Package: mdhglm
Type: Package
Title: Multivariate Double Hierarchical Generalized Linear Models
Version: 1.4
Date: 2016-06-28
Author: Youngjo Lee, Marek Molas, Maengseok Noh
Maintainer: Maengseok Noh <msnoh@pknu.ac.kr>
Description: Allows various models for multivariate response variables where each response is assumed to follow double hierarchical generalized linear models. In double hierarchical generalized linear models, the mean, dispersion parameters for variance of random effects, and residual variance can be further modeled as random-effect models.
Depends: R (>= 3.2.0), methods, Matrix, numDeriv, boot, mvtnorm
License: Unlimited
NeedsCompilation: no
Packaged: 2016-06-28 06:47:37 UTC; msnoh
Repository: CRAN
Date/Publication: 2016-06-28 08:56:42
Package: mederrRank
Title: Bayesian Methods for Identifying the Most Harmful Medication
Errors
Version: 0.0.8
Date: 2015-07-06
Description: Two distinct but related statistical approaches to the problem of identifying the combinations of medication error characteristics that are more likely to result in harm are implemented in this package: 1) a Bayesian hierarchical model with optimal Bayesian ranking on the log odds of harm, and 2) an empirical Bayes model that estimates the ratio of the observed count of harm to the count that would be expected if error characteristics and harm were independent. In addition, for the Bayesian hierarchical model, the package provides functions to assess the sensitivity of results to different specifications of the random effects distributions.
Author: Sergio Venturini, Jessica Myers
Maintainer: Sergio Venturini <sergio.venturini@unibocconi.it>
Depends: BB, methods, numDeriv, utils
Imports: graphics, stats
License: GPL (>= 2)
LazyLoad: yes
NeedsCompilation: no
Packaged: 2015-07-07 16:34:25 UTC; Sergio
Repository: CRAN
Date/Publication: 2015-07-08 00:27:38
Package: mgpd
Type: Package
Title: mgpd: Functions for multivariate generalized Pareto distribution
(MGPD of Type II)
Version: 1.99
Date: 2012-03-15
Author: Pal Rakonczai
Maintainer: Pal Rakonczai <rakonczai.p@gmail.com>
Depends: R (>= 2.10.1), evd, numDeriv, corpcor, fields
Description: Extends distribution and density functions to parametric
multivariate generalized Pareto distributions (MGPD of Type
II), and provides fitting functions which calculate maximum
likelihood estimates for bivariate and trivariate models. (Help
is under progress)
License: GPL-3
Packaged: 2012-03-19 17:13:26 UTC; Irgumburgum
Repository: CRAN
Date/Publication: 2012-03-19 17:35:21
Package: lmeNB
Type: Package
Title: Compute the Personalized Activity Index Based on a Negative
Binomial Model
Version: 1.3
Date: 2015-01-14
Author: Yinshan Zhao and Yumi Kondo (with contributions from Steven G. Johnson, Rudolf Schuerer and Brian Gough on the integration subroutines)
Maintainer: Yumi Kondo <y.kondo@stat.ubc.ca>
Description: The functions in this package implement the safety monitoring procedures proposed in the paper titled "Detection of unusual increases in MRI lesion counts in individual multiple sclerosis patients" by Zhao, Y., Li, D.K.B., Petkau, A.J., Riddehough, A., Traboulsee, A., published in Journal of the American Statistical Association in 2013. The procedure first models longitudinally collected count variables with a negative binomial mixed-effect regression model. To account for the correlation among repeated measures from the same patient, the model has subject-specific random intercept, which can be modelled with a gamma or log-normal distributions. One can also choose the semi-parametric option which does not assume any distribution for the random effect. These mixed-effect models could be useful beyond the application of the safety monitoring. The maximum likelihood methods are used to estimate the unknown fixed effect parameters of the model. Based on the fitted model, the personalized activity index is computed for each patient. Lastly, this package is companion to R package lmeNBBayes, which contains the functions to compute the Personalized Activity Index in Bayesian framework.
License: GPL (>= 2)
Copyright: The portion of numerical integration is based on Cubature,
Copyright (c) 2005-2013 Steven G. Johnson
(http://ab-initio.mit.edu/wiki/index.php/Cubature), which in
turn is based on HIntLib (also distributed under * the GNU GPL,
v2 or later), copyright (c) 2002-2005 Rudolf Schuerer and GNU
GSL (also distributed under the GNU GPL, v2 or later),
copyright (c) 1996-2000 Brian
Gough.(http://www.gnu.org/software/gsl/).
LazyData: true
Depends: numDeriv, statmod, lmeNBBayes
Packaged: 2015-02-02 20:00:39 UTC; yumikondo
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2015-02-02 22:40:23
Package: ltbayes
Type: Package
Title: Simulation-Based Bayesian Inference for Latent Traits of Item
Response Models
Version: 0.3
Date: 2014-07-28
Author: Timothy R. Johnson
Maintainer: Timothy R. Johnson <trjohns@uidaho.edu>
Description: Functions for simulating realizations from the posterior distribution of
a latent trait of an item response model. Distributions are conditional on one or
a subset of response patterns (e.g., sum scores). Functions for computing likelihoods,
Fisher and observed information, posterior modes, and profile likelihood confidence
intervals are also included. These functions are designed to be easily amenable to
user-specified models.
Depends: R (>= 3.1.1), mcmc (>= 0.9-3), MHadaptive (>= 1.1-8), numDeriv
(>= 2012.9-1)
Suggests: coda, mcmcplots, ggmcmc, knitr, ggplot2, gridExtra, reshape2
License: GPL (>= 2)
VignetteBuilder: knitr
Packaged: 2014-07-28 16:17:20 UTC; trjohns
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2014-07-28 18:32:54
Package: mipfp
Type: Package
Title: Multidimensional Iterative Proportional Fitting and Alternative
Models
Version: 3.0-1
Date: 2016-04-29
Authors@R: c(
person("Johan", "Barthelemy", role = c("aut", "cre"), email = "johan@uow.edu.au"),
person("Thomas", "Suesse", role = "aut"),
person("Mohammad", "Namazi-Rad", role = "ctb"))
Author: Johan Barthelemy [aut, cre], Thomas Suesse [aut], Mohammad Namazi-Rad [ctb]
Maintainer: Johan Barthelemy <johan@uow.edu.au>
Description: An implementation of the iterative proportional fitting (IPFP),
maximum likelihood, minimum chi-square and weighted least squares procedures
for updating a N-dimensional array with respect to given target marginal
distributions (which, in turn can be multi-dimensional). The package also
provides an application of the IPFP to simulate multivariate Bernoulli
distributions.
LazyData: yes
Depends: cmm, Rsolnp, numDeriv, R (>= 2.10.0)
License: GPL-2
URL: https://github.com/jojo-/mipfp
NeedsCompilation: no
Packaged: 2016-04-29 03:24:55 UTC; johan
Repository: CRAN
Date/Publication: 2016-04-29 12:11:46
Package: mvglmmRank
Type: Package
Title: Multivariate Generalized Linear Mixed Models for Ranking Sports
Teams
Version: 1.1-2
Depends: Matrix, numDeriv, methods, stats, utils
Date: 2015-11-10
Author: Andrew T. Karl (Adsurgo LLC), Jennifer Broatch (Arizona State University)
Maintainer: Andrew T. Karl <akarl@asu.edu>
Description: Maximum likelihood estimates are obtained via an EM algorithm with either a first-order or a fully exponential Laplace approximation.
ByteCompile: yes
LazyLoad: yes
LazyData: yes
License: GPL-2
NeedsCompilation: no
Packaged: 2015-11-13 06:48:51 UTC; Andrew
Repository: CRAN
Date/Publication: 2015-11-13 08:55:53
providing 
.