Package: modelfree
Type: Package
Version: 1.1-1
Date: 08/08/2012
Title: Model-free estimation of a psychometric function
Author: Ivan Marin-Franch <imarinfr@indiana.edu>, Kamila Zychaluk
<kamila.zychaluk@liverpool.ac.uk>, and David H. Foster
<d.h.foster@manchester.ac.uk>
Maintainer: Kamila Zychaluk <kamila.zychaluk@liverpool.ac.uk>
Depends: R (>= 2.8.1), PolynomF (>= 0.93), SparseM (>= 0.79), stats, utils, base
LazyLoad: yes
LazyData: yes
Description: Local linear estimation of psychometric functions.
Provides functions for nonparametric estimation of a
psychometric function and for estimation of a derived threshold
and slope, and their standard deviations and confidence
intervals
URL: http://www.modelfree.manchester.ac.uk
http://www.modelfree.liv.ac.uk,
http://modelfree.r-forge.r-project.org/
License: GPL (>= 2)
Packaged: 2012-08-09 12:50:21 UTC; zychaluk
Repository: CRAN
Date/Publication: 2012-08-09 14:45:26
Package: maxent
Type: Package
Title: Low-memory Multinomial Logistic Regression with Support for Text
Classification
Version: 1.3.3.1
Date: 2013-04-06
Author: Timothy P. Jurka, Yoshimasa Tsuruoka
Maintainer: Timothy P. Jurka <tpjurka@ucdavis.edu>
Depends: R (>= 2.13.0), methods, SparseM, tm
Imports: Rcpp
LinkingTo: Rcpp
Description: maxent is an R package with tools for low-memory
multinomial logistic regression, also known as maximum entropy.
The focus of this maximum entropy classifier is to minimize
memory consumption on very large datasets, particularly sparse
document-term matrices represented by the tm package. The
classifier is based on an efficient C++ implementation written
by Dr. Yoshimasa Tsuruoka.
License: GPL-3
LazyLoad: yes
Packaged: 2013-11-14 17:02:54 UTC; ripley
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2013-11-14 18:03:19
Package: RTextTools
Type: Package
Title: Automatic Text Classification via Supervised Learning
Version: 1.4.2
Date: 2014-01-18
Author: Timothy P. Jurka, Loren Collingwood, Amber E. Boydstun,
Emiliano Grossman, Wouter van Atteveldt
Maintainer: Timothy P. Jurka <tpjurka@ucdavis.edu>
Depends: R (>= 2.15.0), SparseM
Imports: methods, randomForest, tree, nnet, tm, e1071, ipred, caTools, maxent, glmnet, tau
Description: RTextTools is a machine learning package for automatic
text classification that makes it simple for novice users to
get started with machine learning, while allowing experienced
users to easily experiment with different settings and
algorithm combinations. The package includes nine algorithms
for ensemble classification (svm, slda, boosting, bagging,
random forests, glmnet, decision trees, neural networks,
maximum entropy), comprehensive analytics, and thorough
documentation.
License: GPL-3
URL: http://www.rtexttools.com/
NeedsCompilation: yes
Repository: CRAN
Packaged: 2014-01-19 01:10:18 UTC; tjurka
Date/Publication: 2014-01-19 09:07:18
Package: evmix
Title: Extreme Value Mixture Modelling, Threshold Estimation and
Boundary Corrected Kernel Density Estimation
Version: 2.6
Date: 2015-05-27
Author: Carl Scarrott and Yang Hu, University of Canterbury
Maintainer: Carl Scarrott <carl.scarrott@canterbury.ac.nz>
Depends: stats, graphics, MASS, splines, gsl, SparseM
Description: The usual distribution functions, maximum likelihood inference and
model diagnostics for univariate stationary extreme value mixture models
are provided. Kernel density estimation including various boundary
corrected kernel density estimation methods and a wide choice of kernels,
with cross-validation likelihood based bandwidth estimator.
Reasonable consistency with the base functions in the 'evd' package is
provided, so that users can safely interchange most code.
License: GPL-3
URL: http://www.math.canterbury.ac.nz/~c.scarrott/evmix
Repository: CRAN
NeedsCompilation: no
Packaged: 2015-05-27 09:25:27 UTC; csc51
Date/Publication: 2015-05-27 14:35:20
Package: rms
Version: 4.5-0
Date: 2016-04-02
Title: Regression Modeling Strategies
Author: Frank E Harrell Jr <f.harrell@vanderbilt.edu>
Maintainer: Frank E Harrell Jr <f.harrell@vanderbilt.edu>
Depends: Hmisc (>= 3.17-3), survival (>= 2.37-6), lattice, ggplot2 (>=
2.0), SparseM
Imports: methods, quantreg, nlme (>= 3.1-123), rpart, polspline, multcomp
Suggests: boot, tcltk
Description: Regression modeling, testing, estimation, validation,
graphics, prediction, and typesetting by storing enhanced model design
attributes in the fit. 'rms' is a collection of functions that
assist with and streamline modeling. It also contains functions for
binary and ordinal logistic regression models, ordinal models for
continuous Y with a variety of distribution families, and the Buckley-James
multiple regression model for right-censored responses, and implements
penalized maximum likelihood estimation for logistic and ordinary
linear models. 'rms' works with almost any regression model, but it
was especially written to work with binary or ordinal regression
models, Cox regression, accelerated failure time models,
ordinary linear models, the Buckley-James model, generalized least
squares for serially or spatially correlated observations, generalized
linear models, and quantile regression.
License: GPL (>= 2)
URL: http://biostat.mc.vanderbilt.edu/rms
LazyLoad: yes
NeedsCompilation: yes
Packaged: 2016-04-03 16:06:37 UTC; harrelfe
Repository: CRAN
Date/Publication: 2016-04-04 08:37:12
Package: pheno
Title: Auxiliary functions for phenological data analysis
Version: 1.6
Date: 22.10.2012
Author: Joerg Schaber
Description: Provides some easy-to-use functions for time series
analyses of (plant-) phenological data sets. These functions
mainly deal with the estimation of combined phenological time
series and are usually wrappers for functions that are already
implemented in other R packages adapted to the special
structure of phenological data and the needs of phenologists.
Some date conversion functions to handle Julian dates are also
provided.
Maintainer: Joerg Schaber <j.schaber@web.de>
Depends: R (>= 2.14), nlme, SparseM, quantreg
License: GPL (>= 2)
Packaged: 2012-10-23 07:24:30 UTC; schaber
Repository: CRAN
Date/Publication: 2012-10-23 09:37:11
Package: quantreg
Title: Quantile Regression
Description: Estimation and inference methods for models of conditional quantiles:
Linear and nonlinear parametric and non-parametric (total variation penalized) models
for conditional quantiles of a univariate response and several methods for handling
censored survival data. Portfolio selection methods based on expected shortfall
risk are also included.
Version: 5.26
Authors@R: c(
person("Roger", "Koenker", role = c("cre","aut"), email = "rkoenker@illinois.edu"),
person("Stephen", "Portnoy", role = c("ctb"),
comment = "Contributions to Censored QR code", email = "sportnoy@illinois.edu"),
person(c("Pin", "Tian"), "Ng", role = c("ctb"),
comment = "Contributions to Sparse QR code", email = "pin.ng@nau.edu"),
person("Achim", "Zeileis", role = c("ctb"),
comment = "Contributions to dynrq code essentially identical to his dynlm code",
email = "Achim.Zeileis@uibk.ac.at"),
person("Philip", "Grosjean", role = c("ctb"),
comment = "Contributions to nlrq code", email = "phgrosjean@sciviews.org"),
person(c("Brian", "D"), "Ripley", role = c("trl","ctb"),
comment = "Initial (2001) R port from S (to my everlasting shame --
how could I have been so slow to adopt R!) and for numerous other
suggestions and useful advice", email = "ripley@stats.ox.ac.uk"))
Maintainer: Roger Koenker <rkoenker@illinois.edu>
Repository: CRAN
Depends: R (>= 2.6), stats, SparseM
Imports: methods, graphics, Matrix, MatrixModels
Suggests: tripack, akima, MASS, survival, rgl, logspline, nor1mix, Formula, zoo
License: GPL (>= 2)
URL: http://www.r-project.org
NeedsCompilation: yes
Packaged: 2016-06-07 12:45:41 UTC; roger
Author: Roger Koenker [cre, aut],
Stephen Portnoy [ctb] (Contributions to Censored QR code),
Pin Tian Ng [ctb] (Contributions to Sparse QR code),
Achim Zeileis [ctb] (Contributions to dynrq code essentially identical
to his dynlm code),
Philip Grosjean [ctb] (Contributions to nlrq code),
Brian D Ripley [trl, ctb] (Initial (2001) R port from S (to my
everlasting shame -- how could I have been so slow to adopt R!) and
for numerous other suggestions and useful advice)
Date/Publication: 2016-06-07 16:36:28
providing 
.