Thu, 25 Jun 2015

New package whoapi with initial version 0.1.0
Package: whoapi
Type: Package
Title: A 'Whoapi' API Client
Version: 0.1.0
Date: 2015-06-16
Author: Oliver Keyes
Maintainer: Oliver Keyes <ironholds@gmail.com>
Description: Retrieve data from the 'Whoapi' (https://whoapi.com) store of domain information, including a domain's geographic location, registration status and search prominence.
License: MIT + file LICENSE
LazyData: TRUE
Depends: httr
Suggests: testthat, knitr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2015-06-25 17:44:21 UTC; ironholds
Repository: CRAN
Date/Publication: 2015-06-26 00:05:30

More information about whoapi at CRAN
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New package TSMining with initial version 1.0
Package: TSMining
Type: Package
Title: Mining Univariate and Multivariate Motifs in Time-Series Data
Description: Implementations of a number of functions used to mine numeric time-series data. It covers the implementation of SAX transformation, univariate motif discovery (based on the random projection method), multivariate motif discovery (based on graph clustering), and several functions used for the ease of visualizing the motifs discovered. The details of SAX transformation can be found in J. Lin. E. Keogh, L. Wei, S. Lonardi, Experiencing SAX: A novel symbolic representation of time series, Data Mining and Knowledge Discovery 15 (2) (2007) 107-144. Details on univariate motif discovery method implemented can be found in B. Chiu, E. Keogh, S. Lonardi, Probabilistic discovery of time series motifs, ACM SIGKDD, Washington, DC, USA, 2003, pp. 493-498. Details on the multivariate motif discovery method implemented can be found in A. Vahdatpour, N. Amini, M. Sarrafzadeh, Towards unsupervised activity discovery using multi-dimensional motif detection in time series, IJCAI 2009 21st International Joint Conference on Artificial Intelligence.
Version: 1.0
Date: 2015-06-24
Author: Cheng Fan
Maintainer: Cheng Fan <raja8885@hotmail.com>
Depends: R (>= 3.0.1)
Imports: foreach, ggplot2, plyr, reshape2
Suggests: knitr
VignetteBuilder: knitr
LazyData: true
License: GPL-3
Packaged: 2015-06-25 13:09:35 UTC; Fan
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2015-06-26 00:02:41

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Package sorvi updated to version 0.7.26 with previous version 0.7.20 dated 2015-02-17

Title: Finnish Open Government Data Toolkit
Description: Algorithms for Finnish open government data.
Author: Leo Lahti, Juuso Parkkinen, Joona Lehtomaki, Juuso Haapanen, Jussi Paananen, Einari Happonen
Maintainer: Leo Lahti <louhos@googlegroups.com>

Diff between sorvi versions 0.7.20 dated 2015-02-17 and 0.7.26 dated 2015-06-25

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More information about sorvi at CRAN
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Package seqMeta updated to version 1.6.0 with previous version 1.5 dated 2014-10-28

Title: Meta-Analysis of Region-Based Tests of Rare DNA Variants
Description: Computes necessary information to meta analyze region-based tests for rare genetic variants (e.g. SKAT, T1) in individual studies, and performs meta analysis.
Author: Arie Voorman, Jennifer Brody, Han Chen, Thomas Lumley
Maintainer: Brian Davis <Brian.Davis281@gmail.com>

Diff between seqMeta versions 1.5 dated 2014-10-28 and 1.6.0 dated 2015-06-25

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Package PPtreeViz updated to version 1.1.0 with previous version 1.0.3 dated 2015-05-15

Title: Projection Pursuit Classification Tree Visualization
Description: Tools for exploring projection pursuit classification tree using various projection pursuit indices.
Author: Eun-Kyung Lee
Maintainer: Eun-Kyung Lee <lee.eunk@gmail.com>

Diff between PPtreeViz versions 1.0.3 dated 2015-05-15 and 1.1.0 dated 2015-06-25

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Package MixGHD updated to version 1.7 with previous version 1.6 dated 2015-05-26

Title: Model Based Clustering, Classification and Discriminant Analysis Using the Mixture of Generalized Hyperbolic Distributions
Description: Carries out model-based clustering, classification and discriminant analysis using five different models. The models are all based on the generalized hyperbolic distribution.The first model 'MGHD' is the classical mixture of generalized hyperbolic distributions. The 'MGHFA' is the mixture of generalized hyperbolic factor analyzers for high dimensional data sets. The 'MSGHD', mixture of multiple scaled generalized hyperbolic distributions. The 'cMSGHD' is a 'MSGHD' with convex contour plots. The 'MCGHD', mixture of coalesced generalized hyperbolic distributions is a new more flexible model.
Author: Cristina Tortora, Ryan P. Browne, Brian C. Franczak and Paul D. McNicholas.
Maintainer: Cristina Tortora <ctortora@math.mcmaster.ca>

Diff between MixGHD versions 1.6 dated 2015-05-26 and 1.7 dated 2015-06-25

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Package GUTS updated to version 1.0.0 with previous version 0.9.3 dated 2015-05-15

Title: Fast Calculation of the Likelihood of a Stochastic Survival Model
Description: Given exposure and survival time series as well as parameter values, GUTS allows for the fast calculation of the survival probabilities as well as the logarithm of the corresponding likelihood.
Author: Carlo Albert <carlo.albert@eawag.ch> and Sören Vogel <soeren.vogel@posteo.ch>
Maintainer: Sören Vogel <soeren.vogel@posteo.ch>

Diff between GUTS versions 0.9.3 dated 2015-05-15 and 1.0.0 dated 2015-06-25

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New package Bagidis with initial version 1.0
Package: Bagidis
Type: Package
Title: BAses GIving DIStances
Version: 1.0
Date: 2015-06-24
Author: Catherine Timmermans
Maintainer: Catherine Timmermans <catherine.timmermans@uclouvain.be>
Description: This is the companion package of a PhD thesis entitled "Bases Giving Distances. A new paradigm for investigating functional data with applications for spectroscopy" by Timmermans (2012). See references for details and related publications. The core of the BAGIDIS methodology is a functional wavelet based semi-distance that has been introduced by Timmermans and von Sachs (2010, 2015) and Timmermans, Delsol and von Sachs (2013). This semi-distance allows for comparing curves with sharp local patterns that might not be well aligned from one curve to another. It is data-driven and highly adaptive to the curves being studied. Its main originality is its ability to consider simultaneously horizontal and vertical variations of patterns, which proofs highly useful when used together with clustering algorithms or visualization method. BAGIDIS is an acronym for BAsis GIving DIStances. The extension of BAGIDIS to image data relies on the same principles and has been described in Timmermans and Fryzlewicz (2012), Fryzlewicz and Timmermans (2015).
License: GPL
Depends: abind
Packaged: 2015-06-25 10:47:43 UTC; Catherine
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2015-06-26 00:36:18

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Package covr updated to version 1.2.0 with previous version 1.0.0 dated 2015-05-20

Title: Test Coverage for Packages
Description: Track and report code coverage for your package and (optionally) upload the results to a coverage service like Codecov (http://codecov.io) or Coveralls (http://coveralls.io). Code coverage is a measure of the amount of code being exercised by the tests. It is an indirect measure of test quality. This package is compatible with any testing methodology or framework and tracks coverage of both R code and compiled C/C++/Fortran code.
Author: Jim Hester [aut, cre]
Maintainer: Jim Hester <james.f.hester@gmail.com>

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New package translation.ko with initial version 0.0.1.3
Package: translation.ko
Title: R Manuals Literally Translated in Korean
Version: 0.0.1.3
Authors@R: person("Chel Hee", "Lee", email = "chl948@mail.usask.ca", role = c("aut", "cre"))
Description: R version 2.1.0 and later support Korean translations of program messages. The continuous efforts have been made by <http://developer.r-project.org/TranslationTeams.html> The R Documentation files are licensed under the General Public License, version 2 or 3. This means that the pilot project to translate them into Korean has permission to reproduce them and translate them. This work is done with GNU 'gettext' utilities. The portable object template is updated a weekly basis or whenever changes are necessary. Comments and corrections via email to the maintainer is of course most welcome. In order to voluntarily participate in or offer your help with this translation, please contact the maintainer. To check the change and progress of Korean translation, please visit <http://www.openstatistics.net>.
Maintainer: Chel Hee Lee <chl948@mail.usask.ca>
Depends: R (>= 3.2.1)
License: GPL (>= 2)
LazyData: true
URL: http://www.openstatistics.net
BugReports: chl948@mail.usask.ca
NeedsCompilation: no
Packaged: 2015-06-25 01:40:23 UTC; chel
Author: Chel Hee Lee [aut, cre]
Repository: CRAN
Date/Publication: 2015-06-25 12:15:03

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Package Rhpc updated to version 0.15-176 with previous version 0.15-147 dated 2015-05-28

Title: Permits *apply() Style Dispatch for 'HPC'
Description: Function of apply style using 'MPI' provides better 'HPC' environment on R. and this package supports long vector, can deal with slightly big data.
Author: Junji NAKANO <nakanoj@ism.ac.jp> and Ei-ji Nakama<nakama@com-one.com>
Maintainer: Ei-ji Nakama <nakama@com-one.com>

Diff between Rhpc versions 0.15-147 dated 2015-05-28 and 0.15-176 dated 2015-06-25

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Package httr updated to version 1.0.0 with previous version 0.6.1 dated 2015-01-01

Title: Tools for Working with URLs and HTTP
Description: Useful tools for working with HTTP organised by HTTP verbs (GET(), POST(), etc). Configuration functions make it easy to control additional request components (authenticate(), add_headers() and so on).
Author: Hadley Wickham [aut, cre], RStudio [cph]
Maintainer: Hadley Wickham <hadley@rstudio.com>

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Package earth updated to version 4.4.2 with previous version 4.4.1 dated 2015-06-17

Title: Multivariate Adaptive Regression Splines
Description: Build regression models using the techniques in Friedman's papers "Fast MARS" and "Multivariate Adaptive Regression Splines". (The term "MARS" is trademarked and thus not used in the name of the package.)
Author: Stephen Milborrow. Derived from mda:mars by Trevor Hastie and Rob Tibshirani. Uses Alan Miller's Fortran utilities with Thomas Lumley's leaps wrapper.
Maintainer: Stephen Milborrow <milbo@sonic.net>

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Package snowFT updated to version 1.4-0 with previous version 1.3-0 dated 2012-12-13

Title: Fault Tolerant Simple Network of Workstations
Description: Extension of the snow package supporting fault tolerant and reproducible applications, as well as supporting easy-to-use parallel programming - only one function is needed.
Author: Hana Sevcikova, A. J. Rossini
Maintainer: Hana Sevcikova <hanas@uw.edu>

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Package learnstats updated to version 0.1.1 with previous version 0.1.0 dated 2015-05-02

Title: An Interactive Environment for Learning Statistics
Description: Allows students to use R as an interactive educational environment for statistical concepts, ranging from p-values to confidence intervals to stability in time series.
Author: Daniel Walter [aut, cre]
Maintainer: Daniel Walter <dswalter@gmail.com>

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Package flam updated to version 2.0 with previous version 1.0 dated 2014-10-13

Title: Fits Piecewise Constant Models with Data-Adaptive Knots
Description: Implements the fused lasso additive model as proposed in Petersen, A., Witten, D., and Simon, N. (2014). Fused Lasso Additive Model. arXiv preprint arXiv:1409.5391.
Author: Ashley Petersen
Maintainer: Ashley Petersen <ajpete@uw.edu>

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New package XMRF with initial version 1.0
Package: XMRF
Type: Package
Title: Markov Random Fields for High-Throughput Genetics Data
Version: 1.0
Date: 2015-06-12
Author: Ying-Wooi Wan, Genevera I. Allen, Yulia Baker, Eunho Yang, Pradeep Ravikumar, Zhandong Liu
Maintainer: Ying-Wooi Wan <yingwoow@bcm.edu>
Depends: R (>= 3.0.2)
Imports: igraph, glmnet, MASS, snowfall, parallel, Matrix
Description: Fit Markov Networks to a wide range of high-throughput genomics data.
License: GPL-2
URL: http://www.liuzlab.org/XMRF/
LazyLoad: true
Packaged: 2015-06-24 19:28:43 UTC; wooi
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2015-06-25 07:07:40

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Package adwave updated to version 1.1 with previous version 1.0 dated 2014-10-10

Title: Wavelet Analysis of Genomic Data from Admixed Populations
Description: Implements wavelet-based approaches for describing population admixture. Principal Components Analysis (PCA) is used to define the population structure and produce a localized admixture signal for each individual. Wavelet summaries of the PCA output describe variation present in the data and can be related to population-level demographic processes. For more details, see Sanderson et al. (2015).
Author: Jean Sanderson
Maintainer: Murray Cox <m.p.cox@massey.ac.nz>

Diff between adwave versions 1.0 dated 2014-10-10 and 1.1 dated 2015-06-25

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