/RESTAPIGuide.htm>, which supports embedded signing, and sending of documents.
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2023-06-16 |
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r-dma
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Dynamic model averaging for binary and continuous outcomes.
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2023-06-16 |
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r-distfree.cr
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Constructs confidence regions without the need to know the sampling distribution of bivariate data. The method was proposed by Zhiqiu Hu & Rong-cai Yang (2013) <doi:10.1371/journal.pone.0081179.g001>.
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2023-06-16 |
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r-dynatree
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Inference by sequential Monte Carlo for dynamic tree regression and classification models with hooks provided for sequential design and optimization, fully online learning with drift, variable selection, and sensitivity analysis of inputs. Illustrative examples from the original dynamic trees paper are facilitated by demos in the package; see demo(package="dynaTree").
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2023-06-16 |
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r-durmod
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Estimation of piecewise constant mixed proportional hazard competing risk model with NPMLE. The model is described in S. Gaure et al. (2007) <doi:10.1016/j.jeconom.2007.01.015>, J. Heckman and B. Singer (1984) <doi:10.2307/1911491>, and B.G. Lindsay (1983) <doi:10.1214/aos/1176346059>.
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2023-06-16 |
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r-dqshiny
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Provides highly customizable modules to enhance your shiny apps. Includes layout independent collapsible boxes and value boxes, a very fast autocomplete input, rhandsontable extensions for filtering and paging and much more.
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2023-06-16 |
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r-eaf
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Plots of the empirical attainment function for two objectives.
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2023-06-16 |
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r-drimpute
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R codes for imputing dropout events. Many statistical methods in cell type identification, visualization and lineage reconstruction do not account for dropout events ('PCAreduce', 'SC3', 'PCA', 't-SNE', 'Monocle', 'TSCAN', etc). 'DrImpute' can improve the performance of such software by imputing dropout events.
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2023-06-16 |
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r-double.truncation
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Likelihood-based inference methods with doubly-truncated data are developed under various models. Nonparametric models are based on Efron and Petrosian (1999) <doi:10.1080/01621459.1999.10474187> and Emura, Konno, and Michimae (2015) <doi:10.1007/s10985-014-9297-5>. Parametric models from the special exponential family (SEF) are based on Hu and Emura (2015) <doi:10.1007/s00180-015-0564-z> and Emura, Hu and Konno (2017) <doi:10.1007/s00362-015-0730-y>.
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2023-06-16 |
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r-dos
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Contains data sets, examples and software from the book Design of Observational Studies by Paul R. Rosenbaum, New York: Springer, <doi:10.1007/978-1-4419-1213-8>, ISBN 978-1-4419-1212-1.
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2023-06-16 |
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r-disposables
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Create disposable R packages for testing. You can create, install and load multiple R packages with a single function call, and then unload, uninstall and destroy them with another function call. This is handy when testing how some R code or an R package behaves with respect to other packages.
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2023-06-16 |
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r-dispmod
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Functions for estimating Gaussian dispersion regression models (Aitkin, 1987 <doi:10.2307/2347792>), overdispersed binomial logit models (Williams, 1987 <doi:10.2307/2347977>), and overdispersed Poisson log-linear models (Breslow, 1984 <doi:10.2307/2347661>), using a quasi-likelihood approach.
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2023-06-16 |
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r-dishet
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Model cell type heterogeneity of bulk renal cell carcinoma. The observed gene expression in bulk tumor sample is modeled by a log-normal distribution with the location parameter structured as a linear combination of the component-specific gene expressions.
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2023-06-16 |
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r-ecfsup
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Testing the equality of several covariance functions of functional data. Four different methods are implemented: L2-norm with W-S naive, L2-norm with W-S bias-reduced, L2-norm (Zhang 2013) <ISBN:9781439862735>, and sup-norm with resampling (Guo et al. 2017) <arXiv:1609.04232>.
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2023-06-16 |
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r-dnmf
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Discriminant Non-Negative Matrix Factorization aims to extend the Non-negative Matrix Factorization algorithm in order to extract features that enforce not only the spatial locality, but also the separability between classes in a discriminant manner. It refers to three article, Zafeiriou, Stefanos, et al. "Exploiting discriminant information in nonnegative matrix factorization with application to frontal face verification." Neural Networks, IEEE Transactions on 17.3 (2006): 683-695. Kim, Bo-Kyeong, and Soo-Young Lee. "Spectral Feature Extraction Using dNMF for Emotion Recognition in Vowel Sounds." Neural Information Processing. Springer Berlin Heidelberg, 2013. and Lee, Soo-Young, Hyun-Ah Song, and Shun-ichi Amari. "A new discriminant NMF algorithm and its application to the extraction of subtle emotional differences in speech." Cognitive neurodynamics 6.6 (2012): 525-535.
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2023-06-16 |
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r-distcrete
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Creates discretised versions of continuous distribution functions by mapping continuous values to an underlying discrete grid, based on a (uniform) frequency of discretisation, a valid discretisation point, and an integration range. For a review of discretisation methods, see Chakraborty (2015) <doi:10.1186/s40488-015-0028-6>.
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2023-06-16 |
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r-docopt
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Define a command-line interface by just giving it a description in the specific format.
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2023-06-16 |
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r-distillery
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Some very simple method functions for confidence interval calculation, bootstrap resampling, and to distill pertinent information from a potentially complex object; primarily used in common with packages extRemes and SpatialVx.
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2023-06-16 |
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r-disttools
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Provides convenient methods for accessing the data in 'dist' objects with minimal memory and computational overhead. 'disttools' can be used to extract the distance between any pair or combination of points encoded by a 'dist' object using only the indices of those points. This is an improvement over existing functionality, which requires either coercing a 'dist' object into a matrix or calculating the one dimensional index corresponding to a pair of observations. Coercion to a matrix is undesirable because doing so doubles the amount of memory required for storage. In contrast, there is no inherent downside to the latter solution. However, in part due to several edge cases, correctly and efficiently implementing such a solution can be challenging. 'disttools' abstracts away these challenges and provides a simple interface to access the data in a 'dist' object using the latter approach.
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2023-06-16 |
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r-distrib
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A different way for calculating pdf/pmf, cdf, quantile and random data such that the user is able to consider the name of related distribution as an argument and so easily can changed by a changing argument by user. It must be mentioned that the core and computation base of package 'DISTRIB' is package 'stats'. Although similar functions are introduced previously in package 'stats', but the package 'DISTRIB' has some special applications in some special computational programs.
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2023-06-16 |
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r-diseasemapping
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Formatting of population and case data, calculation of Standardized Incidence Ratios, and fitting the BYM model using INLA.
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2023-06-16 |
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r-dlasso
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An implementation of the differentiable lasso (dlasso) and SCAD (dSCAD) using iterative ridge algorithm. This package allows selecting the tuning parameter by AIC, BIC, GIC and GIC.
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2023-06-16 |
