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Last data update: 2014.03.03

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Results 11 - 20 of 11200 found.
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mcll : Monte Carlo Local Likelihood Estimation

Package: mcll
Type: Package
Title: Monte Carlo Local Likelihood Estimation
Version: 1.2
Date: 2014-3-1
Author: Minjeong Jeon, Cari Kaufman, and Sophia Rabe-Hesketh
Maintainer: Minjeong Jeon<jeon.117@osu.edu>
Depends: R (>= 2.13.0), statmod, locfit
Description: Maximum likelihood estimation using a Monte Carlo local likelihood (MCLL) method
License: GPL (>= 2)
LazyLoad: yes
Packaged: 2014-03-01 18:56:19 UTC; jeon
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2014-03-01 20:25:56

● Data Source: CranContrib
● 0 images, 4 functions, 2 datasets
● Reverse Depends: 0

mclogit : Mixed Conditional Logit

Package: mclogit
Type: Package
Title: Mixed Conditional Logit
Version: 0.3-1
Date: 2014-10-13
Author: Martin Elff
Maintainer: Martin Elff <elff@gmx.com>
Description: This packages provides a function to estimate parameters for
the conditional logit model (also with multinomial counts), and for the
mixed conditional logit model, or conditional logit with random effects
(random intercepts only, no random slopes yet).
The current implementation of random effects is limited to
the PQL technique, which requires large cluster sizes.
License: GPL-2
Depends: stats, Matrix
Enhances: memisc
LazyLoad: Yes
Packaged: 2014-10-13 21:17:58 UTC; elff
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2014-10-14 05:27:20

● Data Source: CranContrib
● 0 images, 3 functions, 2 datasets
● Reverse Depends: 0

mclust : Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation

Package: mclust
Version: 5.2
Date: 2016-03-22
Authors@R: c(person("Chris", "Fraley", role = "aut"),
person("Adrian E.", "Raftery", role = "aut"),
person("Luca", "Scrucca", role = c("aut", "cre"),
email = "luca@stat.unipg.it"),
person("Thomas Brendan", "Murphy", role = "ctb"),
person("Michael", "Fop", role = "ctb"))
Title: Gaussian Mixture Modelling for Model-Based Clustering,
Classification, and Density Estimation
Description: Gaussian finite mixture models fitted via EM algorithm for model-based clustering, classification, and density estimation, including Bayesian regularization, dimension reduction for visualisation, and resampling-based inference.
Depends: R (>= 3.0)
Imports: stats, utils, graphics, grDevices
Suggests: knitr (>= 1.12), rmarkdown (>= 0.9), mix (>= 1.0)
License: GPL (>= 2)
URL: http://www.stat.washington.edu/mclust/
VignetteBuilder: knitr
Repository: CRAN
ByteCompile: true
LazyLoad: yes
NeedsCompilation: yes
Packaged: 2016-03-31 11:16:20 UTC; luca
Author: Chris Fraley [aut],
Adrian E. Raftery [aut],
Luca Scrucca [aut, cre],
Thomas Brendan Murphy [ctb],
Michael Fop [ctb]
Maintainer: Luca Scrucca <luca@stat.unipg.it>
Date/Publication: 2016-03-31 17:39:13

● Data Source: CranContrib
● Cran Task View: Environmetrics, Multivariate
● 0 images, 91 functions, 9 datasets
● Reverse Depends: 23

mcmc : Markov Chain Monte Carlo

Package: mcmc
Version: 0.9-4
Date: 2015-07-16
Title: Markov Chain Monte Carlo
Author: Charles J. Geyer <charlie@stat.umn.edu> and Leif T. Johnson
<ltjohnson@google.com>
Maintainer: Charles J. Geyer <charlie@stat.umn.edu>
Depends: R (>= 2.10.0)
Imports: stats
Suggests: xtable, Iso
ByteCompile: TRUE
Description: Simulates continuous distributions of random vectors using
Markov chain Monte Carlo (MCMC). Users specify the distribution by an
R function that evaluates the log unnormalized density. Algorithms
are random walk Metropolis algorithm (function metrop), simulated
tempering (function temper), and morphometric random walk Metropolis
(Johnson and Geyer, Annals of Statistics, 2012, function morph.metrop),
which achieves geometric ergodicity by change of variable.
License: MIT + file LICENSE
URL: http://www.stat.umn.edu/geyer/mcmc/
https://github.com/cjgeyer/mcmc
NeedsCompilation: yes
Packaged: 2015-07-16 21:03:00 UTC; geyer
Repository: CRAN
Date/Publication: 2015-07-17 00:31:01

● Data Source: CranContrib
● 0 images, 6 functions, 2 datasets
● Reverse Depends: 1

mcmcplots : Create Plots from MCMC Output

Package: mcmcplots
Type: Package
Title: Create Plots from MCMC Output
Version: 0.4.2
Date: 2015-03-15
Authors@R: c(
person("S. McKay", "Curtis", role=c("aut", "cre"), email="s.mckay.curtis@gmail.com"),
person("Ilya", "Goldin", role="ctb"),
person("Evangelos", "Evangelou", role="ctb"),
person("'sumtxt' from GitHub", role="ctb")
)
Maintainer: S. McKay Curtis <s.mckay.curtis@gmail.com>
Depends: coda (>= 0.17.1)
Imports: sfsmisc, colorspace, denstrip
Description: Functions for convenient plotting and viewing of MCMC output.
License: GPL (>= 2)
LazyLoad: yes
LazyData: yes
NeedsCompilation: no
Packaged: 2015-03-19 01:07:47 UTC; McKay
Author: S. McKay Curtis [aut, cre],
Ilya Goldin [ctb],
Evangelos Evangelou [ctb],
'sumtxt' from GitHub [ctb]
Repository: CRAN
Date/Publication: 2015-03-19 06:47:34

● Data Source: CranContrib
● 0 images, 25 functions, 0 datasets
● Reverse Depends: 0

mcmcse : Monte Carlo Standard Errors for MCMC

Package: mcmcse
Version: 1.2-1
Date: 2016-03-24
Title: Monte Carlo Standard Errors for MCMC
Author: James M. Flegal <jflegal@ucr.edu>, John Hughes
<hughesj@umn.edu> and Dootika Vats <vatsx007@umn.edu>
Maintainer: James M. Flegal <jflegal@ucr.edu>
Imports: utils, ellipse, Rcpp (>= 0.11.3)
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, mAr, knitr
Description: Provides tools for computing Monte Carlo standard
errors (MCSE) in Markov chain Monte Carlo (MCMC) settings. MCSE
computation for expectation and quantile estimators is
supported as well as multivariate estimations. The package also provides
functions for computing effective sample size and for plotting
Monte Carlo estimates versus sample size.
License: GPL (>= 2)
URL: http://faculty.ucr.edu/~jflegal
http://www.biostat.umn.edu/~johnh,
http://www.stat.umn.edu/~vatsx007
VignetteBuilder: knitr
Repository: CRAN
NeedsCompilation: yes
Packaged: 2016-03-24 23:28:03 UTC; Dootika
Date/Publication: 2016-03-25 20:01:01

● Data Source: CranContrib
● 0 images, 12 functions, 0 datasets
● Reverse Depends: 0

mco : Multiple Criteria Optimization Algorithms and Related Functions

Package: mco
Version: 1.0-15.1
Title: Multiple Criteria Optimization Algorithms and Related Functions
Description: Functions for multiple criteria optimization using genetic
algorithms and related test problems
Authors@R: c( person("Olaf", "Mersmann", role=c("aut", "cre"),
email="olafm@p-value.net"), person("Heike", "Trautmann",
role=c("ctb"), email="trautmann@wi.uni-muenster.de"),
person("Detlef", "Steuer", role=c("ctb"),
email="detlef.steuer@hsu-hamburg.de"), person("Bernd",
"Bischl", role=c("ctb"), email="bernd_bischl@gmx.net"),
person("Kalyanmoy", "Deb", role=c("cph")) )
Depends: R (>= 3.0.0)
Suggests: scatterplot3d, testthat
License: GPL-2
URL: http://git.p-value.net/p/mco.git
LazyData: yes
Packaged: 2014-11-29 10:29:35 UTC; ripley
Author: Olaf Mersmann [aut, cre],
Heike Trautmann [ctb],
Detlef Steuer [ctb],
Bernd Bischl [ctb],
Kalyanmoy Deb [cph]
Maintainer: Olaf Mersmann <olafm@p-value.net>
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2014-11-29 11:46:39

● Data Source: CranContrib
● Cran Task View: Optimization
● 0 images, 5 functions, 0 datasets
● Reverse Depends: 1

mcparallelDo : A Simplified Interface for Running Commands on Parallel Processes

Package: mcparallelDo
Type: Package
Title: A Simplified Interface for Running Commands on Parallel
Processes
Version: 1.0.0
Date: 2015-12-07
Author: Russell S. Pierce
Maintainer: Russell S. Pierce <russell.s.pierce@gmail.com>
Description: Provides a function that wraps
mcparallel() and mccollect() from 'parallel' with temporary variables and a
task handler. Wrapped in this way the results of an mcparallel() call
can be returned to the R session when the fork is complete
without explicitly issuing a specific mccollect() to retrieve the value.
Outside of top-level tasks, multiple mcparallel() jobs can be retrieved with
a single call to mcparallelDoCheck().
License: GPL-2
Suggests: testthat
RoxygenNote: 5.0.1
Imports: parallel, R.utils, ArgumentCheck, R6
NeedsCompilation: no
Packaged: 2015-12-09 07:30:42 UTC; russell
Repository: CRAN
Date/Publication: 2015-12-09 11:06:36

● Data Source: CranContrib
● 0 images, 5 functions, 1 datasets
● Reverse Depends: 0

mcprofile : Multiple Contrast Profiles

Package: mcprofile
Title: Multiple Contrast Profiles
Date: 2014-11-17
Version: 0.2-1
Author: Daniel Gerhard
Maintainer: Daniel Gerhard <00gerhard@gmail.com>
Description: Calculation of signed root deviance profiles for linear combinations of parameters in a generalized linear model. Multiple tests and simultaneous confidence intervals are provided.
Depends: ggplot2
Imports: quadprog, mvtnorm, splines
LazyLoad: yes
LazyData: yes
License: GPL (>= 2)
VignetteBuilder: knitr
Suggests: knitr, multcomp, MASS
Packaged: 2014-11-16 21:35:38 UTC; daniel
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2014-11-17 00:47:56

● Data Source: CranContrib
● 0 images, 8 functions, 3 datasets
● Reverse Depends: 0

mcr : Method Comparison Regression

Package: mcr
Version: 1.2.1
Date: 2014-02-11
Title: Method Comparison Regression
Author: Ekaterina Manuilova <ekaterina.manuilova@roche.com> Andre Schuetzenmeister <andre.schuetzenmeister@roche.com> Fabian Model <fabian.model@roche.com>
Maintainer: Fabian Model <fabian.model@roche.com>
Depends: R (>= 3.0.0), methods
Suggests: RUnit, XML
Description: This package provides regression methods to quantify the relation between two measurement methods. In particular it addresses regression problems with errors in both variables and without repeated measurements. The package provides implementations of Deming regression, weighted Deming regression, and Passing-Bablok regression following the CLSI EP09-A3 recommendations for analytical method comparison and bias estimation using patient samples.
License: GPL (>= 3)
Collate: "mcrMisc.r" "mcLinReg.r" "mcDeming.r" "mcWDeming.r"
"mcPaBaLarge.r" "mcPaBa.r" "mcCalcCI.r" "mcCalcTstar.r"
"mcBootstrap.r" "MCResultMethods.r" "MCResult.r"
"MCResultAnalyticalMethods.r" "MCResultAnalytical.r"
"MCResultJackknifeMethods.r" "MCResultJackknife.r"
"MCResultResamplingMethods.r" "MCResultResampling.r"
"MCResultBCaMethods.r" "MCResultBCa.r" "mcrInterface.r"
"mcrCompareFit.r" "mcrIncludeLegend.r" "zzz.r"
Packaged: 2014-02-12 12:20:55 UTC; modelf
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2014-02-12 13:39:04

● Data Source: CranContrib
● 0 images, 73 functions, 0 datasets
● Reverse Depends: 0