Sun, 24 May 2015

Package stream updated to version 1.1-4 with previous version 1.1-3 dated 2015-05-23

Title: Infrastructure for Data Stream Mining
Description: A framework for data stream modeling and associated data mining tasks such as clustering and classification. The development of this package was supported in part by NSF IIS-0948893 and NIH R21HG005912.
Author: Michael Hahsler [aut, cre, cph], Matthew Bolanos [aut, cph], John Forrest [aut, cph]
Maintainer: Michael Hahsler <mhahsler@lyle.smu.edu>

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Package wsrf updated to version 1.5.0 with previous version 1.4.0 dated 2014-05-30

Title: Weighted Subspace Random Forest for Classification
Description: A parallel implementation of Weighted Subspace Random Forest. The Weighted Subspace Random Forest algorithm was proposed in the International Journal of Data Warehousing and Mining, 8(2):44-63, 2012, proposed by Baoxun Xu, Joshua Zhexue Huang, Graham Williams, Qiang Wang, and Yunming Ye. The algorithm can classify very high-dimensional data with random forests built using small subspaces. A novel variable weighting method is used for variable subspace selection in place of the traditional random variable sampling.This new approach is particularly useful in building models from high-dimensional data.
Author: Qinghan Meng [aut], He Zhao [aut, cre], Graham Williams [aut], Junchao Lv [ctb], Baoxun Xu [aut]
Maintainer: He Zhao <Simon.Yansen.Zhao@gmail.com>

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Package HiClimR updated to version 1.2.1 with previous version 1.2.0 dated 2015-03-27

Title: Hierarchical Climate Regionalization
Description: A tool for Hierarchical Climate Regionalization applicable to any correlation-based clustering. It adds several features and a new clustering method (called, 'regional' linkage) to hierarchical clustering in R ('hclust' function in 'stats' library): data regridding, coarsening spatial resolution, geographic masking (by continents, regions, or countries), data filtering by mean and/or variance thresholds, data preprocessing (detrending, standardization, and PCA), faster correlation function with preliminary big data support, different clustering methods, hybrid hierarchical clustering, multi-variate clustering (MVC), cluster validation, and visualization of region maps.
Author: Hamada S. Badr [aut, cre], Benjamin F. Zaitchik [aut], Amin K. Dezfuli [aut]
Maintainer: Hamada S. Badr <badr@jhu.edu>

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Package myTAI updated to version 0.1.0 with previous version 0.0.2 dated 2014-12-27

Title: Performing Phylotranscriptomics with R
Description: A statistical framework allowing users interested in the evolution of biological (developmental) processes to capture evolutionary signals in developmental transcriptomes.
Author: Hajk-Georg Drost
Maintainer: Hajk-Georg Drost <hajk-georg.drost@informatik.uni-halle.de>

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Package joint.Cox updated to version 1.1 with previous version 1.0 dated 2015-02-28

Title: Penalized Likelihood Estimation under the Joint Cox Models Between TTP and OS for Meta-Analysis
Description: Perform regression analyses under the joint Cox proportional hazards model between TTP and OS for meta-analysis. The method is applicable for meta-analysis combining several studies or for cluster survival data.
Author: Takeshi Emura
Maintainer: Takeshi Emura <emura@stat.ncu.edu.tw>

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Package showtext updated to version 0.4-2 with previous version 0.4-1 dated 2015-04-27

Title: Using Fonts More Easily in R Graphs
Description: Making it easy to use various types of fonts ('TrueType', 'OpenType', Type 1, web fonts, etc.) in R graphs, and supporting most output formats of R graphics including PNG, PDF and SVG. Text glyphs will be converted into polygons or raster images, hence after the plot has been created, it no longer relies on the font files. No external software such as Ghostscript is needed to use this package.
Author: Yixuan Qiu and authors/contributors of the included software. See file AUTHORS for details.
Maintainer: Yixuan Qiu <yixuan.qiu@cos.name>

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Package MixSim updated to version 1.1-1 with previous version 1.0-9 dated 2013-12-10

Title: Simulating Data to Study Performance of Clustering Algorithms
Description: The utility of this package is in simulating mixtures of Gaussian distributions with different levels of overlap between mixture components. Pairwise overlap, defined as a sum of two misclassification probabilities, measures the degree of interaction between components and can be readily employed to control the clustering complexity of datasets simulated from mixtures. These datasets can then be used for systematic performance investigation of clustering and finite mixture modeling algorithms. Among other capabilities of 'MixSim', there are computing the exact overlap for Gaussian mixtures, simulating Gaussian and non-Gaussian data, simulating outliers and noise variables, calculating various measures of agreement between two partitionings, and constructing parallel distribution plots for the graphical display of finite mixture models.
Author: Volodymyr Melnykov [aut, cre], Wei-Chen Chen [aut], Ranjan Maitra [aut]
Maintainer: Volodymyr Melnykov <vmelnykov@cba.ua.edu>

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