Fri, 27 Feb 2015

Package sidier updated to version 3.0.1 with previous version 3.0 dated 2014-11-18

Title: Substitution and Indel Distances to Infer Evolutionary Relationships
Description: Evolutionary reconstruction based on substitutions and insertion-deletion (indels) analyses in a distance-based framework.
Author: A. Jesus Muñoz Pajares
Maintainer: A.J. Muñoz-Pajares

Diff between sidier versions 3.0 dated 2014-11-18 and 3.0.1 dated 2015-02-27

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Package R.oo updated to version 1.19.0 with previous version 1.18.0 dated 2014-02-25

Title: R Object-Oriented Programming with or without References
Description: Methods and classes for object-oriented programming in R with or without references. Large effort has been made on making definition of methods as simple as possible with a minimum of maintenance for package developers. The package has been developed since 2001 and is now considered very stable. This is a cross-platform package implemented in pure R that defines standard S3 classes without any tricks.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson

Diff between R.oo versions 1.18.0 dated 2014-02-25 and 1.19.0 dated 2015-02-27

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Package pwr updated to version 1.1-2 with previous version 1.1.1 dated 2009-10-26

Title: Basic Functions for Power Analysis
Description: Power analysis functions along the lines of Cohen (1988).
Author: Stephane Champely [aut], Claus Ekstrom [ctb], Peter Dalgaard [ctb], Jeffrey Gill [ctb], Helios De Rosario [cre]
Maintainer: Helios De Rosario

Diff between pwr versions 1.1.1 dated 2009-10-26 and 1.1-2 dated 2015-02-27

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Package MAMS updated to version 0.4 with previous version 0.3 dated 2014-05-07

Title: Designing Multi-Arm Multi-Stage Studies
Description: Designing multi-arm multi-stage studies with normal endpoints and known variance.
Author: Thomas Jaki and Dominic Magirr
Maintainer: Thomas Jaki

Diff between MAMS versions 0.3 dated 2014-05-07 and 0.4 dated 2015-02-27

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Package BDgraph updated to version 2.16 with previous version 2.15 dated 2015-01-23

Title: Graph Estimation Based on Birth-Death MCMC Approach
Description: A general framework to perform Bayesian structure learning in undirected graphical models. The main target is high-dimensional data analysis wherein either continuous or discrete variables.
Author: Abdolreza Mohammadi and Ernst Wit
Maintainer: Abdolreza Mohammadi

Diff between BDgraph versions 2.15 dated 2015-01-23 and 2.16 dated 2015-02-27

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New package GenForImp with initial version 1.0
Package: GenForImp
Type: Package
Title: The Forward Imputation: A Sequential Distance-Based Approach for Imputing Missing Data
Version: 1.0
Date: 2015-02-27
Author: Nadia Solaro, Alessandro Barbiero, Giancarlo Manzi, Pier Alda Ferrari
Maintainer: Alessandro Barbiero
Description: Two methods based on the Forward Imputation approach are implemented for the imputation of quantitative missing data. One method alternates Nearest Neighbour Imputation and Principal Component Analysis (function 'ForImp.PCA'), the other uses Nearest Neighbour Imputation with the Mahalanobis distance (function 'ForImp.Mahala').
License: GPL-3
Depends: mvtnorm, sn
Packaged: 2015-02-27 17:11:22 UTC; admin
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2015-02-27 19:31:42

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Package openNLP updated to version 0.2-4 with previous version 0.2-3 dated 2014-04-19

Title: Apache OpenNLP Tools Interface
Description: An interface to the Apache OpenNLP tools (version 1.5.3). The Apache OpenNLP library is a machine learning based toolkit for the processing of natural language text written in Java. It supports the most common NLP tasks, such as tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing, and coreference resolution. See for more information.
Author: Kurt Hornik [aut, cre]
Maintainer: Kurt Hornik

Diff between openNLP versions 0.2-3 dated 2014-04-19 and 0.2-4 dated 2015-02-27

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Package MicSim updated to version 1.0.7 with previous version 1.0.6 dated 2014-07-02

Title: Performing Continuous-Time Microsimulation
Description: This entry-level toolkit allows performing generic continuous-time microsimulation for a wide range of demograhic applications.
Author: Sabine Zinn
Maintainer: Sabine Zinn

Diff between MicSim versions 1.0.6 dated 2014-07-02 and 1.0.7 dated 2015-02-27

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Package RObsDat updated to version 15.02 with previous version 14.12 dated 2014-12-29

Title: Data Mangement for Hydrology and Beyond Using the Observations Data Model
Description: Data management in hydrology and other fields is facilitated with functions to enter and modify data in a database according to the Observations Data Model (ODM) standard by CUASHI (Consortium of Universities for the Advancement of Hydrologic Science). While this data model has been developed in hydrology, it is also useful for other fields. RObsDat helps in the setup of the database within one of the free database systems MariaDB, PostgreSQL or SQLite. It imports the controlled water vocabulary from the CUASHI web service and provides a smart interface between the analyst and the database: Already existing data entries are detected and duplicates avoided. The data import function converts different data table designs to make import simple. Cleaning and modifications of data are handled with a simple version control system. Variable and location names are treated in a user friendly way, accepting and processing multiple versions. When querying data from the database, it is stored in a spacetime objects within R for subsequent processing.
Author: Dominik Reusser
Maintainer: Dominik Reusser

Diff between RObsDat versions 14.12 dated 2014-12-29 and 15.02 dated 2015-02-27

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Package lcmm updated to version 1.7.2 with previous version 1.7.1 dated 2015-02-26

Title: Extended Mixed Models Using Latent Classes and Latent Processes
Description: Estimation of various extensions of the mixed models including latent class mixed models, joint latent latent class mixed models and mixed models for curvilinear univariate or multivariate longitudinal outcomes using a maximum likelihood estimation method.
Author: Cecile Proust-Lima, Viviane Philipps, Amadou Diakite and Benoit Liquet
Maintainer: Cecile Proust-Lima

Diff between lcmm versions 1.7.1 dated 2015-02-26 and 1.7.2 dated 2015-02-27

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Package NormPsy updated to version 1.0.3 with previous version 1.0.2 dated 2014-11-27

Title: Normalisation of Psychometric Tests
Description: Functions for normalizing psychometric test scores. The normalization aims at correcting the metrological properties of the psychometric tests such as the ceiling and floor effects and the curvilinearity (unequal interval scaling). Functions to compute and plot predictions in the natural scale of the psychometric test from the estimates of a linear mixed model estimated on the normalized scores are also provided.
Author: Cecile Proust-Lima, Viviane Philipps
Maintainer: Cecile Proust-Lima

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New package hsdar with initial version 0.1
Package: hsdar
Type: Package
Title: Manage, Analyse and Simulate Hyperspectral Data in R
Version: 0.1
Date: 2015-02-10
Author: Lukas W. Lehnert [cre, aut], Hanna Meyer [ctb], Joerg Bendix [ctb]
Maintainer: Lukas W. Lehnert
Depends: R (>= 2.10.0), sp, raster, rgdal, rootSolve, signal, methods
Description: Transformation of reflectance spectra, calculation of vegetation indices and red edge parameters, spectral resampling for hyperspectral remote sensing, simulation of reflectance and transmittance using PROSPECT and PROSAIL.
License: GPL
LazyLoad: yes
BuildVignettes: yes
Copyright: see file COPYRIGHTS
URL: http://lcrs.geographie.uni-marburg.de, http://teledetection.ipgp.jussieu.fr/prosail/
Packaged: 2015-02-27 08:50:23 UTC; lehnert
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2015-02-27 12:11:24

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Package FindIt updated to version 0.5 with previous version 0.4 dated 2015-02-07

Title: Finding Heterogeneous Treatment Effects
Description: The heterogeneous treatment effect estimation procedure proposed by Imai and Ratkovic (2013). The proposed method is applicable, for example, when selecting a small number of most (or least) efficacious treatments from a large number of alternative treatments as well as when identifying subsets of the population who benefit (or are harmed by) a treatment of interest. The method adapts the Support Vector Machine classifier by placing separate LASSO constraints over the pre-treatment parameters and causal heterogeneity parameters of interest. This allows for the qualitative distinction between causal and other parameters, thereby making the variable selection suitable for the exploration of causal heterogeneity. The package also contains the function, INT, which estimates the average marginal treatment effect, the average treatment combination effect, and the average marginal treatment interaction effect proposed by Egami and Imai (2015).
Author: Naoki Egami , Marc Ratkovic , Kosuke Imai ,
Maintainer: Naoki Egami

Diff between FindIt versions 0.4 dated 2015-02-07 and 0.5 dated 2015-02-27

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Package CoxRidge updated to version 0.9.2 with previous version 0.9.1 dated 2013-06-26

Title: Cox Models with Dynamic Ridge Penalties
Description: A package for fitting Cox models with penalized ridge-type partial likelihood. The package includes functions for fitting simple Cox models with all covariates controlled by a ridge penalty. The weight of the penalty is optimised by using a REML type-algorithm. Models with time varying effects of the covariates can also be fitted. Some of the covariates may be allowed to be fixed and thus not controlled by the penalty. There are three different penalty functions, ridge, dynamic and weighted dynamic. Time varying effects can be fitted without the need of an expanded dataset.
Author: Aris Perperoglou
Maintainer: Aris Perperoglou

Diff between CoxRidge versions 0.9.1 dated 2013-06-26 and 0.9.2 dated 2015-02-27

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Package x.ent (with last version 1.0.6) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2014-11-02 1.0.6
2014-08-20 0.0.4

Permanent link
Package userfriendlyscience updated to version 0.2-0 with previous version 0.1-2 dated 2014-04-22

Title: Quantitative Analysis Made Accessible
Description: Contains a number of functions that serve two goals: first, make R more accessible to people migrating from SPSS by adding a number of functions that behave roughly like their SPSS equivalents; and second, make a number of slightly more advanced functions more user friendly to relatively novice users.
Author: Gjalt-Jorn Peters
Maintainer: Gjalt-Jorn Peters

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Package spatstat updated to version 1.41-1 with previous version 1.40-0 dated 2014-12-31

Title: Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests
Description: Comprehensive toolbox for analysing spatial data, mainly Spatial Point Patterns, including multitype/marked points and spatial covariates, in any two-dimensional spatial region. Also supports three-dimensional point patterns, space-time point patterns in any number of dimensions, and point patterns on a linear network. Contains about 2000 functions for plotting spatial data, exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. Data types include point patterns, line segment patterns, spatial windows, pixel images, tessellations, and linear networks. Exploratory methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Diggle-Cressie-Loosmore-Ford, Dao-Genton) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov) are also supported. Parametric models can be fitted to point pattern data using the functions ppm, kppm, slrm similar to glm. Types of models include Poisson, Gibbs, Cox and cluster point processes. Models may involve dependence on covariates, interpoint interaction, cluster formation and dependence on marks. Models are fitted by maximum likelihood, logistic regression, minimum contrast, and composite likelihood methods. Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise, AIC). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots.
Author: Adrian Baddeley , Rolf Turner and Ege Rubak , with substantial contributions of code by Kasper Klitgaard Berthelsen; Abdollah Jalilian; Marie-Colette van Lieshout; Tuomas Rajala; Dominic Schuhmacher; and Rasmus Waagepetersen. Additional contributions by Q.W. Ang; S. Azaele; M. Baddeley; C. Beale; M. Bell; R. Bernhardt; T. Bendtsen; A. Bevan; B. Biggerstaff; L. Bischof; R. Bivand; J.M. Blanco Moreno; F. Bonneu; J. Burgos; S. Byers; Y.M. Chang; J.B. Chen; I. Chernayavsky; Y.C. Chin; B. Christensen; J.-F. Coeurjolly; R. Corria Ainslie; M. de la Cruz; P. Dalgaard; S. Das; P.J. Diggle; P. Donnelly; I. Dryden; S. Eglen; A. El-Gabbas; O. Flores; E.D. Ford; P. Forbes; S. Frank; J. Franklin; N. Funwi-Gabga; O. Garcia; A. Gault; M. Genton; S. Ghalandarayeshi; J. Gilbey; J. Goldstick; P. Grabarnik; C. Graf; U. Hahn; A. Hardegen; M.B. Hansen; M. Hazelton; J. Heikkinen; M. Hering; M. Herrmann; K. Hornik; P. Hunziker; R. Ihaka; A. Jammalamadaka; R. John-Chandran; D. Johnson; M. Khanmohammadi; P. Kovesi; M. Kuhn; J. Laake; F. Lavancier; T. Lawrence; R.A. Lamb; J. Lee; G.P. Leser; H.T. Li; G. Limitsios; A. Lister; B. Madin; J. Marcus; K. Marchikanti; R. Mark; J. Mateu; P. McCullagh; U. Mehlig; S. Meyer; X.C. Mi; L. De Middeleer; R.K. Milne; E. Miranda; J. Moller; E. Mudrak; G.M. Nair; N. Nava; L.S. Nielsen; F. Nunes; J.R. Nyengaard; J. Oehlschlaegel; T. Onkelinx; S. O'Riordan; E. Parilov; J. Picka; N. Picard; M. Porter; S. Protsiv; A. Raftery; S. Rakshit; P. Ramon; X. Raynaud, M. Reiter; I. Renner; T.O. Richardson; B.D. Ripley; E. Rosenbaum; B. Rowlingson; J. Rudokas; J. Rudge; C. Ryan; F. Safavimanesh; A. Sarkka; K. Schladitz; S. Schutte; B.T. Scott; G.C. Shen; V. Shcherbakov; I.-M. Sintorn; Y. Song; M. Spiess; M. Stevenson; K. Stucki; M. Sumner; P. Surovy; B. Taylor; T. Thorarinsdottir; B. Turlach; T. Tvedebrink; K. Ummer; M. Uppala; A. van Burgel; T. Verbeke; M. Vihtakari; A. Villers; F. Vinatier; S. Voss; H. Wang; H. Wendrock; J. Wild; C. Witthoft; S. Wong; M. Woringer; M.E. Zamboni and A. Zeileis.
Maintainer: Adrian Baddeley

Diff between spatstat versions 1.40-0 dated 2014-12-31 and 1.41-1 dated 2015-02-27

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More information about spatstat at CRAN
Permanent link

Package RcppEigen updated to version 0.3.2.4.0 with previous version 0.3.2.3.0 dated 2014-12-23

Title: Rcpp Integration for the Eigen Templated Linear Algebra Library
Description: R and Eigen integration using Rcpp. Eigen is a C++ template library for linear algebra: matrices, vectors, numerical solvers and related algorithms. It supports dense and sparse matrices on integer, floating point and complex numbers, decompositions of such matrices, and solutions of linear systems. Its performance on many algorithms is comparable with some of the best implementations based on Lapack and level-3 BLAS. The RcppEigen package includes the header files from the Eigen C++ template library (currently version 3.2.3). Thus users do not need to install Eigen itself in order to use RcppEigen. Since version 3.1.1, Eigen is licensed under the Mozilla Public License (version 2); earlier version were licensed under the GNU LGPL version 3 or later. RcppEigen (the Rcpp bindings/bridge to Eigen) is licensed under the GNU GPL version 2 or later, as is the rest of Rcpp.
Author: Douglas Bates, Romain Francois and Dirk Eddelbuettel; the authors of Eigen for the included version of Eigen
Maintainer: Dirk Eddelbuettel

Diff between RcppEigen versions 0.3.2.3.0 dated 2014-12-23 and 0.3.2.4.0 dated 2015-02-27

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Package mads updated to version 0.1.2 with previous version 0.1.1 dated 2014-12-23

Title: Multi-Analysis Distance Sampling
Description: Performs distance sampling analyses on a number of species accounting for unidentified sightings, model uncertainty and covariate uncertainty.
Author: Laura Marshall
Maintainer: Laura Marshall

Diff between mads versions 0.1.1 dated 2014-12-23 and 0.1.2 dated 2015-02-27

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 MD5                         |   18 +++++++++---------
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More information about mads at CRAN
Permanent link

New package itsadug with initial version 0.8
Package: itsadug
Title: Interpreting Time Series and Autocorrelated Data Using GAMMs
Version: 0.8
Date: 2015-02-26
Authors@R: c( person("Jacolien", "van Rij", email="vanrij.jacolien@gmail.com", role = c("aut", "cre")),person("Martijn","Wieling", role = "aut"), person("R. Harald","Baayen", role = "aut"), person("Hedderik", "van Rijn", role = "aut"))
Description: GAMM (Generalized Additive Mixed Modeling; Lin & Zhang, 1999) as implemented in the R package mgcv (Wood, S.N., 2006; 2011) is a nonlinear regression analysis which is particularly useful for time course data such as EEG, pupil dilation, gaze data (eye tracking), and articulography recordings, but also for behavioral data such as reaction times and response data. As time course measures are sensitive to autocorrelation problems, GAMMs implements methods to reduce the autocorrelation problems. This package includes functions for the evaluation of GAMM models (e.g., model comparisons, determining regions of significance, inspection of autocorrelational structure in residuals) and interpreting of GAMMs (e.g., visualization of complex interactions, and contrasts).
License: GPL (>= 2)
LazyData: true
Depends: R (>= 2.10), mgcv (>= 1.8)
URL: http://github.com/vr-vr/itsadug
VignetteBuilder: knitr
Suggests: knitr, xtable, sp
Packaged: 2015-02-26 15:26:27 UTC; Jacolien
Author: Jacolien van Rij [aut, cre], Martijn Wieling [aut], R. Harald Baayen [aut], Hedderik van Rijn [aut]
Maintainer: Jacolien van Rij
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2015-02-27 06:57:09

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Package geostatsp updated to version 1.2.1 with previous version 1.1.9 dated 2015-01-23

Title: Geostatistical Modelling with Likelihood and Bayes
Description: Geostatistical modelling facilities using Raster and SpatialPoints objects are provided. Non-Gaussian models are fit using INLA, and Gaussian geostatistical models use Maximum Likelihood Estimation..
Author: Patrick Brown [aut, cre], Robert Hijmans [ctb]
Maintainer: Patrick Brown

Diff between geostatsp versions 1.1.9 dated 2015-01-23 and 1.2.1 dated 2015-02-27

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Package DSsim updated to version 1.0.3 with previous version 1.0.2 dated 2014-12-23

Title: Distance Sampling Simulations
Description: Performs distance sampling simulations. It repeatedly generates instances of a user defined population within a given survey region, generates realisations of a survey design (currently these must be pre-generated using Distance software) and simulates the detection process. The data are then analysed so that the results can be compared for accuracy and precision across all replications. This will allow users to select survey designs which will give them the best accuracy and precision given their expectations about population distribution. Any uncertainty in population distribution or population parameters can be included by running the different survey designs for a number of different population descriptions. An example simulation can be found in the help file for make.simulation.
Author: Laura Marshall
Maintainer: Laura Marshall

Diff between DSsim versions 1.0.2 dated 2014-12-23 and 1.0.3 dated 2015-02-27

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More information about DSsim at CRAN
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Package bio3d updated to version 2.2-1 with previous version 2.1-3 dated 2014-10-27

Title: Biological Structure Analysis
Description: Utilities to process, organize and explore protein structure, sequence and dynamics data. Features include the ability to read and write structure, sequence and dynamic trajectory data, perform sequence and structure database searches, data summaries, atom selection, alignment, superposition, rigid core identification, clustering, torsion analysis, distance matrix analysis, structure and sequence conservation analysis, normal mode analysis, principal component analysis of heterogeneous structure data, and correlation network analysis from normal mode and molecular dynamics data. In addition, various utility functions are provided to enable the statistical and graphical power of the R environment to work with biological sequence and structural data. Please refer to the URLs below for more information.
Author: Barry Grant, Xin-Qiu Yao, Lars Skjaerven, Julien Ide
Maintainer: Barry Grant

Diff between bio3d versions 2.1-3 dated 2014-10-27 and 2.2-1 dated 2015-02-27

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 270 files changed, 3382 insertions(+), 2420 deletions(-)

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2013-10-17 1.2-6

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