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: HydeNet
Type: Package
Title: Hybrid Bayesian Networks Using R and JAGS
Version: 0.10.3
Date: 2015-01-18
Author: Jarrod E. Dalton <daltonj@ccf.org> and Benjamin Nutter <benjamin.nutter@gmail.com>
Maintainer: Benjamin Nutter <benjamin.nutter@gmail.com>
Description: Facilities for easy implementation of hybrid Bayesian networks
using R. Bayesian networks are directed acyclic graphs representing joint
probability distributions, where each node represents a random variable and
each edge represents conditionality. The full joint distribution is
therefore factorized as a product of conditional densities, where each node
is assumed to be independent of its non-descendents given information on its
parent nodes. Since exact, closed-form algorithms are computationally
burdensome for inference within hybrid networks that contain a combination
of continuous and discrete nodes, particle-based approximation techniques
like Markov Chain Monte Carlo are popular. We provide a user-friendly
interface to constructing these networks and running inference using the 'rjags' package.
Econometric analyses (maximum expected utility under competing policies,
value of information) involving decision and utility nodes are also
supported.
License: MIT + file LICENSE
Depends: R (>= 3.0.0), nnet, rjags
Imports: ArgumentCheck, DiagrammeR (>= 0.8), plyr, dplyr, graph, gRbase, magrittr, pixiedust (>= 0.6.1), stats, stringr, utils
Suggests: knitr, survival, testthat
VignetteBuilder: knitr
SystemRequirements: JAGS (http://mcmc-jags.sourceforge.net)
LazyLoad: yes
LazyData: true
URL: https://github.com/nutterb/HydeNet,
BugReports: https://github.com/nutterb/HydeNet/issues
NeedsCompilation: no
Packaged: 2016-02-05 13:36:55 UTC; Nutter
Repository: CRAN
Date/Publication: 2016-02-05 19:41:00
Package: PurBayes
Type: Package
Title: Bayesian Estimation of Tumor Purity and Clonality
Version: 1.3
Date: 2013-05-13
Author: Nicholas B. Larson
Maintainer: Nicholas B. Larson <larson.nicholas@mayo.edu>
Depends: rjags
Description: PurBayes is an MCMC-based algorithm that uses
next-generation sequencing data to estimate tumor purity and
clonality for paired tumor-normal data.
License: GPL-2
Packaged: 2013-05-16 12:59:54 UTC; m097340
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2013-05-16 17:20:31
Package: R2jags
Version: 0.5-7
Date: 2015-8-22
Title: Using R to Run 'JAGS'
Author: Yu-Sung Su <suyusung@tsinghua.edu.cn>,
Masanao Yajima <yajima@stat.ucla.edu>,
Maintainer: Yu-Sung Su <suyusung@tsinghua.edu.cn>
Depends: R (>= 2.14.0), rjags (>= 3-3)
Imports: abind, coda (>= 0.13), graphics, grDevices, methods, R2WinBUGS, parallel, stats, utils
SystemRequirements: JAGS (http://mcmc-jags.sourceforge.net)
Description: Providing wrapper functions to implement Bayesian analysis in JAGS. Some major features include monitoring convergence of a MCMC model using Rubin and Gelman Rhat statistics, automatically running a MCMC model till it converges, and implementing parallel processing of a MCMC model for multiple chains.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2015-08-22 14:21:26 UTC; suyusung
Repository: CRAN
Date/Publication: 2015-08-23 10:39:57
Package: BANOVA
Type: Package
Title: Hierarchical Bayesian ANOVA Models
Version: 0.5
Date: 2016-04-02
Author: Chen Dong, Michel Wedel
SystemRequirements: JAGS (http://mcmc-jags.sourceforge.net)
Maintainer: Chen Dong <cdong@math.umd.edu>
Depends: R (>= 3.0.1), rjags (>= 3-13), runjags (>= 1.2.1-0), coda (>=
0.16-1)
Description: It covers several Bayesian Analysis of Variance (BANOVA) models used in analysis of experimental designs in which both within- and between- subjects factors are manipulated. They can be applied to data that are common in the behavioral sciences and related fields. The package includes: Hierarchical Bayes ANOVA models with normal response, t response, Binomial(Bernoulli) response, Poisson response, ordered multinomial response and multinomial response variables. All models accommodate unobserved heterogeneity by including a normal distribution of the parameters across individuals. Outputs of the package include tables of sums of squares, effect sizes and p-values, and tables of means, which are easily interpretable for behavioral researchers. BANOVA uses JAGS as the computational platform.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2016-04-03 03:24:15 UTC; CDONG
Repository: CRAN
Date/Publication: 2016-04-03 19:37:13
Package: BaySIC
Type: Package
Title: Bayesian Analysis of Significantly Mutated Genes in Cancer
Version: 1.0
Date: 2013-03-12
Author: Nicholas B. Larson
Maintainer: Nicholas B. Larson <larson.nicholas@mayo.edu>
Depends: R (>= 2.10), rjags, fields, poibin
Description: This R package is the software implementation of the
algorithm BaySIC, a Bayesian approach toward analysis of
significantly mutated genes in cancer data.
License: GPL (>= 2)
Packaged: 2013-04-03 12:50:37 UTC; m097340
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2013-04-04 00:51:05
Package: auRoc
Title: Various Methods to Estimate the AUC
Version: 0.1-0
Author: Dai Feng
Description: Estimate the AUC using a variety of methods as follows:
(1) frequentist nonparametric methods based on the Mann-Whitney statistic or kernel methods.
(2) frequentist parametric methods using the likelihood ratio test based on higher-order
asymptotic results, the signed log-likelihood ratio test, the Wald test,
or the approximate ''t'' solution to the Behrens-Fisher problem.
(3) Bayesian parametric MCMC methods.
Maintainer: Dai Feng <dai_feng@merck.com>
Depends: R (>= 3.0.2), rjags (>= 3-11), ProbYX (>= 1.1)
Imports: coda (>= 0.16-1), MBESS (>= 3.3.3)
License: GPL
NeedsCompilation: no
Packaged: 2015-12-21 20:29:11 UTC; fengd
Repository: CRAN
Date/Publication: 2015-12-21 21:57:32
Package: simmr
Type: Package
Title: A Stable Isotope Mixing Model
Version: 0.3
Date: 2016-01-18
Author: Andrew Parnell
Maintainer: Andrew Parnell <andrew.parnell@ucd.ie>
Description: Fits a stable isotope mixing model via JAGS in R. The package allows for any number of isotopes or sources, as well as concentration dependencies.
Depends: R (>= 3.2.2), rjags, ggplot2
Imports: MASS, compositions, boot, reshape2, coda, graphics, stats, viridis
Encoding: UTF-8
License: GPL (>= 2)
LazyData: TRUE
Suggests: knitr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2016-01-19 08:48:41 UTC; andrewparnell
Repository: CRAN
Date/Publication: 2016-01-19 11:57:28
Package: prevalence
Type: Package
Title: Tools for Prevalence Assessment Studies
Version: 0.4.0
Date: 2015-04-20
Authors@R: c(person("Brecht", "Devleesschauwer",
role = c("aut", "cre"), email = "brechtdv@gmail.com"),
person("Paul", "Torgerson", role = "aut"),
person("Johannes", "Charlier", role = "aut"),
person("Bruno", "Levecke", role = "aut"),
person("Nicolas", "Praet", role = "aut"),
person("Sophie", "Roelandt", role = "aut"),
person("Suzanne", "Smit", role = "aut"),
person("Pierre", "Dorny", role = "aut"),
person("Dirk", "Berkvens", role = "aut"),
person("Niko", "Speybroeck", role = "aut"))
Author: Brecht Devleesschauwer [aut, cre], Paul Torgerson [aut],
Johannes Charlier [aut], Bruno Levecke [aut], Nicolas Praet [aut],
Sophie Roelandt [aut], Suzanne Smit [aut], Pierre Dorny [aut],
Dirk Berkvens [aut], Niko Speybroeck [aut]
Maintainer: Brecht Devleesschauwer <brechtdv@gmail.com>
BugReports: https://github.com/brechtdv/prevalence/issues
Description: The prevalence package provides Frequentist and Bayesian methods for prevalence assessment studies. IMPORTANT: the truePrev functions in the prevalence package call on JAGS (Just Another Gibbs Sampler), which therefore has to be available on the user's system. JAGS can be downloaded from http://mcmc-jags.sourceforge.net/.
Depends: R (>= 3.0.0), rjags, coda, methods
SystemRequirements: JAGS (>= 3.2.0) (see
http://mcmc-jags.sourceforge.net)
License: GPL (>= 2)
URL: http://prevalence.cbra.be/
LazyLoad: yes
NeedsCompilation: no
Packaged: 2015-04-20 14:55:49 UTC; UGent
Repository: CRAN
Date/Publication: 2015-04-20 18:30:21
providing 
.