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Last data update: 2014.03.03

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Results 1 - 6 of 6 found.
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MIXFIM : Evaluation of the FIM in NLMEMs using MCMC

Package: MIXFIM
Type: Package
Title: Evaluation of the FIM in NLMEMs using MCMC
Version: 1.0
Date: 2015-08-17
Author: Marie-Karelle Riviere-Jourdan and France Mentre <france.mentre@inserm.fr>
Maintainer: Marie-Karelle Riviere-Jourdan <eldamjh@gmail.com>
Copyright: All files are copyright Institut National de la Sante Et de
la Recherche Medicale.
Description: Evaluation and optimization of the Fisher Information Matrix in NonLinear Mixed Effect Models using Markov Chains Monte Carlo for continuous and discrete data.
License: GPL-3
Depends: R (>= 3.0.2), rstan (>= 2.7.0-1), mvtnorm (>= 1.0-2), ggplot2
(>= 1.0.1)
LinkingTo:
Packaged: 2015-08-31 18:49:21 UTC; Marie-Karelle
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2015-08-31 23:58:27

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

eggCounts : Hierarchical Modelling of Faecal Egg Counts

Package: eggCounts
Imports: actuar, boot, coda, utils, testthat, numbers
Depends: R (>= 3.2.0), Rcpp (>= 0.11.0), rstan (>= 2.9.0-3), methods
Suggests: lattice
Title: Hierarchical Modelling of Faecal Egg Counts
Version: 1.0
Date: 2016-04-09
Authors@R: c(person("Craig", "Wang", role = c("cre","aut"),
email = "craig.wang@uzh.ch"),
person("Michaela", "Paul", role = c("aut"),
email = "michaela.paul@uzh.ch"),
person("Reinhard", "Furrer", role = c("ctb"),
email = "reinhard.furrer@math.uzh.ch"),
person("Trustees of", "Columbia University", role = "cph", comment = "rstanarm"))
Description: An implementation of hierarchical models
for faecal egg count data to assess anthelmintic
efficacy. Bayesian inference is done via MCMC sampling using Stan.
License: GPL (>= 3)
LinkingTo: StanHeaders (>= 2.9.0), rstan (>= 2.9.0-3), BH (>= 1.58.0),
Rcpp (>= 0.11.0), RcppEigen
LazyLoad: yes
NeedsCompilation: yes
URL: http://www.math.uzh.ch/as/index.php?id=eggCounts
RcppModules: stan_fit4paired_mod, stan_fit4unpaired_mod,
stan_fit4zipaired_mod, stan_fit4ziunpaired_mod,
stan_fit4nb_mod, stan_fit4zinb_mod
Packaged: 2016-04-16 08:03:41 UTC; crwang
Author: Craig Wang [cre, aut],
Michaela Paul [aut],
Reinhard Furrer [ctb],
Trustees of Columbia University [cph] (rstanarm)
Maintainer: Craig Wang <craig.wang@uzh.ch>
Repository: CRAN
Date/Publication: 2016-04-16 10:46:51

● Data Source: CranContrib
● 0 images, 7 functions, 3 datasets
● Reverse Depends: 0

CopulaDTA : Copula Based Bivariate Beta-Binomial Model for Diagnostic Test Accuracy Studies

Package: CopulaDTA
Type: Package
Title: Copula Based Bivariate Beta-Binomial Model for Diagnostic Test
Accuracy Studies
Version: 0.0.3
Date: 2016-05-31
Authors@R: person("Victoria", "N Nyaga", email="victoria.nyaga@outlook.com", role=c("aut", "cre"))
Depends: R (>= 3.2.2), rstan (>= 2.8.2)
Imports: methods, ggplot2 (>= 1.0.1), plyr (>= 1.8.3), stats (>=
3.2.2), reshape2 (>= 1.4.1), grDevices (>= 3.2.2)
Description: Modelling of sensitivity and specificity on their natural scale
using copula based bivariate beta-binomial distribution to yield marginal mean sensitivity
and specificity. The intrinsic negative correlation between sensitivity and
specificity is modelled using a copula function. A forest plot can be obtained
for categorical covariates or for the model with intercept only.
License: GPL-2
LazyData: TRUE
RoxygenNote: 5.0.1
Suggests: testthat, knitr, loo, Rmisc, httr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2016-05-31 14:04:03 UTC; Dries
Author: Victoria N Nyaga [aut, cre]
Maintainer: Victoria N Nyaga <victoria.nyaga@outlook.com>
Repository: CRAN
Date/Publication: 2016-06-01 16:22:48

● Data Source: CranContrib
● 0 images, 17 functions, 0 datasets
● Reverse Depends: 0

hBayesDM : Hierarchical Bayesian Modeling of Decision-Making Tasks

Package: hBayesDM
Title: Hierarchical Bayesian Modeling of Decision-Making Tasks
Version: 0.2.1
Date: 2016-04-02
Authors@R: c(
person("Woo-Young", "Ahn", email = "ahn.280@osu.edu", role = c("aut", "cre")),
person("Nate", "Haines", email = "haines.175@osu.edu", role = c("aut")),
person("Lei", "Zhang", email = "bnuzhanglei2008@gmail.com", role = c("aut")) )
Description: Fit an array of decision-making tasks with computational models in a hierarchical Bayesian framework. Can perform hierarchical Bayesian analysis of various computational models with a single line of coding.
Depends: rstan, loo, R (>= 3.0.2)
Imports: grid, parallel, mail, modeest, ggplot2
URL: http://u.osu.edu/ccsl/codedata/hbayesdm/
License: GPL-3
LazyData: true
Author: Woo-Young Ahn [aut, cre],
Nate Haines [aut],
Lei Zhang [aut]
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-04-02 23:10:14 UTC; wahn
Maintainer: Woo-Young Ahn <ahn.280@osu.edu>
Repository: CRAN
Date/Publication: 2016-04-03 16:55:57

● Data Source: CranContrib
● 0 images, 21 functions, 0 datasets
● Reverse Depends: 0

brms : Bayesian Regression Models using Stan

Package: brms
Type: Package
Title: Bayesian Regression Models using Stan
Version: 0.9.1
Date: 2016-05-09
Authors@R: person("Paul-Christian", "Buerkner", email = "paul.buerkner@gmail.com",
role = c("aut", "cre"))
Depends: R (>= 3.2.0), rstan (>= 2.9.0), ggplot2 (>= 2.0.0), methods
Imports: loo (>= 0.1.4), shinystan (>= 2.1.0), gridExtra (>= 2.0.0),
lme4 (>= 1.1-11), Matrix (>= 1.1.1), coda, abind, statmod,
stats, graphics, utils, parallel, grDevices, grid
Suggests: testthat (>= 0.9.1), mvtnorm, KernSmooth, R.rsp, knitr,
rmarkdown
Description: Fit Bayesian generalized (non-)linear mixed models using Stan for full
Bayesian inference.
LazyData: true
NeedsCompilation: yes
License: GPL (>= 3)
URL: http://github.com/paul-buerkner/brms
BugReports: http://github.com/paul-buerkner/brms/issues
VignetteBuilder: R.rsp, knitr
RoxygenNote: 5.0.1
Packaged: 2016-05-17 14:49:28 UTC; paulb
Author: Paul-Christian Buerkner [aut, cre]
Maintainer: Paul-Christian Buerkner <paul.buerkner@gmail.com>
Repository: CRAN
Date/Publication: 2016-05-17 21:13:39

● Data Source: CranContrib
● 0 images, 42 functions, 3 datasets
● Reverse Depends: 0

varian : Variability Analysis in R

Package: varian
Type: Package
Version: 0.2.2
Title: Variability Analysis in R
Description: Uses a Bayesian model to
estimate the variability in a repeated
measure outcome and use that as an outcome or a predictor
in a second stage model.
Date: 2016-2-28
Author: Joshua F. Wiley [aut, cre],
Elkhart Group Limited [cph]
Maintainer: Joshua F. Wiley <josh@elkhartgroup.com>
URL: https://github.com/ElkhartGroup/varian
BugReports: https://github.com/ElkhartGroup/varian/issues
Depends: R (>= 3.1.1), rstan (>= 2.7.0), ggplot2
Imports: stats, MASS, Formula, grid, gridExtra
Suggests: testthat
LazyLoad: yes
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2016-02-28 11:18:15 UTC; Joshua
Repository: CRAN
Date/Publication: 2016-02-28 12:57:15

● Data Source: CranContrib
● 0 images, 13 functions, 0 datasets
● Reverse Depends: 0