Sun, 25 Jan 2015

Package tsoutliers updated to version 0.5 with previous version 0.4 dated 2014-06-27

Title: Detection of Outliers in Time Series
Description: Detection of outliers in time series following the Chen and Liu (1993) procedure. Innovative outliers, additive outliers, level shifts, temporary changes and seasonal level shifts are considered.
Author: Javier López-de-Lacalle
Maintainer: Javier López-de-Lacalle

Diff between tsoutliers versions 0.4 dated 2014-06-27 and 0.5 dated 2015-01-25

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Package spate updated to version 1.4 with previous version 1.3 dated 2013-12-29

Title: Spatio-Temporal Modeling of Large Data Using a Spectral SPDE Approach
Description: This package provides functionality for spatio-temporal modeling of large data sets. A Gaussian process in space and time is defined through a stochastic partial differential equation (SPDE). The SPDE is solved in the spectral space, and after discretizing in time and space, a linear Gaussian state space model is obtained. When doing inference, the main computational difficulty consists in evaluating the likelihood and in sampling from the full conditional of the spectral coefficients, or equivalently, the latent space-time process. In comparison to the traditional approach of using a spatio-temporal covariance function, the spectral SPDE approach is computationally advantageous. This package aims at providing tools for two different modeling approaches. First, the SPDE based spatio-temporal model can be used as a component in a customized hierarchical Bayesian model (HBM). The functions of the package then provide parameterizations of the process part of the model as well as computationally efficient algorithms needed for doing inference with the HBM. Alternatively, the adaptive MCMC algorithm implemented in the package can be used as an algorithm for doing inference without any additional modeling. The MCMC algorithm supports data that follow a Gaussian or a censored distribution with point mass at zero. Covariates can be included in the model through a regression term.
Author: Fabio Sigrist, Hans R. Kuensch, Werner A. Stahel
Maintainer: Fabio Sigrist

Diff between spate versions 1.3 dated 2013-12-29 and 1.4 dated 2015-01-25

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New package reproducer with initial version 0.1.2
Package: reproducer
Title: Reproduce Statistical Analyses and Meta-Analyses
Version: 0.1.2
Date: 2015-01-25
Authors@R: c( person("Lech", "Madeyski", email = "lech.madeyski@gmail.com", role = c("cre", "aut")), person("Marian", "Jureczko", email = "marian.jureczko@gmail.com", role = "ctb", comment = "Data contributor"))
Maintainer: Lech Madeyski
Description: The reproducer R package includes data analysis functions and data sets (e.g., related to software defect prediction) to streamline reproducible research in software engineering.
Depends: R (>= 3.1.1)
License: CC BY 4.0
LazyData: true
URL: http://madeyski.e-informatyka.pl/reproducible-research/
Imports: openxlsx (>= 2.2.1), ggplot2 (>= 1.0.0), gridExtra(>= 0.9.1)
NeedsCompilation: no
Packaged: 2015-01-25 16:16:28 UTC; lma
Author: Lech Madeyski [cre, aut], Marian Jureczko [ctb] (Data contributor)
Repository: CRAN
Date/Publication: 2015-01-25 21:30:59

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Package mirtCAT updated to version 0.4.2 with previous version 0.4 dated 2015-01-22

Title: Computerized Adaptive Testing with Multidimensional Item Response Theory
Description: Provides tools to generate an HTML interface for creating adaptive and non-adaptive educational and psychological tests using the shiny package. Suitable for applying unidimensional and multidimensional computerized adaptive tests using item response theory methodology and for creating simple questionnaires forms to collect response data directly in R.
Author: Phil Chalmers [aut, cre, cph]
Maintainer: Phil Chalmers

Diff between mirtCAT versions 0.4 dated 2015-01-22 and 0.4.2 dated 2015-01-25

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Package RWekajars updated to version 3.7.12-1 with previous version 3.7.11-1 dated 2014-04-26

Title: R/Weka interface jars
Description: External jars required for package RWeka.
Author: Kurt Hornik [aut, cre], University of Waikato [ctb, cph] (Weka Java library)
Maintainer: Kurt Hornik

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Package RWeka updated to version 0.4-24 with previous version 0.4-23 dated 2014-04-26

Title: R/Weka interface
Description: An R interface to Weka (Version 3.7.12). Weka is a collection of machine learning algorithms for data mining tasks written in Java, containing tools for data pre-processing, classification, regression, clustering, association rules, and visualization. Package RWeka contains the interface code, the Weka jar is in a separate package RWekajars. For more information on Weka see .
Author: Kurt Hornik [aut, cre], Christian Buchta [ctb], Torsten Hothorn [ctb], Alexandros Karatzoglou [ctb], David Meyer [ctb], Achim Zeileis [ctb]
Maintainer: Kurt Hornik

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Package RcppArmadillo updated to version 0.4.600.4.0 with previous version 0.4.600.0 dated 2014-12-27

Title: Rcpp Integration for the Armadillo Templated Linear Algebra Library
Description: R and Armadillo integration using Rcpp Armadillo is a templated C++ linear algebra library (by Conrad Sanderson) that aims towards a good balance between speed and ease of use. Integer, floating point and complex numbers are supported, as well as a subset of trigonometric and statistics functions. Various matrix decompositions are provided through optional integration with LAPACK and ATLAS libraries. The RcppArmadillo package includes the header files from the templated Armadillo library. Thus users do not need to install Armadillo itself in order to use RcppArmadillo. Armadillo is licensed under the MPL 2.0, while RcppArmadillo (the Rcpp bindings/bridge to Armadillo) is licensed under the GNU GPL version 2 or later, as is the rest of Rcpp.
Author: Romain Francois, Dirk Eddelbuettel and Doug Bates
Maintainer: Dirk Eddelbuettel

Diff between RcppArmadillo versions 0.4.600.0 dated 2014-12-27 and 0.4.600.4.0 dated 2015-01-25

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Package XLConnect updated to version 0.2-10 with previous version 0.2-9 dated 2014-08-14

Title: Excel Connector for R
Description: Provides comprehensive functionality to read, write and format Excel data.
Author: Mirai Solutions GmbH [aut], Martin Studer [cre], The Apache Software Foundation [ctb, cph] (Apache POI, Apache Commons Codec), Stephen Colebourne [ctb, cph] (Joda-Time Java library)
Maintainer: Martin Studer

Diff between XLConnect versions 0.2-9 dated 2014-08-14 and 0.2-10 dated 2015-01-25

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Package snht updated to version 1.0.1 with previous version 1.0 dated 2014-11-03

Title: Standard Normal Homogeneity Test
Description: Robust and non-robust SNHT tests for changepoint detection.
Author: Josh Browning
Maintainer: Josh Browning

Diff between snht versions 1.0 dated 2014-11-03 and 1.0.1 dated 2015-01-25

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Package RegressionFactory updated to version 0.7.1 with previous version 0.7 dated 2014-12-01

Title: Expander Functions for Generating Full Gradient and Hessian from Single- and Multi-Slot Base Distributions
Description: The expander functions rely on the mathematics developed for the Hessian-definiteness invariance theorem for linear projection transformations of variables, described in authors' paper, to generate the full, high-dimensional gradient and Hessian from the lower-dimensional derivative objects. This greatly relieves the computational burden of generating the regression-function derivatives, which in turn can be fed into any optimization routine that utilizes such derivatives. The theorem guarantees that Hessian definiteness is preserved, meaning that reasoning about this property can be performed in the low-dimensional space of the base distribution. This is often a much easier task than its equivalent in the full, high-dimensional space. Definiteness of Hessian can be useful in selecting optimization/sampling algorithms such as Newton-Raphson optimization or its sampling equivalent, the Stochastic Newton Sampler. Finally, in addition to being a computational tool, the regression expansion framework is of conceptual value by offering new opportunities to generate novel regression problems.
Author: Alireza S. Mahani, Mansour T.A. Sharabiani
Maintainer: Alireza S. Mahani

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