k3ylabs/cosoco-image-dataset huggingface dataset:
Package: r-cran-kernelheaping (2.3.0-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=Kernelheaping
Depends: r-base-core (>= 4.1.2-1ubuntu2), r-api-4.0, r-cran-mass, r-cran-ks, r-cran-sparr, r-cran-sp, r-cran-plyr, r-cran-dplyr, r-cran-fastmatch, r-cran-fitdistrplus, r-cran-gb2, r-cran-magrittr, r-cran-mvtnorm
Description:  GNU R kernel density estimation for heaped and rounded data In self-reported or anonymised data the user often encounters heaped data, i.e. data which are rounded (to a possibly different degree of coarseness). While this is mostly a minor problem in parametric density estimation the bias can be very large for non-parametric methods such as kernel density estimation. This package implements a partly Bayesian algorithm treating the true unknown values as additional parameters and estimates the rounding parameters to give a corrected kernel density estimate. It supports various standard bandwidth selection methods. Varying rounding probabilities (depending on the true value) and asymmetric rounding is estimable as well: Gross, M. and Rendtel, U. (2016) (<doi:10.1093/jssam/smw011>). Additionally, bivariate non- parametric density estimation for rounded data, Gross, M. et al. (2016) (<doi:10.1111/rssa.12179>), as well as data aggregated on areas is supported.
Package: r-cran-kernlab (0.9-29-1build2)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=kernlab
Depends: libblas3 | libblas.so.3, libc6 (>= 2.29), libgcc-s1 (>= 3.0), liblapack3 | liblapack.so.3, libstdc++6 (>= 4.9), r-base-core (>= 4.0.0.20200528-1), r-api-4.0
Description:  GNU R package for kernel-based machine learning lab The kernlab package provides kernel-based machine learning methods for classification, regression, clustering, novelty detection, quantile regression and dimensionality reduction.  Among other methods kernlab includes Support Vector Machines, Spectral Clustering, Kernel PCA, Gaussian Processes and a QP solver.
Package: r-cran-kernsmooth (2.23-20-1)
Section: universe/math
Homepage: https://cran.r-project.org/package=KernSmooth
Depends: r-base-core (>= 4.0.4-1build1), r-api-4.0, libblas3 | libblas.so.3, libc6 (>= 2.29), r-cran-mass
Description:  GNU R package for kernel smoothing and density estimation This package provides functions for kernel smoothing and density estimation corresponding to M.P. Wand and M.C. Jones, "Kernel Smoothing", 1995. . This package is part of the set of packages that are 'recommended' by R Core and shipped with upstream source releases of R itself. . URL: http://www.maths.unsw.edu.au/~wand
Package: r-cran-keyring (1.3.0-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=keyring
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-cran-assertthat, r-cran-askpass, r-cran-openssl, r-cran-r6, r-cran-sodium, r-cran-yaml, r-cran-filelock, r-cran-rappdirs
Description:  access the system credential store from GNU R Platform independent 'API' to access the operating system's credential store. Currently supports: 'Keychain' on 'macOS', Credential Store on 'Windows', the Secret Service 'API' on 'Linux', and a simple, platform independent store implemented with environment variables. Additional storage back-ends can be added easily.
Package: r-cran-km.ci (0.5-2-2build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=km.ci
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-survival
Description:  GNU R confidence intervals for the Kaplan-Meier estimator Computes various confidence intervals for the Kaplan-Meier estimator, namely: Petos CI, Rothman CI, CI's based on Greenwoods variance, Thomas and Grunkemeier CI and the simultaneous confidence bands by Nair and Hall and Wellner.
Package: r-cran-kmi (0.5.5-2build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=kmi
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-mitools, r-cran-survival
Description:  GNU R Kaplan-Meier Multiple Imputation This GNU R package provides Kaplan-Meier Multiple Imputation for the Analysis of Cumulative Incidence Functions in the Competing Risks Setting. It Performs a Kaplan-Meier multiple imputation to recover the missing potential censoring information from competing risks events, so that standard right-censored methods could be applied to the imputed data sets to perform analyses of the cumulative incidence functions (Allignol and Beyersmann, 2010 <doi:10.1093/biostatistics/kxq018>).
Package: r-cran-kmsurv (0.1-5-2build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=KMsurv
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0
Description:  data sets for GNU R from Klein and Moeschberger (1997), Survival Analysis Data sets and functions for Klein and Moeschberger (1997), "Survival Analysis, Techniques for Censored and Truncated Data", Springer.
Package: r-cran-knitr (1.37+dfsg-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=knitr
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-cran-evaluate (>= 0.10), r-cran-highr, r-cran-stringr (>= 0.6), r-cran-yaml (>= 2.1.19), r-cran-xfun (>= 0.27), libjs-mathjax, libjs-highlight.js, libjs-jquery, libjs-bootstrap, libjs-jquery-datatables, libjs-normalize.css
Description:  GNU R package for dynamic report generation using Literate Programming The R package knitr is a general-purpose literate programming engine, with lightweight API's designed to give users full control of the output without heavy coding work. It combines many features into one package with slight tweaks motivated from everyday use of Sweave.
Package: r-cran-knn.covertree (1.0-2)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=knn.covertree
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0, r-cran-rcpp (>= 1.0.2), r-cran-rcppeigen (>= 0.3.3.5.0), r-cran-matrix, libc6 (>= 2.29), libgcc-s1 (>= 3.0), libstdc++6 (>= 9)
Description:  GNU R accurate kNN implementation with multiple distance measures Similarly to the 'FNN' package, this package allows calculation of the k nearest neighbors (kNN) of a data matrix. The implementation is based on cover trees introduced by Alina Beygelzimer, Sham Kakade, and John Langford (2006) <doi:10.1145/1143844.1143857>.
Package: r-cran-kohonen (3.0.10+dfsg-2)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=kohonen
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-rcpp (>= 0.12.12), libc6 (>= 2.29), libgcc-s1 (>= 3.3.1), libgomp1 (>= 4.9), libstdc++6 (>= 9)
Description:  GNU R supervised and unsupervised self-organising maps Functions to train self-organising maps (SOMs). Also interrogation of the maps and prediction using trained maps are supported. The name of the package refers to Teuvo Kohonen, the inventor of the SOM.
Package: r-cran-ks (1.13.3-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=ks
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-cran-fnn (>= 1.1), r-cran-kernlab, r-cran-kernsmooth (>= 2.22), r-cran-matrix, r-cran-mclust, r-cran-mgcv, r-cran-multicool, r-cran-mvtnorm (>= 1.0-0), r-cran-plot3d, r-cran-pracma, libc6 (>= 2.2.5)
Description:  GNU R kernel smoothing Kernel smoothers for univariate and multivariate data, including densities, density derivatives, cumulative distributions, clustering, classification, density ridges, significant modal regions, and two- sample hypothesis tests. Chacon & Duong (2018) <doi:10.1201/9780429485572>.
Package: r-cran-ksamples (1.2-9-2)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=kSamples
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0, r-cran-suppdists, libc6 (>= 2.4)
Description:  GNU R K-Sample Rank Tests and their Combinations Compares k samples using the Anderson-Darling test, Kruskal-Wallis type tests with different rank score criteria, Steel's multiple comparison test, and the Jonckheere-Terpstra (JT) test. It computes asymptotic, simulated or (limited) exact P-values, all valid under randomization, with or without ties, or conditionally under random sampling from populations, given the observed tie pattern. Except for Steel's test and the JT test it also combines these tests across several blocks of samples. Also analyzed are 2 x t contingency tables and their blocked combinations using the Kruskal-Wallis criterion. Steel's test is inverted to provide simultaneous confidence bounds for shift parameters. A plotting function compares tail probabilities obtained under asymptotic approximation with those obtained via simulation or exact calculations.
Package: r-cran-kutils (1.70+dfsg-2build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=kutils
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-foreign, r-cran-xtable, r-cran-plyr, r-cran-openxlsx, r-cran-runit
Description:  GNU R project management tools Tools for data importation, recoding, and inspection that are used at the University of Kansas Center for Research Methods and Data Analysis. There are functions to create new project folders, R code templates, create uniquely named output directories, and to quickly obtain a visual summary for each variable in a data frame.  The main feature here is the systematic implementation of the "variable key" framework for data importation and recoding.
Package: r-cran-labdsv (2.0-1-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=labdsv
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-mgcv, r-cran-cluster, r-cran-rtsne, r-cran-mass, libc6 (>= 2.14)
Description:  Ordination and Multivariate Analysis for Ecology A variety of ordination and community analyses useful in analysis of data sets in community ecology. Includes many of the common ordination methods, with graphical routines to facilitate their interpretation, as well as several novel analyses.
Package: r-cran-labeling (0.4.2-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=labeling
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0
Description:  GNU R Axis Labeling optimization This system extends Wilkinsons optimization-based labeling approach to create a more robust, full-featured axis labeler.
Package: r-cran-laeken (0.5.2-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=laeken
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-boot, r-cran-mass
Description:  GNU R estimation of indicators on social exclusion and poverty Estimation of indicators on social exclusion and poverty, as well as Pareto tail modeling for empirical income distributions.
Package: r-cran-lambda.r (1.2.4-2build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=lambda.r
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-formatr
Description:  GNU R modeling data with functional programming This GNU R package provides 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.
Package: r-cran-lamw (2.1.1-1build2)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=lamW
Depends: r-base-core (>= 4.1.2-1ubuntu2), r-api-4.0, r-cran-rcpp, r-cran-rcppparallel (>= 4.3.20), libc6 (>= 2.34), libgcc-s1 (>= 3.0), libstdc++6 (>= 6)
Description:  GNU R Lambert-W function Implements both real-valued branches of the Lambert-W function (Corless et al, 1996) <doi:10.1007/BF02124750> without the need for installing the entire GSL.
Package: r-cran-lasso2 (1.2-22-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=lasso2
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, libc6 (>= 2.14)
Description:  GNU R L1 constrained estimation aka `lasso' Routines and documentation for solving regression problems while imposing an L1 constraint on the estimates, based on the algorithm of Osborne et al. (1998).
Package: r-cran-later (1.3.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=later
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-rcpp (>= 0.12.9), r-cran-rlang, libc6 (>= 2.34), libgcc-s1 (>= 3.3.1), libstdc++6 (>= 11)
Description:  GNU R utilities for delaying function execution This GNU R packages enables the execution of arbitrary R or C functions some time after the current time, after the R execution stack has emptied.
Package: r-cran-lattice (0.20-45-1)
Section: universe/math
Homepage: https://cran.r-project.org/package=lattice
Depends: libc6 (>= 2.4), r-base-core (>= 4.1.1-2), r-api-4.0
Description:  GNU R package for 'Trellis' graphics This package provides functions for 'Trellis' graphics -- a framework for data visualization developed at the Bell Labs by Rick Becker, Bill Cleveland et al, extending ideas presented in Bill Cleveland's 1993 book 'Visualizing Data'. . This package is part of the set of packages that are 'recommended' by R Core and shipped with upstream source releases of R itself.
Package: r-cran-latticeextra (0.6-29-3build1)
Section: universe/math
Homepage: https://cran.r-project.org/package=latticeExtra
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-lattice, r-cran-png, r-cran-jpeg, r-cran-rcolorbrewer
Description:  GNU R package of additional graphical displays based on lattice This CRAN package provides generic functions and standard methods for trellis-based displays.
Package: r-cran-lava (1.6.10+dfsg-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=lava
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-future.apply, r-cran-progressr, r-cran-numderiv, r-cran-survival, r-cran-squarem
Description:  GNU R latent variable models A general implementation of Structural Equation Models with latent variables (MLE, 2SLS, and composite likelihood estimators) with both continuous, censored, and ordinal outcomes (Holst and Budtz-Joergensen (2013) <doi:10.1007/s00180-012-0344-y>). The package also provides methods for graph exploration (d-separation, back-door criterion), simulation of general non-linear latent variable models, and estimation of influence functions for a broad range of statistical models.
Package: r-cran-lavaan (0.6.10-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=lavaan
Depends: r-base-core (>= 4.1.2-1ubuntu2), r-api-4.0, r-cran-mass, r-cran-mnormt, r-cran-pbivnorm, r-cran-numderiv
Description:  GNU R package for latent variable analysis -- lavaan This package supplies latent variable analysis for R.  One can use lavaan to estimate a large variety of multivariate statistical models, including path analysis, confirmatory factor analysis, structural equation modeling and growth curve models.
Package: r-cran-lavasearch2 (1.5.6+dfsg-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=lavaSearch2
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0, r-cran-ggplot2, r-cran-lava (>= 1.6.4), r-cran-doparallel, r-cran-mass, r-cran-matrix, r-cran-multcomp, r-cran-mvtnorm, r-cran-nlme, r-cran-rcpp, r-cran-reshape2, r-cran-sandwich, r-cran-rcpparmadillo, libblas3 | libblas.so.3, libc6 (>= 2.29), libgcc-s1 (>= 3.0), liblapack3 | liblapack.so.3, libstdc++6 (>= 9)
Description:  GNU R tools for model specification in the latent variable framework Tools for model specification in the latent variable framework (add-on to the 'lava' package). The package contains three main functionalities: Wald tests/F-tests with improved control of the type 1 error in small samples, adjustment for multiple comparisons when searching for local dependencies, and adjustment for multiple comparisons when doing inference for multiple latent variable models.
Package: r-cran-lazyeval (0.2.2-1build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=lazyeval
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, libc6 (>= 2.2.5)
Description:  GNU R lazy (non-standard) evaluation This GNU R package provides a disciplined approach to non-standard evaluation. . Lazyeval provides principled tools to perform non-standard evaluation (NSE) in R.  It is helpful for programmin with packages like dplyr and ggplot2, or to use a principled way of working with delayed expressions in own packages. As the name suggests, non-standard evaluation breaks away from the standard evaluation (SE) rules in order to do something special.
Package: r-cran-lbfgsb3c (2020-3.2-2)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=lbfgsb3c
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0, r-cran-rcpp (>= 0.12.3), r-cran-numderiv, r-cran-rcpparmadillo, libc6 (>= 2.14), libgcc-s1 (>= 3.0), libgfortran5 (>= 8), libstdc++6 (>= 5.2)
Description:  GNU R limited memory BFGS minimizer with bounds on Parameters Interfacing to Nocedal et al. L-BFGS-B.3.0 (See <http://users.iems.northwestern.edu/~nocedal/lbfgsb.html>) limited memory BFGS minimizer with bounds on parameters. This is a fork of 'lbfgsb3'. This registers a 'R' compatible 'C' interface to L-BFGS-B.3.0 that uses the same function types and optimization as the optim() function (see writing 'R' extensions and source for details). This package also adds more stopping criteria as well as allowing the adjustment of more tolerances.
Package: r-cran-leaps (3.1-1build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=leaps
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, libc6 (>= 2.4)
Description:  Regression Subset Selection Regression subset selection, including exhaustive search.
Package: r-cran-learnbayes (2.15.1-4build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=LearnBayes
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0
Description:  GNU R functions for learning bayesian inference LearnBayes contains a collection of functions helpful in learning the basic tenets of Bayesian statistical inference. It contains functions for summarizing basic one and two parameter posterior distributions and predictive distributions. It contains MCMC algorithms for summarizing posterior distributions defined by the user. It also contains functions for regression models, hierarchical models, Bayesian tests, and illustrations of Gibbs sampling.
Package: r-cran-leiden (0.3.9+dfsg-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=leiden
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-reticulate, r-cran-matrix, r-cran-igraph
Description:  GNU R implementation of Leiden clustering algorithm Implements the 'Python leidenalg' module to be called in R. Enables clustering using the leiden algorithm for partition a graph into communities. See the 'Python' repository for more details: <https://github.com/vtraag/leidenalg> Traag et al (2018) From Louvain to Leiden: guaranteeing well-connected communities. <arXiv:1810.08473>.
Package: r-cran-lexrankr (0.5.2-2)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=lexRankr
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0, r-cran-snowballc, r-cran-igraph, r-cran-rcpp, libc6 (>= 2.14), libgcc-s1 (>= 3.0), libstdc++6 (>= 5.2)
Description:  extractive summarization of text with the LexRank algorithm An R implementation of the LexRank algorithm implementing stochastic graph-based method for computing relative importance of textual units for Natural Language Processing. The technique on the problem of Text Summarization (TS) is tested. Extractive TS relies on the concept of sentence salience to identify the most important sentences in a document or set of documents. Salience is typically defined in terms of the presence of particular important words or in terms of similarity to a centroid pseudo-sentence.
Package: r-cran-lhs (1.1.3-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=lhs
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-rcpp, libc6 (>= 2.29), libgcc-s1 (>= 3.3.1), libstdc++6 (>= 11)
Description:  GNU R Latin Hypercube Samples This package provides a number of methods for creating and augmenting Latin Hypercube Samples. . Latin hypercube sampling (LHS) is a statistical method for generating a sample of plausible collections of parameter values from a multidimensional distribution. The sampling method is often used to construct computer experiments.
Package: r-cran-libcoin (1.0-9-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=libcoin
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-mvtnorm, libc6 (>= 2.29), liblapack3 | liblapack.so.3
Description:  GNU R linear test statistics for permutation inference Basic infrastructure for linear test statistics and permutation inference in the framework of Strasser and Weber (1999) <http://epub.wu.ac.at/102/>. This package must not be used by end-users. CRAN package 'coin' implements all user interfaces and is ready to be used by anyone.
Package: r-cran-lifecycle (1.0.1-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=lifecycle
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-glue, r-cran-rlang (>= 0.4.10)
Description:  manage the life cycle of your GNU R package functions Manage the life cycle of your exported functions with shared conventions, documentation badges, and non-invasive deprecation warnings. The 'lifecycle' package defines four development stages (experimental, maturing, stable, and questioning) and three deprecation stages (soft-deprecated, deprecated, and defunct). It makes it easy to insert badges corresponding to these stages in your documentation. Usage of deprecated functions are signalled with increasing levels of non-invasive verbosity.
Package: r-cran-linprog (0.9-2-2)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=linprog
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0, r-cran-lpsolve
Description:  GNU R linear programming / optimization This package can be used to solve Linear Programming / Linear Optimization problems by using the simplex algorithm.
Package: r-cran-lisreltor (0.1.4-3build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=lisrelToR
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0
Description:  import output from LISREL into GNU R This is an unofficial package aimed at automating the import of LISREL output in R.  This package or its maintainer is not in any way affiliated with the creators of LISREL and SSI, Inc.
Package: r-cran-listenv (0.8.0+dfsg-1build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=listenv
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0
Description:  R package: Environments Behaving (Almost) as Lists List environments are environments that have list-like properties. For instance, the elements of a list environment are ordered and can be accessed and iterated over using index subsetting, e.g. 'x <- listenv(a=1, b=2); for (i in seq_along(x)) x[[i]] <- x[[i]]^2; y <- as.list(x)'.
Package: r-cran-littler (0.3.15-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=littler
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, libc6 (>= 2.34)
Description:  GNU R scripting and command-line front-end The 'r' (aka 'littler') program provides a lightweight binary wrapper around the GNU R language and environment for statistical computing and graphics. . While R can be used in batch mode, the r binary adds full support for both 'shebang'-style scripting (i.e. using a  hashmark-exclamation-path expression as the first line in scripts) as well as command-line use in standard Unix pipelines. In other words, r provides the R language without the environment.
Package: r-cran-lme4 (1.1-28-1)
Section: universe/math
Homepage: https://cran.r-project.org/package=lme4
Depends: libc6 (>= 2.29), libgcc-s1 (>= 3.0), libstdc++6 (>= 5.2), r-base-core (>= 4.1.2-1ubuntu2), r-api-4.0, r-cran-matrix (>= 1.2-1), r-cran-mass, r-cran-lattice, r-cran-boot, r-cran-nlme (>= 3.1-123), r-cran-minqa (>= 1.2.2-2), r-cran-nloptr (>= 1.0.4), r-cran-rcpp (>= 0.10.5), r-cran-rcppeigen (>= 0.3.2.0.2-2), r-cran-statmod
Description:  GNU R package for linear mixed effects model fitting This CRAN package provides S4 classes and methods for fitting and examining linear mixed effects models (also called multilevel models, panel data models, and several other names) and generalized linear mixed effects models.