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r-ltsa
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Methods of developing linear time series modelling. Methods are given for loglikelihood computation, forecasting and simulation.
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2025-04-22 |
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r-lsei
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It contains functions that solve least squares linear regression problems under linear equality/inequality constraints. Functions for solving quadratic programming problems are also available, which transform such problems into least squares ones first. It is developed based on the 'Fortran' program of Lawson and Hanson (1974, 1995), which is public domain and available at <http://www.netlib.org/lawson-hanson/>.
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2025-04-22 |
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r-lrcontrast
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Provides functions for calculating test statistics, simulating quantiles and simulating p-values of likelihood ratio contrast tests in regression models with a lack of identifiability.
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2025-04-22 |
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r-lpsolveapi
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The lpSolveAPI package provides an R interface to 'lp_solve', a Mixed Integer Linear Programming (MILP) solver with support for pure linear, (mixed) integer/binary, semi-continuous and special ordered sets (SOS) models.
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2025-04-22 |
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r-lpstimeseries
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Learned Pattern Similarity (LPS) for time series. Implements a novel approach to model the dependency structure in time series that generalizes the concept of autoregression to local auto-patterns. Generates a pattern-based representation of time series along with a similarity measure called Learned Pattern Similarity (LPS). Introduces a generalized autoregressive kernel.This package is based on the 'randomForest' package by Andy Liaw.
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2025-04-22 |
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r-lpridge
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Local Polynomial Regression with Ridging.
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2025-04-22 |
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r-lowrankqp
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Solves quadratic programming problems where the Hessian is represented as the product of two matrices. Thanks to Greg Hunt for helping getting this version back on CRAN. The methods in this package are described in: Ormerod, Wand and Koch (2008) "Penalised spline support vector classifiers: computational issues" <doi:10.1007/s00180-007-0102-8>.
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2025-04-22 |
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r-lorec
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Estimate covariance matrices that contain low rank and sparse components
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2025-04-22 |
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r-lowmemtkmeans
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Performs the trimmed k-means clustering algorithm with lower memory use. It also provides a number of utility functions such as BIC calculations.
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2025-04-22 |
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r-lokern
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Kernel regression smoothing with adaptive local or global plug-in bandwidth selection.
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2025-04-22 |
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r-logspline
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Contains routines for logspline density estimation. The function oldlogspline() uses the same algorithm as the logspline package version 1.0.x; i.e. the Kooperberg and Stone (1992) algorithm (with an improved interface). The recommended routine logspline() uses an algorithm from Stone et al (1997) <DOI:10.1214/aos/1031594728>.
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2025-04-22 |
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r-loglognorm
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Functions to sample from the double log normal distribution and calculate the density, distribution and quantile functions.
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2025-04-22 |
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r-logicreg
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Routines for fitting Logic Regression models. Logic Regression is described in Ruczinski, Kooperberg, and LeBlanc (2003) <DOI:10.1198/1061860032238>. Monte Carlo Logic Regression is described in and Kooperberg and Ruczinski (2005) <DOI:10.1002/gepi.20042>.
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2025-04-22 |
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r-logconcens
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Based on right or interval censored data, compute the maximum likelihood estimator of a (sub)probability density under the assumption that it is log-concave. For further information see Duembgen, Rufibach and Schuhmacher (2014) <doi:10.1214/14-EJS930>.
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2025-04-22 |
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r-loder
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Read and write access to PNG image files using the LodePNG library. The package has no external dependencies.
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2025-04-22 |
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r-log4r
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The log4r package is meant to provide a fast, lightweight, object-oriented approach to logging in R based on the widely-emulated 'log4j' system and etymology.
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2025-04-22 |
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r-loe
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Local Ordinal embedding (LOE) is one of graph embedding methods for unweighted graphs.
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2025-04-22 |
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r-locpol
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Computes local polynomial estimators for the regression and also density. It comprises several different utilities to handle kernel estimators.
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2025-04-22 |
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r-locfit
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Local regression, likelihood and density estimation methods as described in the 1999 book by Loader.
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2025-04-22 |
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r-localgauss
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Computational routines for estimating local Gaussian parameters. Local Gaussian parameters are useful for characterizing and testing for non-linear dependence within bivariate data. See e.g. Tjostheim and Hufthammer, Local Gaussian correlation: A new measure of dependence, Journal of Econometrics, 2013, Volume 172 (1), pages 33-48 <DOI:10.1016/j.jeconom.2012.08.001>.
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2025-04-22 |
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r-localcontrol
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Implements novel nonparametric approaches to address biases and confounding when comparing treatments or exposures in observational studies of outcomes. While designed and appropriate for use in studies involving medicine and the life sciences, the package can be used in other situations involving outcomes with multiple confounders. The package implements a family of methods for non-parametric bias correction when comparing treatments in observational studies, including survival analysis settings, where competing risks and/or censoring may be present. The approach extends to bias-corrected personalized predictions of treatment outcome differences, and analysis of heterogeneity of treatment effect-sizes across patient subgroups. For further details, please see: Lauve NR, Nelson SJ, Young SS, Obenchain RL, Lambert CG. LocalControl: An R Package for Comparative Safety and Effectiveness Research. Journal of Statistical Software. 2020. p. 1–32. Available from <doi:10.18637/jss.v096.i04>.
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2025-04-22 |
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r-lobstr
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A set of tools for inspecting and understanding R data structures inspired by str(). Includes ast() for visualizing abstract syntax trees, ref() for showing shared references, cst() for showing call stack trees, and obj_size() for computing object sizes.
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2025-04-22 |
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r-lmperm
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Linear model functions using permutation tests.
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2025-04-22 |
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r-lmsubsets
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Exact and approximation algorithms for variable-subset selection in ordinary linear regression models. Either compute all submodels with the lowest residual sum of squares, or determine the single-best submodel according to a pre-determined statistical criterion. Hofmann et al. (2020) <doi:10.18637/jss.v093.i03>.
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2025-04-22 |
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r-lmom
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Functions related to L-moments: computation of L-moments and trimmed L-moments of distributions and data samples; parameter estimation; L-moment ratio diagram; plot vs. quantiles of an extreme-value distribution.
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2025-04-22 |
