Package: mcsm
Type: Package
Title: Functions for Monte Carlo Methods with R
Version: 1.0
Date: 2009-02-26
Depends: stats, MASS, coda
Author: Christian P. Robert, Universite Paris Dauphine
Maintainer: Christian P. Robert <xian@ceremade.dauphine.fr>
Description: mcsm contains a collection of functions that allows the
reenactment of the R programs used in the book EnteR Monte
Carlo Methods without further programming. Programs being
available as well, they can be modified by the user to conduct
one's own simulations.
License: GPL (>= 2)
Packaged: 2009-04-28 10:03:21 UTC; hornik
Repository: CRAN
Date/Publication: 2009-04-28 10:10:13
Package: lira
Type: Package
Title: LInear Regression in Astronomy
Version: 1.2.0
Date: 2016-03-20
Author: Mauro Sereno
Maintainer: Mauro Sereno <mauro.sereno@unibo.it>
Description: Performs Bayesian linear regression in astronomy. The method accounts for heteroscedastic errors in both the independent and the dependent variables, intrinsic scatters (in both variables), time evolution of slopes, normalization and scatters, Malmquist and Eddington bias, and break of linearity. The posterior distribution of the regression parameters is sampled with a Gibbs method exploiting the JAGS library.
License: GPL-2
Depends: R (>= 2.14.0), coda, rjags
SystemRequirements: JAGS (>= 3.0.0) (see
http://mcmc-jags.sourceforge.net)
NeedsCompilation: no
Packaged: 2016-03-20 20:06:17 UTC; maurosereno
Repository: CRAN
Date/Publication: 2016-03-21 00:20:08
Package: MCMC.OTU
Type: Package
Title: Bayesian Analysis of Multivariate Counts Data in DNA
Metabarcoding and Ecology
Version: 1.0.10
Date: 2016-02-10
Author: Mikhail V. Matz
Maintainer: Mikhail V. Matz <matz@utexas.edu>
Description: Poisson-lognormal generalized linear mixed model analysis of multivariate counts data using MCMC, aiming to infer the changes in relative proportions of individual variables. The package was originally designed for sequence-based analysis of microbial communities ("metabarcoding", variables = operational taxonomic units, OTUs), but can be used for other types of multivariate counts, such as in ecological applications (variables = species). The results are summarized and plotted using 'ggplot2' functions. Includes functions to remove sample and variable outliers and reformat counts into normalized log-transformed values for correlation and principal component/coordinate analysis. Walkthrough and examples: http://www.bio.utexas.edu/research/matz_lab/matzlab/Methods_files/walkthroughExample_mcmcOTU_R.txt.
License: GPL-3
Depends: MCMCglmm, ggplot2, coda
NeedsCompilation: no
Packaged: 2016-02-11 19:23:29 UTC; c-monstr
Repository: CRAN
Date/Publication: 2016-02-12 00:53:04
Package: MCMC.qpcr
Type: Package
Title: Bayesian Analysis of qRT-PCR Data
Version: 1.2.2
Date: 2015-10-26
Author: Mikhail V. Matz
Maintainer: Mikhail V. Matz <matz@utexas.edu>
Description: Quantitative RT-PCR data are analyzed using generalized linear mixed models based on lognormal-Poisson error distribution, fitted using MCMC. Control genes are not required but can be incorporated as Bayesian priors or, when template abundances correlate with conditions, as trackers of global effects (common to all genes). The package also implements a lognormal model for higher-abundance data and a "classic" model involving multi-gene normalization on a by-sample basis. Several plotting functions are included to extract and visualize results. The detailed tutorial is available here: http://bit.ly/1Nwo4CB.
License: GPL-3
Depends: MCMCglmm, ggplot2, coda
NeedsCompilation: no
Packaged: 2015-10-28 00:10:05 UTC; c-monstr
Repository: CRAN
Date/Publication: 2015-10-28 08:44:52
Package: MCMCpack
Version: 1.3-6
Date: 2016-4-16
Title: Markov Chain Monte Carlo (MCMC) Package
Author: Andrew D. Martin, Kevin M. Quinn, and Jong Hee Park
Maintainer: Jong Hee Park <jongheepark@snu.ac.kr>
Depends: R (>= 2.10.0), coda (>= 0.11-3), MASS, stats
Imports: graphics, grDevices, lattice, methods, utils, mcmc, quantreg
Description: Contains functions to perform Bayesian
inference using posterior simulation for a number of
statistical models. Most simulation is done in compiled C++
written in the Scythe Statistical Library Version 1.0.3. All
models return coda mcmc objects that can then be summarized
using the coda package. Some useful
utility functions such as density functions,
pseudo-random number generators for statistical
distributions, a general purpose Metropolis sampling algorithm,
and tools for visualization are provided.
License: GPL-3
SystemRequirements: gcc (>= 4.0)
URL: http://mcmcpack.berkeley.edu
Packaged: 2016-04-15 00:19:09 UTC; parkjonghee
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2016-04-15 08:32:53
Package: HSROC
Type: Package
Title: Meta-Analysis of Diagnostic Test Accuracy when Reference Test is
Imperfect
Version: 2.1.8
Date: 2015-02-09
Author: Ian Schiller and Nandini Dendukuri
Maintainer: Ian Schiller <ian.schiller@clinepi.mcgill.ca>
Depends: R (>= 3.1.2), lattice, coda, MASS, MCMCpack
Description: Implements a model for joint meta-analysis of sensitivity and specificity of the diagnostic test under evaluation, while taking into account the possibly imperfect sensitivity and specificity of the reference test. This hierarchical model accounts for both within and between study variability. Estimation is carried out using a Bayesian approach, implemented via a Gibbs sampler. The model can be applied in situations where more than one reference test is used in the selected studies.
License: GPL-2
URL: http://www.nandinidendukuri.com/
Encoding: latin1
Packaged: 2015-02-09 19:01:28 UTC; ian.schiller
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2015-02-10 00:32:01
providing 
.