k3ylabs/cosoco-image-dataset huggingface dataset:
Package: r-cran-aer (1.2-9-2build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=AER
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-car (>= 2.0-19), r-cran-lmtest, r-cran-sandwich (>= 2.4-0), r-cran-survival (>= 2.37-5), r-cran-zoo, r-cran-formula (>= 0.2-0)
Description:  Applied Econometrics with R This GNU R package provides functions, data sets, examples, demos, and vignettes for the book Christian Kleiber and Achim Zeileis (2008), Applied Econometrics with R, Springer-Verlag, New York. ISBN 978-0-387-77316-2. (See the vignette "AER" for a package overview.)
Package: r-cran-afex (1.0-1-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=afex
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-lme4 (>= 1.1-8), r-cran-pbkrtest (>= 0.4-1), r-cran-lmertest (>= 3.0-0), r-cran-car, r-cran-reshape2
Description:  GNU R package for analyzing factorial experiments using ANOVA or mixed models The r-cran-afex package is a GNU R package providing convenience functions for analyzing factorial experiments using ANOVA or mixed models. aov_ez(), aov_car(), and aov_4() allow specification of between, within (i.e., repeated- measures), or mixed between-within (i.e., split- plot) ANOVAs for data in long format (i.e., one observation per row), potentially aggregating multiple observations per individual and cell of the design. mixed() fits mixed models using lme4::lmer() and computes p-values for all fixed effects using either Kenward-Roger approximation for degrees of freedom (LMM only), parametric bootstrap (LMMs and GLMMs), or likelihood ratio tests (LMMs and GLMMs). afex uses type 3 sums of squares as default (imitating commercial statistical software).
Package: r-cran-airr (1.3.0-2)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=airr
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0, r-cran-readr, r-cran-stringi, r-cran-yaml
Description:  GNU R AIRR data representation reference library Schema definitions and read, write and validation tools for data formatted in accordance with the AIRR Data Representation schemas defined by the AIRR Community <http://docs.airr-community.org>.
Package: r-cran-alakazam (1.2.0-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=alakazam
Depends: r-base-core (>= 4.1.2-1), r-api-4.0, r-cran-ggplot2 (>= 3.3.4), r-cran-airr (>= 1.3), r-cran-ape, r-cran-dplyr (>= 1.0), r-cran-igraph (>= 1.0), r-cran-matrix, r-cran-progress, r-cran-rcpp (>= 0.12.12), r-cran-readr, r-cran-rlang, r-cran-scales, r-cran-seqinr, r-cran-stringi, r-cran-tibble, r-cran-tidyr (>= 1.0), r-bioc-biostrings (>= 2.56.0), r-bioc-genomicalignments (>= 1.24.0), r-bioc-iranges (>= 2.22.2), libc6 (>= 2.14), libgcc-s1 (>= 3.3.1), libstdc++6 (>= 9)
Description:  Immunoglobulin Clonal Lineage and Diversity Analysis Alakazam is part of the Immcantation analysis framework for Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) and provides a set of tools to investigate lymphocyte receptor clonal lineages, diversity, gene usage, and other repertoire level properties, with a focus on high-throughput immunoglobulin (Ig) sequencing. . Alakazam serves five main purposes:  * Providing core functionality for other R packages in the Immcantation    framework. This includes common tasks such as file I/O, basic DNA    sequence manipulation, and interacting with V(D)J segment and gene    annotations.  * Providing an R interface for interacting with the output of the    pRESTO and Change-O tool suites.  * Performing lineage reconstruction on clonal populations of Ig    sequences and analyzing the topology of the resultant lineage trees.  * Performing clonal abundance and diversity analysis on lymphocyte    repertoires.  * Performing physicochemical property analyses of lymphocyte receptor    sequences.
Package: r-cran-amap (0.8-18-2build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=amap
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, libc6 (>= 2.29), libgcc-s1 (>= 3.0), libstdc++6 (>= 4.1.1)
Description:  Another Multidimensional Analysis Package Tools for Clustering and Principal Component Analysis (With robust methods, and parallelized functions).
Package: r-cran-amelia (1.8.0-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=Amelia
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-rcpp (>= 0.11), r-cran-foreign, r-cran-rcpparmadillo, libblas3 | libblas.so.3, libc6 (>= 2.14), libgcc-s1 (>= 3.3.1), liblapack3 | liblapack.so.3, libstdc++6 (>= 9)
Description:  GNU R package supporting multiple imputation of missing data Amelia II "multiply imputes" missing data in a single cross-section (such as a survey), from a time series (like variables collected for each year in a country), or from a time-series-cross-sectional data set (such as collected by years for each of several countries). Amelia II implements a bootstrapping-based algorithm that gives essentially the same answers as the standard IP or EMis approaches, is usually considerably faster than existing approaches and can handle many more variables. . The program also generalizes existing approaches by allowing for trends in time series across observations within a cross-sectional unit, as well as priors that allow experts to incorporate beliefs they have about the values of missing cells in their data. Amelia II also includes useful diagnostics of the fit of multiple imputation models. The program works from the R command line or via a graphical user interface that does not require users to know R.
Package: r-cran-amore (0.2-16-2)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=AMORE
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, libc6 (>= 2.4), libgomp1 (>= 4.9)
Description:  GNU R: A MORE flexible neural network package This package was born to release the TAO robust neural network algorithm to the R users. It has grown and can be of interest for the users wanting to implement their own training algorithms as well as for those others whose needs lye only in the "user space".
Package: r-cran-animation (2.7+dfsg-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=animation
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-magick, libjs-jquery, libjs-highlight.js
Description:  GNU R gallery of animations and utilities to create animations Provides functions for animations in statistics, covering topics in probability theory, mathematical statistics, multivariate statistics, non-parametric statistics, sampling survey, linear models, time series, computational statistics, data mining and machine learning. These functions may be helpful in teaching statistics and data analysis. Also provided in this package are a series of functions to save animations to various formats, e.g. Flash, 'GIF', HTML pages, 'PDF' and videos. 'PDF' animations can be inserted into 'Sweave' / 'knitr' easily.
Package: r-cran-apcluster (1.4.9-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=apcluster
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-cran-rcpp (>= 0.11.1), r-cran-matrix, libc6 (>= 2.14), libgcc-s1 (>= 3.0), libstdc++6 (>= 11)
Description:  Affinity Propagation Clustering Implements Affinity Propagation clustering introduced by Frey and Dueck (2007) <DOI:10.1126/science.1136800>. The algorithms are largely analogous to the 'Matlab' code published by Frey and Dueck. The package further provides leveraged affinity propagation and an algorithm for exemplar-based agglomerative clustering that can also be used to join clusters obtained from affinity propagation. Various plotting functions are available for analyzing clustering results.
Package: r-cran-ape (5.6-1-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=ape
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-cran-nlme, r-cran-lattice, r-cran-rcpp (>= 0.12.0), libc6 (>= 2.29), libgcc-s1 (>= 3.0), liblapack3 | liblapack.so.3, libstdc++6 (>= 11)
Description:  GNU R package for Analyses of Phylogenetics and Evolution This package provides functions for reading, writing, plotting, and manipulating phylogenetic trees, analyses of comparative data in a phylogenetic framework, ancestral character analyses, analyses of diversification and macroevolution, computing distances from DNA sequences, reading and writing nucleotide sequences as well as importing from BioConductor, and several tools such as Mantel's test, generalized skyline plots, graphical exploration of phylogenetic data (alex, trex, kronoviz), estimation of absolute evolutionary rates and clock-like trees using mean path lengths and penalized likelihood, dating trees with non-contemporaneous sequences, translating DNA into AA sequences, and assessing sequence alignments. Phylogeny estimation can be done with the NJ, BIONJ, ME, MVR, SDM, and triangle methods, and several methods handling incomplete distance matrices (NJ*, BIONJ*, MVR*, and the corresponding triangle method). Some functions call external applications (PhyML, Clustal, T-Coffee, Muscle) whose results are returned into R.
Package: r-cran-aplpack (1.3.5-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=aplpack
Depends: r-base-core (>= 4.1.1-2), r-api-4.0
Description:  Another Plot PACKage: stem.leaf, bagplot, faces, spin3R and others This GNU R package provided a set of functions for drawing some special plots:  * stem.leaf plots a stem and leaf plot,  * stem.leaf.backback plots back-to-back versions of stem and leafs,  * bagplot plots a bagplot,  * skyline.hist plots several histgramm in one plot of a one dimensional data    set,  * plotsummary plots a graphical summary of a data set with one or more    variables,  * plothulls plots sequentially hulls of a bivariate data set,  * faces plots chernoff faces,  * spin3R for an inspection of a 3-dim point cloud,  * slider functions for interactive graphics.
Package: r-cran-argparse (2.1.3-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=argparse
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-cran-r6, r-cran-findpython, r-cran-jsonlite, python3
Description:  GNU R command line parser for optional and positional arguments This GNU R package provides a command line parser to be used with Rscript to write "#!" shebang scripts that gracefully accept positional and optional arguments and automatically generate usage.
Package: r-cran-argparser (0.7.1-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=argparser
Depends: r-base-core (>= 4.1.1-2), r-api-4.0
Description:  GNU R command-line argument parser Cross-platform command-line argument parser written purely in R with no external dependencies. It is useful with the Rscript front-end and facilitates turning an R script into an executable script.
Package: r-cran-arm (1.12-2-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=arm
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-mass, r-cran-matrix (>= 1.0), r-cran-lme4 (>= 1.0), r-cran-abind, r-cran-coda, r-cran-nlme
Description:  Data Analysis Using Regression and Multilevel/Hierarchical Models R functions for processing 'lm', 'glm', 'svy.glm', 'merMod' and 'polr' outputs.
Package: r-cran-arsenal (3.6.3-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=arsenal
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-knitr (>= 1.29)
Description:  arsenal of GNU R functions for large-scale statistical summaries An Arsenal of 'R' functions for large-scale statistical summaries, which are streamlined to work within the latest reporting tools in 'R' and 'RStudio' and which use formulas and versatile summary statistics for summary tables and models. The primary functions include tableby(), a Table-1-like summary of multiple variable types 'by' the levels of one or more categorical variables; paired(), a Table-1-like summary of multiple variable types paired across two time points; modelsum(), which performs simple model fits on one or more endpoints for many variables (univariate or adjusted for covariates); freqlist(), a powerful frequency table across many categorical variables; comparedf(), a function for comparing data.frames; and write2(), a function to output tables to a document.
Package: r-cran-askpass (1.1-2)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=askpass
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0, r-cran-sys (>= 2.1), libc6 (>= 2.2.5)
Description:  safe password entry for GNU R, Git, and SSH Cross-platform utilities for prompting the user for credentials or a passphrase, for example to authenticate with a server or read a protected key. Includes native programs for MacOS and Windows, hence no 'tcltk' is required. Password entry can be invoked in two different ways: directly from R via the askpass() function, or indirectly as password-entry back-end for 'ssh-agent' or 'git-credential' via the SSH_ASKPASS and GIT_ASKPASS environment variables. Thereby the user can be prompted for credentials or a passphrase if needed when R calls out to git or ssh.
Package: r-cran-assertive.base (0.0-9-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=assertive.base
Depends: r-base-core (>= 4.1.1-2), r-api-4.0
Description:  GNU R lightweight core of the 'assertive' package A minimal set of predicates and assertions used by the assertive package.  This is mainly for use by other package developers who want to include run-time testing features in their own packages.  End-users will usually want to use assertive directly.
Package: r-cran-assertive.sets (0.0-3-3build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=assertive.sets
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-assertive.base (>= 0.0-7)
Description:  GNU R assertions to check properties of sets A set of predicates and assertions for checking the properties of sets.  This is mainly for use by other package developers who want to include run-time testing features in their own packages.  End-users will usually want to use assertive directly.
Package: r-cran-assertthat (0.2.1-2build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=yassertthat
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0
Description:  GNU R easy pre and post assertions Assertthat is an extension to stopifnot() that makes it easy to declare the pre and post conditions that you code should satisfy, while also producing friendly error messages so that your users know what they've done wrong.
Package: r-cran-av (0.7.0+dfsg-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=av
Depends: r-base-core (>= 4.1.2-1ubuntu2), r-api-4.0, libavfilter7 (>= 7:4.4), libc6 (>= 2.29)
Description:  working with Audio and Video in GNU R Bindings to 'FFmpeg' <http://www.ffmpeg.org/> AV library for working with audio and video in R. Generates high quality video from images or R graphics with custom audio. Also offers high performance tools for reading raw audio, creating 'spectrograms', and converting between countless audio / video formats. This package interfaces directly to the C API and does not require any command line utilities.
Package: r-cran-aweek (1.0.2-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=aweek
Depends: r-base-core (>= 4.0.3-1), r-api-4.0
Description:  GNU R convert dates to arbitrary week definitions Which day a week starts depends heavily on the either the local or professional context. This package is designed to be a lightweight solution to easily switching between week-based date definitions.
Package: r-cran-backports (1.4.1-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=backports
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0
Description:  reimplementation of functions introduced since R-3.0.0 Implementations of functions which have been introduced in R since version 3.0.0. The backports are conditionally exported which results in R resolving the function names to the version shipped with R (if available) and uses the implemented backports as fallback. This way package developers can make use of the new functions without worrying about the minimum required R version.
Package: r-cran-base64enc (0.1-3-3)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=base64enc
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0, libc6 (>= 2.4)
Description:  GNU R package that provides tools for base64 encoding This package provides tools for handling base64 encoding. It is more flexible than the orphaned base64 package.
Package: r-cran-base64url (1.4-2build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=base64url
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-backports (>= 1.1.0), libc6 (>= 2.2.5)
Description:  GNU R fast and URL-safe Base64 encoder and decoder In contrast to RFC3548, the 62nd character ("+") is replaced with "-", the 63rd character ("/") is replaced with "_". Furthermore, the encoder does not fill the string with trailing "=". The resulting encoded strings comply to the regular expression pattern "[A-Za-z0-9_-]" and thus are safe to use in URLs or for file names. The package also comes with a simple base32 encoder/decoder suited for case insensitive file systems.
Package: r-cran-batchjobs (1.8-2build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=BatchJobs
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-bbmisc (>= 1.9), r-cran-backports (>= 1.1.1), r-cran-brew, r-cran-checkmate (>= 1.8.0), r-cran-data.table (>= 1.9.6), r-cran-dbi, r-cran-digest, r-cran-rsqlite (>= 1.0.9011), r-cran-sendmailr, r-cran-stringi (>= 0.4-1)
Description:  GNU R batch computing This GNU R package Provides Map, Reduce and Filter variants to generate jobs on batch computing systems like PBS/Torque, LSF, SLURM and Sun Grid Engine.  Multicore and SSH systems are also supported. For further details see the project web page.
Package: r-cran-batchtools (0.9.15+dfsg-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=batchtools
Depends: r-base-core (>= 4.0.3-1), r-api-4.0, r-cran-backports (>= 1.1.2), r-cran-base64url (>= 1.1), r-cran-brew, r-cran-checkmate (>= 1.8.5), r-cran-data.table (>= 1.11.2), r-cran-digest (>= 0.6.9), r-cran-fs (>= 1.2.0), r-cran-progress (>= 1.1.1), r-cran-r6, r-cran-rappdirs, r-cran-stringi, r-cran-withr (>= 2.0.0), libc6 (>= 2.2.5)
Description:  GNU R tools for computation on batch systems As a successor of the packages 'BatchJobs' and 'BatchExperiments', this package provides a parallel implementation of the Map function for high performance computing systems managed by schedulers IBM Spectrum LSF OpenLava, Univa Grid Engine/Oracle Grid Engine, Slurm, TORQUE/PBS, or Docker Swarm. . A multicore and socket mode allow the parallelization on a local machines, and multiple machines can be hooked up via SSH to create a makeshift cluster. Moreover, the package provides an abstraction mechanism to define large-scale computer experiments in a well-organized and reproducible way.
Package: r-cran-bayesfactor (0.9.12-4.3+dfsg-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=BayesFactor
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-cran-coda, r-cran-matrix (>= 1.1-1), r-cran-pbapply, r-cran-mvtnorm, r-cran-stringr, r-cran-gtools, r-cran-matrixmodels, r-cran-rcpp (>= 0.11.2), r-cran-hypergeo, r-cran-rcppeigen (>= 0.3.2.2.0), libc6 (>= 2.29), libgcc-s1 (>= 3.0), libstdc++6 (>= 5.2)
Description:  GNU R Bayes factors for t-tests, ANOVAs and contingency tables r-cran-bayesfactor is a GNU R package providing a suite of functions for computing various Bayes factors for simple designs, including contingency tables, one- and two-sample designs, one- way designs, general ANOVA designs, and linear regression.
Package: r-cran-bayesfm (0.1.5-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=BayesFM
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-cran-checkmate (>= 1.8.0), r-cran-coda, r-cran-ggplot2 (>= 2.1.0), r-cran-gridextra, r-cran-plyr (>= 1.8.0), libc6 (>= 2.29), libgfortran5 (>= 10), liblapack3 | liblapack.so.3
Description:  GNU R Bayesian inference for factor modeling Collection of procedures to perform Bayesian analysis on a variety of factor models. Currently, it includes: Bayesian Exploratory Factor Analysis (befa), an approach to dedicated factor analysis with stochastic search on the structure of the factor loading matrix. The number of latent factors, as well as the allocation of the manifest variables to the factors, are not fixed a priori but determined during MCMC sampling. More approaches will be included in future releases of this package.
Package: r-cran-bayesm (3.1-4+dfsg-1build2)
Section: universe/math
Homepage: https://cran.r-project.org/package=bayesm
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-rcpp (>= 0.12.0), r-cran-rcpparmadillo, libblas3 | libblas.so.3, libc6 (>= 2.29), libgcc-s1 (>= 3.0), liblapack3 | liblapack.so.3, libstdc++6 (>= 9)
Description:  GNU R package for Bayesian inference The bayesm package covers many important models used in marketing and micro-econometrics applications. The package includes: .  * Bayes Regression (univariate or multivariate dep var)  * Multinomial Logit (MNL) and Multinomial Probit (MNP)  * Multivariate Probit,  * Multivariate Mixtures of Normals  * Hierarchical Linear Models with normal prior and covariates  * Hierarchical Multinomial Logits with mixture of normals prior and    covariates  * Bayesian analysis of choice-based conjoint data  * Bayesian treatment of linear instrumental variables models  * Analyis of Multivariate Ordinal survey data with scale usage heterogeneity    (as in Rossi et al, JASA (01)). . For further reference, consult the authors' book, _Bayesian Statistics and Marketing_ by Allenby, McCulloch and Rossi.
Package: r-cran-bayesplot (1.8.1-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=bayesplot
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-dplyr (>= 0.8.0), r-cran-ggplot2 (>= 3.0.0), r-cran-ggridges, r-cran-glue, r-cran-reshape2, r-cran-rlang (>= 0.3.0), r-cran-tibble, r-cran-tidyselect
Description:  GNU R plotting for bayesian models Plotting functions for posterior analysis, model checking, and MCMC diagnostics. The package is designed not only to provide convenient functionality for users, but also a common set of functions that can be easily used by developers working on a variety of R packages for Bayesian modeling, particularly (but not exclusively) packages interfacing with 'Stan'.
Package: r-cran-bayestestr (0.11.5-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=bayestestR
Depends: r-base-core (>= 4.1.2-1), r-api-4.0, r-cran-insight (>= 0.14.1), r-cran-datawizard (>= 0.2.0)
Description:  GNU R understand and describe Bayesian models and posterior distributions Provides utilities to describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion (Highest Density Interval - HDI; Kruschke, 2015 <doi:10.1016/C2012-0-00477-2>) and indices used for null-hypothesis testing (such as ROPE percentage, pd and Bayes factors).
Package: r-cran-bbmisc (1.11-4)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=BBmisc
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0, r-cran-checkmate (>= 1.8.0), libc6 (>= 2.4)
Description:  GNU R Miscellaneous helper functions for B. Bischl Miscellaneous helper functions for and from B. Bischl and some other guys at TU Dortmund, mainly for package development.
Package: r-cran-bbmle (1.0.24-3ubuntu1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=bbmle
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-cran-numderiv, r-cran-lattice, r-cran-mass, r-cran-bdsmatrix, r-cran-matrix, r-cran-mvtnorm
Description:  GNU R tools for general maximum likelihood estimation This GNU R package provides methods and functions for fitting maximum likelihood models in R. This package modifies and extends the 'mle' classes in the 'stats4' package.