Sat, 18 Oct 2014

Package tis updated to version 1.27 with previous version 1.23 dated 2013-01-08

Title: Time Indexes and Time Indexed Series
Description: Functions and S3 classes for time indexes and time indexed series, which are compatible with FAME frequencies.
Author: Jeff Hallman
Maintainer: Jeff Hallman

Diff between tis versions 1.23 dated 2013-01-08 and 1.27 dated 2014-10-18

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Package picasso updated to version 0.3.0 with previous version 0.2.0 dated 2014-10-06

Title: Pathwise Calibrated Sparse Shooting Algorithm
Description: Implement a new family of efficient algorithms, called PathwIse CalibrAted Sparse Shooting AlgOrithm, for a variety of sparse learning problems, including Sparse Linear Regression, Sparse Logistic Regression, Sparse Column Inverse Operator and Sparse Multivariate Regression. Different types of active set identification schemes are implemented, such as cyclic search, greedy search, stochastic search and proximal gradient search. Besides, the package provides the choices between convex (L1 norm) and non-convex (MCP and SCAD) regularizations. Moreover, group regularization, such as group Lasso, group MCP and group SCAD, are also implemented for Sparse Linear Regression, Sparse Logistic Regression and Sparse Multivariate Regression.
Author: Xingguo Li, Tuo Zhao and Han Liu
Maintainer: Xingguo Li

Diff between picasso versions 0.2.0 dated 2014-10-06 and 0.3.0 dated 2014-10-18

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New package multispatialCCM with initial version 1.0
Package: multispatialCCM
Title: Multispatial Convergent Cross Mapping
Version: 1.0
Date: 2014-10-18
Author: Adam Clark
Maintainer: Adam Clark
Depends: R (>= 3.0.2)
Description: The multispatial convergent cross mapping algorithm can be used as a test for causal associations between pairs of processes represented by time series. This is a combination of convergent cross mapping (CCM), described in Sugihara et al., 2012, Science, 338, 496-500, and dew-drop regression, described in Hsieh et al., 2008, American Naturalist, 171, 71–80. The algorithm allows CCM to be implemented on data that are not from a single long time series. Instead, data can come from many short time series, which are stitched together using bootstrapping.
License: GPL (>= 2)
Encoding: UTF-8
Packaged: 2014-10-18 23:48:53 UTC; atclark
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2014-10-19 01:55:59

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New package logconPH with initial version 1.0
Package: logconPH
Type: Package
Title: CoxPH Model with Log Concave Baseline Distribution
Version: 1.0
Date: 2014-08-19
Author: Clifford Anderson-Bergman
Maintainer: Clifford Anderson-Bergman
Description: Computes a cox PH model with a log concave baseline distribution. If no covariates are provided, estimates the log concave NPMLE. Built specifically for interval censored data, where data is a n by 2 matrix with [i, 1] as the left side of the interval for subject i and [i,2] as right side. Uncensored data can be entered by setting [i,1] = [i,2]. Alternatively, this can also handle uncensored data. If all the data is uncensored, you may enter data as a length(n) vector.
License: GPL-2
Packaged: 2014-10-18 23:32:43 UTC; Cliff
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2014-10-19 01:49:27

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Package flare updated to version 1.5.0 with previous version 1.4.0 dated 2014-07-09

Title: Family of Lasso Regression
Description: The package "flare" provides the implementation of a family of Lasso variants including Dantzig Selector, LAD Lasso, SQRT Lasso, Lq Lasso for estimating high dimensional sparse linear model. We adopt the alternating direction method of multipliers and convert the original optimization problem into a sequential L1 penalized least square minimization problem, which can be efficiently solved by linearization algorithm. A multi-stage screening approach is adopted for further acceleration. Besides the sparse linear model estimation, we also provide the extension of these Lasso variants to sparse Gaussian graphical model estimation including TIGER and CLIME using either L1 or adaptive penalty. Missing values can be tolerated for Dantzig selector and CLIME. The computation is memory-optimized using the sparse matrix output.
Author: Xingguo Li, Tuo Zhao, Lie Wang, Xiaoming Yuan and Han Liu
Maintainer: Xingguo Li

Diff between flare versions 1.4.0 dated 2014-07-09 and 1.5.0 dated 2014-10-18

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Package checkmate updated to version 1.5.0 with previous version 1.4 dated 2014-09-03

Title: Fast and versatile argument checks
Description: Tests and assertions to perform frequent argument checks. A substantial part of the package was written in C to minimize any worries about execution time overhead.
Author: Michel Lang , Bernd Bischl
Maintainer: Michel Lang

Diff between checkmate versions 1.4 dated 2014-09-03 and 1.5.0 dated 2014-10-18

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Package openxlsx updated to version 2.2.1 with previous version 2.0.15 dated 2014-07-27

Title: Read, Write and Edit XLSX Files.
Description: Simplifies the creation of XLSX files by providing a high level interface to writing, styling and editing worksheets. Through the use of Rcpp, read/write times are comparable to the xlsx and XLConnect packages with the added benefit of removing the dependency on Java.
Author: Alexander Walker [aut, cre], Luca Braglia [ctb]
Maintainer: Alexander Walker

Diff between openxlsx versions 2.0.15 dated 2014-07-27 and 2.2.1 dated 2014-10-18

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Package raster updated to version 2.3-12 with previous version 2.3-10 dated 2014-10-16

Title: raster: Geographic data analysis and modeling
Description: Reading, writing, manipulating, analyzing and modeling of gridded spatial data. The package implements basic and high-level functions. Processing of very large files is supported.
Author: Robert J. Hijmans [cre, aut], Jacob van Etten [ctb], Matteo Mattiuzzi [ctb], Michael Sumner [ctb], Jonathan A. Greenberg [ctb], Oscar Perpinan Lamigueiro [ctb], Andrew Bevan [ctb], Etienne B. Racine [ctb], Ashton Shortridge [ctb]
Maintainer: Robert J. Hijmans

Diff between raster versions 2.3-10 dated 2014-10-16 and 2.3-12 dated 2014-10-18

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Package stochprofML updated to version 1.2 with previous version 1.1 dated 2014-05-22

Title: Stochastic Profiling using Maximum Likelihood Estimation
Description: This is an R package accompanying the paper "Parameterizing cell-to-cell regulatory heterogeneities via stochastic transcriptional profiles" by Sameer S Bajikar, Christiane Fuchs, Andreas Roller, Fabian J Theis and Kevin A Janes (PNAS 2014, 111(5), E626-635). In this paper, we measure expression profiles from small heterogeneous populations of cells, where each cell is assumed to be from a mixture of lognormal distributions. We perform maximum likelihood estimation in order to infer the mixture ratio and the parameters of these lognormal distributions from the cumulated expression measurements.
Author: Christiane Fuchs
Maintainer: Christiane Fuchs

Diff between stochprofML versions 1.1 dated 2014-05-22 and 1.2 dated 2014-10-18

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

Title: Ecological and biogeographical null model tests for comparing rarefaction curves
Description: Randomization tests for the statistical comparison of \emph{i} = two or more individual-based, sample-based or coverage-based rarefaction curves. The ecological null hypothesis is that the \emph{i} samples were all drawn randomly from a single assemblage, with (necessarily) a single underlying species abundance distribution. The biogeographic null hypothesis is that the \emph{i} samples were all drawn from different assemblages that, nonetheless, share similar species richness and species abundance distributions
Author: Luis Cayuela and Nicholas J. Gotelli
Maintainer: Luis Cayuela

Diff between rareNMtests versions 1.0 dated 2014-06-06 and 1.1 dated 2014-10-18

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New package landpred with initial version 1.0
Package: landpred
Type: Package
Title: Landmark Prediction of a Survival Outcome
Version: 1.0
Author: Layla Parast
Maintainer: Layla Parast
Description: This package includes functions for landmark prediction of a survival outcome incorporating covariate and short-term event information. For more information about landmark prediction please see: Parast, Layla, Su-Chun Cheng, and Tianxi Cai. Incorporating short-term outcome information to predict long-term survival with discrete markers. Biometrical Journal 53.2 (2011): 294-307.
License: GPL
Imports: survival
Packaged: 2014-10-17 22:28:12 UTC; parast
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2014-10-18 06:36:04

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