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r-lamme
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Log-analytic methods intended for testing multiplicative effects.
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2025-04-22 |
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r-lambda.r
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A language extension to efficiently write functional programs in R. Syntax extensions include multi-part function definitions, pattern matching, guard statements, built-in (optional) type safety.
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2025-04-22 |
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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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2025-04-22 |
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r-lagsequential
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Lag-sequential analysis is a method of assessing of patterns (what tends to follow what?) in sequences of codes. The codes are typically for discrete behaviors or states. The functions in this package read a stream of codes, or a frequency transition matrix, and produce a variety of lag sequential statistics, including transitional frequencies, expected transitional frequencies, transitional probabilities, z values, adjusted residuals, Yule's Q values, likelihood ratio tests of stationarity across time and homogeneity across groups or segments, transformed kappas for unidirectional dependence, bidirectional dependence, parallel and nonparallel dominance, and significance levels based on both parametric and randomization tests. The methods are described in Bakeman & Quera (2011) <doi:10.1017/CBO9781139017343>, O'Connor (1999) <doi:10.3758/BF03200753>, Wampold & Margolin (1982) <doi:10.1037/0033-2909.92.3.755>, and Wampold (1995, ISBN:0-89391-919-5).
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2025-04-22 |
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r-lagged
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Provides classes and methods for lagged objects.
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2025-04-22 |
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r-laercio
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The package contains functions to compare and group means.
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2025-04-22 |
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r-laeken
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Estimation of indicators on social exclusion and poverty, as well as Pareto tail modeling for empirical income distributions.
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2025-04-22 |
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r-labstats
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Contains data sets to accompany the book: Lazic SE (2016). "Experimental Design for Laboratory Biologists: Maximising Information and Improving Reproducibility". Cambridge University Press.
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2025-04-22 |
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r-labstatr
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Insieme di funzioni di supporto al volume "Laboratorio di Statistica con R", Iacus-Masarotto, MacGraw-Hill Italia, 2006. This package contains sets of functions defined in "Laboratorio di Statistica con R", Iacus-Masarotto, MacGraw-Hill Italia, 2006. Function names and docs are in italian as well.
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2025-04-22 |
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r-labrs
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Dati, scripts e funzioni per il libro "Ricerca sociale con R. Concetti e funzioni base per la ricerca sociale" (Datasets, scripts and functions to support the book "Ricerca sociale con R. Concetti e funzioni base per la ricerca sociale").
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2025-04-22 |
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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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2025-04-22 |
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r-label.switching
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The Bayesian estimation of mixture models (and more general hidden Markov models) suffers from the label switching phenomenon, making the MCMC output non-identifiable. This package can be used in order to deal with this problem using various relabelling algorithms.
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2025-04-22 |
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r-labeledloop
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Support labeled loop and escape from nested loop
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2025-04-22 |
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r-l2boost
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Efficient implementation of Friedman's boosting algorithm with l2-loss function and coordinate direction (design matrix columns) basis functions.
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2025-04-22 |
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r-kzs
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A spatial smoothing algorithm based on convolutions of finite rectangular kernels that provides sharp resolution in the presence of high levels of noise.
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2025-04-22 |
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r-kulife
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Provides various functions and data sets from experiments at the Faculty of Life Sciences, University of Copenhagen. This package will be discontinued and archived, and the functions and datasets will be maintained and updated in the MESS package
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2025-04-22 |
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r-kuiper.2samp
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This function performs the two-sample Kuiper test to assess the anomaly of continuous, one-dimensional probability distributions. References used for this method are (1). Kuiper, N. H. (1960). <DOI:10.1016/S1385-7258(60)50006-0> and (2). Paltani, S. (2004). <DOI:10.1051/0004-6361:20034220>.
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2025-04-22 |
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r-kstmatrix
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Knowledge space theory by Doignon and Falmagne (1999) <doi:10.1007/978-3-642-58625-5> is a set- and order-theoretical framework, which proposes mathematical formalisms to operationalize knowledge structures in a particular domain. The 'kstMatrix' package provides basic functionalities to generate, handle, and manipulate knowledge structures and knowledge spaces. Opposed to the 'kst' package, 'kstMatrix' uses matrix representations for knowledge structures. Furthermore, 'kstMatrix' contains several knowledge spaces developed by the research group around Cornelia Dowling through querying experts.
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2025-04-22 |
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r-kstatistics
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Methods and tools for estimate (joint) cumulants of a given population distribution using (multivariate) k-statistics and (multivariate) polykays,symmetric unbiased estimators with minimum variance. For more details see Di Nardo E., Guarino G., Senato D. (2009) <arXiv:0807.5008>.
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2025-04-22 |
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r-kselection
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Selection of k in k-means clustering based on Pham et al. paper ``Selection of k in k-means clustering''.
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2025-04-22 |
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r-kseaapp
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Infers relative kinase activity from phosphoproteomics data using the method described by Casado et al. (2013) <doi:10.1126/scisignal.2003573>.
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2025-04-22 |
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r-ksd
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An adaptation of Kernelized Stein Discrepancy, this package provides a goodness-of-fit test of whether a given i.i.d. sample is drawn from a given distribution. It works for any distribution once its score function (the derivative of log-density) can be provided. This method is based on "A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation" by Liu, Lee, and Jordan, available at <http://arxiv.org/abs/1602.03253>.
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2025-04-22 |
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r-krmm
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Solves kernel ridge regression, within the the mixed model framework, for the linear, polynomial, Gaussian, Laplacian and ANOVA kernels. The model components (i.e. fixed and random effects) and variance parameters are estimated using the expectation-maximization (EM) algorithm. All the estimated components and parameters, e.g. BLUP of dual variables and BLUP of random predictor effects for the linear kernel (also known as RR-BLUP), are available. The kernel ridge mixed model (KRMM) is described in Jacquin L, Cao T-V and Ahmadi N (2016) A Unified and Comprehensible View of Parametric and Kernel Methods for Genomic Prediction with Application to Rice. Front. Genet. 7:145. <doi:10.3389/fgene.2016.00145>.
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2025-04-22 |
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r-krls
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Package implements Kernel-based Regularized Least Squares (KRLS), a machine learning method to fit multidimensional functions y=f(x) for regression and classification problems without relying on linearity or additivity assumptions. KRLS finds the best fitting function by minimizing the squared loss of a Tikhonov regularization problem, using Gaussian kernels as radial basis functions. For further details see Hainmueller and Hazlett (2014).
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2025-04-22 |
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r-krige
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Estimates kriging models for geographical point-referenced data. Method is described in Monogan and Gill (2016) <doi:10.1017/psrm.2015.5>.
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2025-04-22 |
