Package: lmSupport
Type: Package
Title: Support for Linear Models
Version: 2.9.4
Date: 2016-04-20
Author: John Curtin <jjcurtin@wisc.edu>
Maintainer: John Curtin <jjcurtin@wisc.edu>
Description: Accompanies Markus Brauer, Bas Rokers, and John Curtin's two-course
graduate series in General, Generalized, and Multi-level Linear Models (PSY
610/710).
License: GPL (>= 2)
Depends: car
Imports: psych, gvlma, AICcmodavg, lme4, pbkrtest, grDevices, graphics, stats, utils
LazyLoad: yes
URL: http://dionysus.psych.wisc.edu/
NeedsCompilation: no
RoxygenNote: 5.0.1
Packaged: 2016-04-20 15:26:34 UTC; jjcurtin
Repository: CRAN
Date/Publication: 2016-04-20 21:20:07
Package: lmeNBBayes
Type: Package
Title: Compute the Personalized Activity Index Based on a Flexible
Bayesian Negative Binomial Model
Version: 1.3.1
Date: 2013-12-13
Author: Yumi Kondo
Maintainer: Yumi Kondo <y.kondo@stat.ubc.ca>
Description: The functions in this package implement the safety monitoring procedures proposed in the paper titled "A flexible mixed effect negative binomial regression model for detecting unusual increases in MRI lesion counts in individual multiple sclerosis patients" by Kondo, Y., Zhao, Y. and Petkau, A.J. 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 is modelled with the infinite mixture of Beta distributions, very flexible distribution that theoretically allows any form. The package also has the option of a single beta distribution for random effects. These mixed-effect models could be useful beyond the application of the safety monitoring. The inference is based on MCMC samples and this package contains a Gibbs sampler to sample from the posterior distribution of the negative binomial mixed-effect regression model. Based on the fitted model, the personalized activity index is computed for each patient. Lastly, this package is companion to R package lmeNB, which contains the functions to compute the Personalized Activity Index in the frequentist framework.
License: GPL (>= 2)
Depends:
LinkingTo:
Packaged: 2015-02-20 22:51:57 UTC; yumikondo
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2015-02-21 01:31:16
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: lmeVarComp
Type: Package
Title: Testing for a subset of variance components in linear mixed
models
Version: 1.0
Date: 2014-08-27
Author: Yichi Zhang
Maintainer: Yichi Zhang <yzhang52@ncsu.edu>
Description: Test zero variance components in linear mixed models and
test additivity in nonparametric regression
using the restricted likelihood ratio test and the generalized F-test.
License: GPL (>= 2)
Suggests: RLRsim, varComp
ByteCompile: yes
NeedsCompilation: yes
Packaged: 2014-08-27 17:33:32 UTC; yzhang52
Repository: CRAN
Date/Publication: 2014-08-27 21:17:18
Package: lmec
Type: Package
Title: Linear Mixed-Effects Models with Censored Responses
Version: 1.0
Date: 2009-01-28
Author: Florin Vaida and Lin Liu
Maintainer: Lin Liu <linliu@ucsd.edu>
Description: This package includes a function to fit a linear
mixed-effects model in the formulation described in Laird and
Ware (1982) but allowing for censored normal responses. In this
version, the with-in group errors are assumed independent and
identically distributed.
License: GPL-2
Depends: mvtnorm
Packaged: 2012-10-29 08:59:06 UTC; ripley
Repository: CRAN
Date/Publication: 2012-10-29 08:59:06
Package: lmem.qtler
Type: Package
Title: Linear Mixed Effects Models for QTL Mapping for Multienvironment
and Multitrait Analysis
Version: 0.1.0
Authors@R: c(person("Lucia", "Gutierrez", role = "aut",
email = "gutierrezcha@wisc.edu"),
person("Gaston", "Quero",role =c("aut","cre"),
email = "gastonquero@gmail.com"),
person("Schubert", "Fernandez",role ="aut",
email = "sfernandez@inia.org.uy"),
person("Sofia", "Brandariz",role ="aut",
email = "brandarizsofia@gmail.com"),
person("Sebastian", "Simondi",role ="ctb",
email = "sebastian.simondi@gmail.com"))
Author: Lucia Gutierrez [aut],
Gaston Quero [aut, cre],
Schubert Fernandez [aut],
Sofia Brandariz [aut],
Sebastian Simondi [ctb]
Maintainer: Gaston Quero <gastonquero@gmail.com>
Description: Performs QTL mapping analysis for balanced and for
multi-environment and multi-trait analysis using mixed models.
Balanced population, single trait, single environment QTL mapping is
performed through marker-regression (Haley and Knott (1992) <DOI:10.1038/hdy.1992.131>,
Martinez and Curnow (1992) <DOI:10.1007/BF00222330>,
while multi-environment and multi-trait QTL
mapping is performed through linear mixed models.
These functions could use any of the following populations: double haploid,
F2, recombinant inbred lines, back-cross, and 4-way crosses.
Performs a Single Marker Analysis, a Single Interval Mapping,
or a Composite Interval Mapping analysis, and then constructs a final model
with all of the relevant QTL.
License: GPL-3
Depends: R (>= 2.10)
LazyData: TRUE
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
Imports: qtl, lme4, lattice, pastecs, stringr, graphics, utils, grDevices, stats
Encoding: UTF-8
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-05-05 15:16:20 UTC; GQ
Repository: CRAN
Date/Publication: 2016-05-06 00:09:50
Package: lmenssp
Type: Package
Title: Linear Mixed Effects Models with Non-Stationary Stochastic
Processes
Version: 1.1
Date: 2015-07-17
Author: Ozgur Asar, Peter J. Diggle
Maintainer: Ozgur Asar <o.asar@lancaster.ac.uk>
Depends: MASS, nlme, mvtnorm, geoR,
Description: Contains functions to estimate model parameters and filter, smooth and forecast random effects coefficients for mixed models with stationary and non-stationary stochastic processes under multivariate normal and t response distributions, diagnostic checks, bootstrap standard error calculation, etc.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2015-07-17 16:45:59 UTC; asar
Repository: CRAN
Date/Publication: 2015-07-17 19:58:17
providing 
.