Thu, 04 Jun 2015

Package RMark updated to version 2.1.13 with previous version 2.1.12 dated 2015-03-15

Title: R Code for Mark Analysis
Description: An interface to the software package MARK that constructs input files for MARK and extracts the output. MARK was developed by Gary White and is freely available at (http://www.phidot.org/software/mark/downloads/) but is not open source.
Author: Jeff Laake <jeff.laake@noaa.gov> with code contributions from Eldar Rakhimberdiev, Ben Augustine and Daniel Turek, and example data and analysis from Bret Collier, Jay Rotella, David Pavlacky, and Andrew Paul.
Maintainer: Jeff Laake <Jeff.Laake@noaa.gov>

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Package progress updated to version 1.0.2 with previous version 1.0.1 dated 2015-05-30

Title: Terminal Progress Bars
Description: Terminal progress bars. They are configurable, may include percentage, elapsed time, and/or the estimated completion time. They work in the command line, in Emacs, R Studio, Windows Rgui and Mac OSX R.app. The package also provides a C++ API, that works with or without Rcpp.
Author: Gabor Csardi [aut, cre]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

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New package RobustEM with initial version 1.0
Package: RobustEM
Type: Package
Title: Robust Mixture Modeling Fitted via Spatial-EM Algorithm for Model-Based Clustering and Outlier Detection
Version: 1.0
Date: 2015-06-04
Author: Aishat Aloba, Kai Yu, Xin Dang, Yixin Chen, and Henry Bart Jr.
Maintainer: Aishat Aloba <adetokaloba@gmail.com>
Description: The Spatial-EM is a new robust EM algorithm for the finite mixture learning procedures. The algorithm utilizes median- based location and rank-based scatter estimators to replace sample mean and sample covariance matrix in each M step, hence enhancing stability and robustness of the algorithm. To understand more about this algorithm, read the article ''Yu, K., Dang, X., Bart Jr, H. and Chen, Y. (2015). Robust Model- based Learning via Spatial-EM Algorithm. IEEE Transactions on Knowledge and Data Engineering, 27(6), 1670-1682. doi:10.1109/TKDE.2014.2373355''.
License: GPL-3
Depends: R (>= 2.15.0)
Imports: mvtnorm,e1071,ggplot2,ellipse, doParallel,grid, foreach
NeedsCompilation: yes
Packaged: 2015-06-04 19:08:46 UTC; Aishat
Repository: CRAN
Date/Publication: 2015-06-05 01:11:35

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Package MuMIn updated to version 1.14.0 with previous version 1.13.4 dated 2015-02-25

Title: Multi-Model Inference
Description: Model selection and model averaging based on information criteria (AICc and alike).
Author: Kamil Bartoń
Maintainer: Kamil Bartoń <kamil.barton@go2.pl>

Diff between MuMIn versions 1.13.4 dated 2015-02-25 and 1.14.0 dated 2015-06-04

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Package bpcp updated to version 1.2.5 with previous version 1.2.4 dated 2014-11-21

Title: Beta Product Confidence Procedure for Right Censored Data
Description: Calculates nonparametric pointwise confidence intervals for the survival distribution for right censored data. Has two-sample tests for dissimilarity (e.g., difference, ratio or odds ratio) in survival at a fixed time. Especially important for small sample sizes or heavily censored data. Includes mid-p options.
Author: Michael P. Fay
Maintainer: Michael P. Fay <mfay@niaid.nih.gov>

Diff between bpcp versions 1.2.4 dated 2014-11-21 and 1.2.5 dated 2015-06-04

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Package ssym updated to version 1.5.3 with previous version 1.5.2 dated 2015-01-08

Title: Fitting Semi-Parametric log-Symmetric Regression Models
Description: Set of tools to fit a semi-parametric regression model suitable for analysis of data sets in which the response variable is continuous, strictly positive, asymmetric and possibly, censored. Under this setup, both the median and the skewness of the response variable distribution are explicitly modeled by using semi-parametric functions, whose non-parametric components may be approximated by natural cubic splines or P-splines. Supported distributions for the model error include log-normal, log-Student-t, log-power-exponential, log-hyperbolic, log-contaminated-normal, log-slash, Birnbaum-Saunders and Birnbaum-Saunders-t distributions.
Author: Luis Hernando Vanegas <hvanegasp@gmail.com> and Gilberto A. Paula
Maintainer: Luis Hernando Vanegas <hvanegasp@gmail.com>

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Package preseqR updated to version 1.2.1 with previous version 1.1.1 dated 2015-04-01

Title: Predicting Species Accumulation Curves
Description: Estimating species accumulation curves by rational function approximations to the non-parametric empirical Bayes estimator and by the zero-truncated Negative Binomial distribution.
Author: Chao Deng, Timothy Daley and Andrew D. Smith
Maintainer: Chao Deng <chaodeng@usc.edu>

Diff between preseqR versions 1.1.1 dated 2015-04-01 and 1.2.1 dated 2015-06-04

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Package gap updated to version 1.1-14 with previous version 1.1-13 dated 2015-06-03

Title: Genetic Analysis Package
Description: It is designed as an integrated package for genetic data analysis of both population and family data. Currently, it contains functions for sample size calculations of both population-based and family-based designs, probability of familial disease aggregation, kinship calculation, statistics in linkage analysis, and association analysis involving genetic markers including haplotype analysis with or without environmental covariates.
Author: Jing Hua Zhao and colleagues with inputs from Kurt Hornik and Brian Ripley
Maintainer: Jing Hua Zhao <jinghua.zhao@mrc-epid.cam.ac.uk>

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New package odds.converter with initial version 1.1
Package: odds.converter
Type: Package
Title: Betting Odds Conversion
Version: 1.1
Date: 2015-05-31
Author: Marco Blume
Maintainer: Marco Blume <marco.blume@pinnaclesports.com>
Description: Conversion between the most common odds types for sports betting. Hong Kong odds, US odds, Decimal odds, Indonesian odds, Malaysian odds, and raw Probability are covered in this package.
License: GPL-2
NeedsCompilation: no
Packaged: 2015-06-04 15:15:08 UTC; administrator
Repository: CRAN
Date/Publication: 2015-06-04 18:15:53

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Package kml updated to version 2.3.1 with previous version 2.3 dated 2015-05-20

Title: K-Means for Longitudinal Data
Description: An implementation of k-means specifically design to cluster longitudinal data. It provides facilities to deal with missing value, compute several quality criterion (Calinski and Harabatz, Ray and Turie, Davies and Bouldin, BIC, ...) and propose a graphical interface for choosing the 'best' number of clusters.
Author: Christophe Genolini [cre, aut], Bruno Falissard [ctb]
Maintainer: Christophe Genolini <christophe.genolini@u-paris10.fr>

Diff between kml versions 2.3 dated 2015-05-20 and 2.3.1 dated 2015-06-04

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New package kineticF with initial version 1.0
Package: kineticF
Type: Package
Title: Framework for the Analysis of Kinetic Visual Field Data
Version: 1.0
Depends: R(> 3.1.0)
Imports: circular, lqmm, splancs, sp, plotrix, MASS
Date: 2015-06-04
Author: Dipesh E Patel & Mario Cortina-Borja
Maintainer: Dipesh E Patel <dipesh_patel@ucl.ac.uk>
Description: Data cleaning, processing, visualisation and analysis for manual (Goldmann) and automated (Octopus 900) kinetic visual field data.
License: GPL (>= 2)
NeedsCompilation: no
LazyData: true
Packaged: 2015-06-04 14:03:07 UTC; sejjdp1
Repository: CRAN
Date/Publication: 2015-06-04 17:32:34

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Package clustMD updated to version 1.1 with previous version 1.0 dated 2014-06-12

Title: Model Based Clustering for Mixed Data
Description: Model-based clustering of mixed data (i.e. data which consist of continuous, binary, ordinal or nominal variables) using a parsimonious mixture of latent Gaussian variable models.
Author: Damien McParland
Maintainer: Damien McParland <damien.mcparland@ucd.ie>

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Package PowerTOST updated to version 1.2-07 with previous version 1.2-06 dated 2015-01-23

Title: Power and Sample Size Based on Two One-Sided t-Tests (TOST) for (Bio)Equivalence Studies
Description: Contains functions to calculate power and sample size for various study designs used for bioequivalence studies. See function known.designs() for study designs covered. Moreover the package contains functions for power and sample size based on 'expected' power in case of uncertain (estimated) variability. ----- Added are functions for the power and sample size for the ratio of two means with normally distributed data on the original scale (based on Fieller's confidence ('fiducial') interval). ----- Contains further functions for power and sample size calculations based on non-inferiority t-test. This is not a TOST procedure but eventually useful if the question of 'non-superiority' must be evaluated. The power and sample size calculations based on non-inferiority test may also performed via 'expected' power in case of uncertain (estimated) variability. ----- Contains functions power.scABEL() and sampleN.scABEL() to calculate power and sample size for the BE decision via scaled (widened) BE acceptance limits based on simulations. Contains further functions power.RSABE() and sampleN.RSABE() to calculate power and sample size for the BE decision via reference scaled ABE criterion according to the FDA procedure based on simulations. Contains further functions power.NTIDFDA() and sampleN.NTIDFDA() to calculate power and sample size for the BE decision via the FDA procedure for NTID's based on simulations. ----- Contains functions for power analysis of a sample size plan for ABE (pa.ABE()), scaled ABE (pa.scABE()) and scaled ABE for NTID's (pa.NTIDFDA()) analysing power if deviating from assumptions of the plan. ----- Contains further functions for power calculations / samplesize estimation for dose proportionality studies using the Power model.
Author: Detlew Labes [aut, cre], Helmut Schuetz [aut], Benjamin Lang [ctb]
Maintainer: Detlew Labes <DetlewLabes@gmx.de>

Diff between PowerTOST versions 1.2-06 dated 2015-01-23 and 1.2-07 dated 2015-06-04

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Package clusterCrit updated to version 1.2.5 with previous version 1.2.4 dated 2014-12-11

Title: Clustering Indices
Description: Compute clustering validation indices.
Author: Bernard Desgraupes (University of Paris Ouest - Lab Modal'X)
Maintainer: Bernard Desgraupes <bernard.desgraupes@u-paris10.fr>

Diff between clusterCrit versions 1.2.4 dated 2014-12-11 and 1.2.5 dated 2015-06-04

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Package cem updated to version 1.1.16 with previous version 1.1.10 dated 2014-03-25

Title: Coarsened Exact Matching
Description: Implementation of the Coarsened Exact Matching algorithm.
Author: Iacus, Stefano M., King, Gary, Porro, Giuseppe
Maintainer: Stefano M. Iacus <stefano.iacus@unimi.it>

Diff between cem versions 1.1.10 dated 2014-03-25 and 1.1.16 dated 2015-06-04

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New package zetadiv with initial version 0.1
Package: zetadiv
Title: Functions to Compute Compositional Turnover Using Zeta Diversity
Version: 0.1
Author: Guillaume Latombe, Melodie A. McGeoch, Cang Hui
Maintainer: Guillaume Latombe <guillaume.latombe@monash.edu>
Description: Functions to compute compositional turnover using zeta-diversity, the number of species shared by multiple assemblages. The package includes a Zeta.order() function to compute zeta-diversity for a specific number of assemblages, and a Zeta.decline() function to compute zeta-diversity for a range of numbers of assemblages. It also includes additional functions to explain how zeta-diversity varies with distance and with differences of environmental variables between assemblages, using linear regressions and generalized additive models.
Depends: R (>= 3.0.0)
License: GPL-3
Imports: car, mgcv, vegan
LazyData: true
Packaged: 2015-06-04 06:29:34 UTC; lguillau
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2015-06-04 12:01:48

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Package sglasso updated to version 1.2.1 with previous version 1.2 dated 2015-05-04

Title: Lasso Method for RCON(V,E) Models
Description: RCON(V, E) models (Højsgaard, et al., 2008) are a kind of restriction of the Gaussian Graphical Models defined by a set of equality constraints on the entries of the concentration matrix. 'sglasso' package implements the structured graphical lasso (sglasso) estimator proposed in Abbruzzo et al. (2014) for the weighted l1-penalized RCON(V, E) model. Two cyclic coordinate algorithms are implemented to compute the sglasso estimator, i.e. a cyclic coordinate minimization (CCM) and a cyclic coordinate descent (CCD) algorithm.
Author: Luigi Augugliaro
Maintainer: Luigi Augugliaro <luigi.augugliaro@unipa.it>

Diff between sglasso versions 1.2 dated 2015-05-04 and 1.2.1 dated 2015-06-04

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Package SAENET updated to version 1.1 with previous version 1.0 dated 2015-02-03

Title: A Stacked Autoencoder Implementation with Interface to 'neuralnet'
Description: An implementation of a stacked sparse autoencoder for dimension reduction of features and pre-training of feed-forward neural networks with the 'neuralnet' package is contained within this package. The package also includes a predict function for the stacked autoencoder object to generate the compressed representation of new data if required. For the purposes of this package, 'stacked' is defined in line with http://ufldl.stanford.edu/wiki/index.php/Stacked_Autoencoders . The underlying sparse autoencoder is defined in the documentation of 'autoencoder'.
Author: Stephen Hogg [aut, cre], Eugene Dubossarsky [aut]
Maintainer: Stephen Hogg <saenet.r@gmail.com>

Diff between SAENET versions 1.0 dated 2015-02-03 and 1.1 dated 2015-06-04

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New package RevEcoR with initial version 0.99.1
Package: RevEcoR
Type: Package
Title: Reverse Ecology Analysis on Microbiome
Version: 0.99.1
Date: 2015-5-13
Author: Yang Cao, Fei Li
Maintainer: Yang Cao <yiluheihei@gmail.com>
Description: An implementation of the reverse ecology framework. Reverse ecology refers to the use of genomics to study ecology with no a priori assumptions about the organism(s) under consideration, linking organisms to their environment. It allows researchers to reconstruct the metabolic networks and study the ecology of poorly characterized microbial species from their genomic information, and has substantial potential for microbial community ecological analysis.
Depends: R (>= 2.14)
Imports: Biobase, Matrix, igraph, XML, stringr, KEGGREST, magrittr, mmnet, gtools, plyr
Suggests: knitr, methods
VignetteBuilder: knitr
License: GPL (>= 2)
LazyData: yes
NeedsCompilation: no
Packaged: 2015-06-04 07:45:51 UTC; yang
Repository: CRAN
Date/Publication: 2015-06-04 11:48:50

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Package icenReg updated to version 1.2.4 with previous version 1.2.3 dated 2015-06-03

Title: Regression Models for Interval Censored Data
Description: Regression models for interval censored data. Currently supports a semi-parametric Cox-PH and proportional odds models and fully parametric Cox-PH and proportional odds models. Also includes functions for easy visual diagnostics of model fits.
Author: Clifford Anderson-Bergman
Maintainer: Clifford Anderson-Bergman <pistacliffcho@gmail.com>

Diff between icenReg versions 1.2.3 dated 2015-06-03 and 1.2.4 dated 2015-06-04

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Package cowplot updated to version 0.3.1 with previous version 0.3.0 dated 2015-06-03

Title: Streamlined Plot Theme and Plot Annotations for 'ggplot2'
Description: Some helpful extensions and modifications to the 'ggplot2' library. In particular, this package makes it easy to combine multiple 'ggplot2' plots into one and label them with letters, e.g. A, B, C, etc., as is often required for scientific publications. The package also provides a streamlined and clean theme that is used in the Wilke lab, hence the package name, which stands for Claus O. Wilke's plot library.
Author: Claus O. Wilke [aut, cre], Hadley Wickham [cph]
Maintainer: Claus O. Wilke <wilke@austin.utexas.edu>

Diff between cowplot versions 0.3.0 dated 2015-06-03 and 0.3.1 dated 2015-06-04

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Package aSPU updated to version 1.35 with previous version 1.33 dated 2015-05-27

Title: Adaptive Sum of Powered Score Test
Description: R codes for the (adaptive) Sum of Powered Score ('SPU' and 'aSPU') tests, inverse variance weighted Sum of Powered score ('SPUw' and 'aSPUw') tests and gene-based and some pathway based association tests (Pathway based Sum of Powered Score tests ('SPUpath') and adaptive 'SPUpath' ('aSPUpath') test, Gene-based Association Test that uses an extended Simes procedure ('GATES'), Hybrid Set-based Test ('HYST'), extended version of 'GATES' test for pathway-based association testing ('Gates-Simes'). ). The tests can be used with genetic and other data sets with covariates. The response variable is binary or quantitative.
Author: Il-Youp Kwak and others (See Author(s) in each function manual)
Maintainer: Il-Youp Kwak <ikwak@umn.edu>

Diff between aSPU versions 1.33 dated 2015-05-27 and 1.35 dated 2015-06-04

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