Fri, 13 Oct 2017

Package WWR updated to version 1.2.1 with previous version 1.2.0 dated 2017-06-14

Title: Weighted Win Loss Statistics and their Variances
Description: Calculate the (weighted) win loss statistics including the win ratio, win difference and win product and their variances, with which the p-values are also calculated. The variance estimation is based on Luo et al. (2015) <doi:10.1111/biom.12225> and Luo et al. (2017) <doi:10.1002/sim.7284>. This package also calculates general win loss statistics with user-specified win loss function with variance estimation based on Bebu and Lachin (2016) <doi:10.1093/biostatistics/kxv032>.
Author: Xiaodong Luo [aut, cre], Junshan Qiu [ctb], Steven Bai [ctb], Hong Tian [ctb], Mike Mikailov [ctb], Sanofi [cph]
Maintainer: Xiaodong Luo <Xiaodong.Luo@sanofi.com>

Diff between WWR versions 1.2.0 dated 2017-06-14 and 1.2.1 dated 2017-10-13

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Package slickR updated to version 0.2.2 with previous version 0.2.0 dated 2017-09-15

Title: Create Interactive Carousels with the JavaScript 'Slick' Library
Description: Create and customize interactive carousels using the 'Slick' JavaScript library and the 'htmlwidgets' package. The carousels can contain plots produced in R, images, 'iframes', videos and other 'htmlwidgets'. These carousels can be used directly from the R console, from 'RStudio', in Shiny apps and R Markdown documents.
Author: Jonathan Sidi [aut, cre]
Maintainer: Jonathan Sidi <yonis@metrumrg.com>

Diff between slickR versions 0.2.0 dated 2017-09-15 and 0.2.2 dated 2017-10-13

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Package lawn updated to version 0.4.2 with previous version 0.4.0 dated 2017-09-15

Title: Client for 'Turfjs' for 'Geospatial' Analysis
Description: Client for 'Turfjs' (<http://turfjs.org>) for 'geospatial' analysis. The package revolves around using 'GeoJSON' data. Functions are included for creating 'GeoJSON' data objects, measuring aspects of 'GeoJSON', and combining, transforming, and creating random 'GeoJSON' data objects.
Author: Scott Chamberlain [aut, cre], Jeff Hollister [aut], Morgan Herlocker [cph]
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

Diff between lawn versions 0.4.0 dated 2017-09-15 and 0.4.2 dated 2017-10-13

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Package RxODE updated to version 0.6-1 with previous version 0.6-0 dated 2017-10-05

Title: Facilities for Simulating from ODE-Based Models
Description: Facilities for running simulations from ordinary differential equation (ODE) models, such as pharmacometrics and other compartmental models. A compilation manager translates the ODE model into C, compiles it, and dynamically loads the object code into R for improved computational efficiency. An event table object facilitates the specification of complex dosing regimens (optional) and sampling schedules. NB: The use of this package requires both C and Fortran compilers, for details on their use with R please see Section 6.3, Appendix A, and Appendix D in the "R Administration and Installation" manual. Also the code is mostly released under GPL. The VODE and LSODA are in the public domain. The information is available in the inst/COPYRIGHTS.
Author: Matthew L. Fidler [aut], Melissa Hallow [aut], Wenping Wang [aut, cre]
Maintainer: Wenping Wang <wwang8198@gmail.com>

Diff between RxODE versions 0.6-0 dated 2017-10-05 and 0.6-1 dated 2017-10-13

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Package PTXQC updated to version 0.92.0 with previous version 0.91.0 dated 2017-10-06

Title: Quality Report Generation for MaxQuant Results
Description: Generates Proteomics (PTX) quality control (QC) reports for shotgun LC-MS data analyzed with the MaxQuant software suite (see <http://www.maxquant.org>). Reports are customizable (target thresholds, subsetting) and available in HTML or PDF format. Published in J. Proteome Res., Proteomics Quality Control: Quality Control Software for MaxQuant Results (2015) <doi:10.1021/acs.jproteome.5b00780>.
Author: Chris Bielow <chris.bielow@fu-berlin.de>
Maintainer: Chris Bielow <chris.bielow@fu-berlin.de>

Diff between PTXQC versions 0.91.0 dated 2017-10-06 and 0.92.0 dated 2017-10-13

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Package PNADcIBGE updated to version 0.2.1 with previous version 0.2.0 dated 2017-10-10

Title: Downloading, Reading and Analysing PNADc Microdata
Description: Provides tools for download, read, and analyse the PNADc household survey from Brazilian Institute of Geography and Statistics. The data must be downloaded from the official website <https://www.ibge.gov.br/>. Further analyses must be made using package 'survey'.
Author: Douglas Braga [aut, cre]
Maintainer: Douglas Braga <douglas.braga@ibge.gov.br>

Diff between PNADcIBGE versions 0.2.0 dated 2017-10-10 and 0.2.1 dated 2017-10-13

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Package PLmixed updated to version 0.1.2 with previous version 0.1.1 dated 2017-08-31

Title: Estimate (Generalized) Linear Mixed Models with Factor Structures
Description: Utilizes the 'lme4' package and the optim() function from 'stats' to estimate (generalized) linear mixed models (GLMM) with factor structures using a profile likelihood approach, as outlined in Jeon and Rabe-Hesketh (2012) <doi:10.3102/1076998611417628>. Factor analysis and item response models can be extended to allow for an arbitrary number of nested and crossed random effects, making it useful for multilevel and cross-classified models.
Author: Minjeong Jeon [aut], Nicholas Rockwood [aut, cre]
Maintainer: Nicholas Rockwood <rockwood.19@osu.edu>

Diff between PLmixed versions 0.1.1 dated 2017-08-31 and 0.1.2 dated 2017-10-13

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Package mrfDepth updated to version 1.0.5 with previous version 1.0.4 dated 2017-06-14

Title: Depth Measures in Multivariate, Regression and Functional Settings
Description: Tools to compute depth measures and implementations of related tasks such as outlier detection, data exploration and classification of multivariate, regression and functional data.
Author: Pieter Segaert [aut, cre], Mia Hubert [aut], Peter Rousseeuw [aut], Jakob Raymaekers [aut], Kaveh Vakili [ctb]
Maintainer: Pieter Segaert <Pieter.Segaert@kuleuven.be>

Diff between mrfDepth versions 1.0.4 dated 2017-06-14 and 1.0.5 dated 2017-10-13

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Package mixOmics updated to version 6.3.0 with previous version 6.2.0 dated 2017-08-17

Title: Omics Data Integration Project
Description: Multivariate methods are well suited to large omics data sets where the number of variables (e.g. genes, proteins, metabolites) is much larger than the number of samples (patients, cells, mice). They have the appealing properties of reducing the dimension of the data by using instrumental variables (components), which are defined as combinations of all variables. Those components are then used to produce useful graphical outputs that enable better understanding of the relationships and correlation structures between the different data sets that are integrated. mixOmics offers a wide range of multivariate methods for the exploration and integration of biological datasets with a particular focus on variable selection. The package proposes several sparse multivariate models we have developed to identify the key variables that are highly correlated, and/or explain the biological outcome of interest. The data that can be analysed with mixOmics may come from high throughput sequencing technologies, such as omics data (transcriptomics, metabolomics, proteomics, metagenomics etc) but also beyond the realm of omics (e.g. spectral imaging). The methods implemented in mixOmics can also handle missing values without having to delete entire rows with missing data. A non exhaustive list of methods include variants of generalised Canonical Correlation Analysis, sparse Partial Least Squares and sparse Discriminant Analysis. Recently we implemented integrative methods to combine multiple data sets: N-integration with variants of Generalised Canonical Correlation Analysis and P-integration with variants of multi-group Partial Least Squares.
Author: Kim-Anh Le Cao, Florian Rohart, Ignacio Gonzalez, Sebastien Dejean with key contributors Benoit Gautier, Francois Bartolo and contributions from Pierre Monget, Jeff Coquery, FangZou Yao, Benoit Liquet.
Maintainer: Kim-Anh Le Cao <kimanh.lecao@unimelb.edu.au>

Diff between mixOmics versions 6.2.0 dated 2017-08-17 and 6.3.0 dated 2017-10-13

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Package globals updated to version 0.10.3 with previous version 0.10.2 dated 2017-08-08

Title: Identify Global Objects in R Expressions
Description: Identifies global ("unknown" or "free") objects in R expressions by code inspection using various strategies, e.g. conservative or liberal. The objective of this package is to make it as simple as possible to identify global objects for the purpose of exporting them in distributed compute environments.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

Diff between globals versions 0.10.2 dated 2017-08-08 and 0.10.3 dated 2017-10-13

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Package EAinference updated to version 0.2.1 with previous version 0.2.0 dated 2017-09-16

Title: Estimator Augmentation and Simulation-Based Inference
Description: Estimator augmentation methods for statistical inference on high-dimensional data, as described in Zhou, Q. (2014) <arXiv:1401.4425v2> and Zhou, Q. and Min, S. (2017) <doi:10.1214/17-EJS1309>. It provides several simulation-based inference methods: (a) Gaussian and wild multiplier bootstrap for lasso, group lasso, scaled lasso, scaled group lasso and their de-biased estimators, (b) importance sampler for approximating p-values in these methods, (c) Markov chain Monte Carlo lasso sampler with applications in post-selection inference.
Author: Seunghyun Min [aut, cre], Qing Zhou [aut]
Maintainer: Seunghyun Min <seunghyun@ucla.edu>

Diff between EAinference versions 0.2.0 dated 2017-09-16 and 0.2.1 dated 2017-10-13

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Package ClusterR updated to version 1.0.7 with previous version 1.0.6 dated 2017-08-03

Title: Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans and K-Medoids Clustering
Description: Gaussian mixture models, k-means, mini-batch-kmeans and k-medoids clustering with the option to plot, validate, predict (new data) and estimate the optimal number of clusters. The package takes advantage of 'RcppArmadillo' to speed up the computationally intensive parts of the functions.
Author: Lampros Mouselimis <mouselimislampros@gmail.com>
Maintainer: Lampros Mouselimis <mouselimislampros@gmail.com>

Diff between ClusterR versions 1.0.6 dated 2017-08-03 and 1.0.7 dated 2017-10-13

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Package brglm2 updated to version 0.1.5 with previous version 0.1.4 dated 2017-05-22

Title: Bias Reduction in Generalized Linear Models
Description: Estimation and inference from generalized linear models based on various methods for bias reduction. The 'brglmFit' fitting method can achieve reduction of estimation bias by solving either the mean bias-reducing adjusted score equations in Firth (1993) <doi:10.1093/biomet/80.1.27> and Kosmidis and Firth (2009) <doi:10.1093/biomet/asp055>, or the median bias-reduction adjusted score equations in Kenne et al. (2016) <arXiv:1604.04768>, or through the direct subtraction of an estimate of the bias of the maximum likelihood estimator from the maximum likelihood estimates as in Cordeiro and McCullagh (1991) <http://www.jstor.org/stable/2345592>. Estimation in all cases takes place via a quasi Fisher scoring algorithm, and S3 methods for the construction of of confidence intervals for the reduced-bias estimates are provided. In the special case of generalized linear models for binomial and multinomial responses, the adjusted score approaches return estimates with improved frequentist properties, that are also always finite, even in cases where the maximum likelihood estimates are infinite (e.g. complete and quasi-complete separation). 'brglm2' also provides pre-fit and post-fit methods for detecting separation and infinite maximum likelihood estimates in binomial response generalized linear models.
Author: Ioannis Kosmidis [aut, cre], Kjell Konis [ctb], Euloge Clovis Kenne Pagui [ctb], Nicola Sartori [ctb]
Maintainer: Ioannis Kosmidis <i.kosmidis@ucl.ac.uk>

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Package bedr updated to version 1.0.4 with previous version 1.0.3 dated 2016-08-23

Title: Genomic Region Processing using Tools Such as 'BEDTools', 'BEDOPS' and 'Tabix'
Description: Genomic regions processing using open-source command line tools such as 'BEDTools', 'BEDOPS' and 'Tabix'. These tools offer scalable and efficient utilities to perform genome arithmetic e.g indexing, formatting and merging. bedr API enhances access to these tools as well as offers additional utilities for genomic regions processing.
Author: Daryl Waggott [aut], Syed Haider [aut], Emilie Lalonde [ctb], Clement Fung [ctb], Paul C. Boutros [aut, cre, cph]
Maintainer: Paul C. Boutros <Paul.Boutros@oicr.on.ca>

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Package survivalMPL updated to version 0.1.2 with previous version 0.1.1 dated 2014-08-30

Title: Penalised Maximum Likelihood for Survival Analysis Models
Description: Estimate the regression coefficients and the baseline hazard of proportional hazard Cox models using maximum penalised likelihood. A 'non-parametric' smooth estimate of the baseline hazard function is provided.
Author: Dominique-Laurent Couturier, Jun Ma, Stephane Heritier, Maurizio Manuguerra.
Maintainer: Maurizio Manuguerra <maurizio.manuguerra@mq.edu.au>

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Package MetaSubtract updated to version 1.2 with previous version 1.1 dated 2017-09-11

Title: Subtracting Summary Statistics of One or more Cohorts from Meta-GWAS Results
Description: If results from a meta-GWAS are used for validation in one of the cohorts that was included in the meta-analysis, this will yield biased (i.e. too optimistic) results. The validation cohort needs to be independent from the meta-GWAS results. MetaSubtract will subtract the results of the respective cohort from the meta-GWAS results analytically without having to redo the meta-GWAS analysis using the leave-one-out methodology. It can handle different meta-analyses methods and takes into account if single or double genomic control correction was applied to the original meta-analysis. It can be used for whole GWAS, but also for a limited set of SNPs or other genetic markers.
Author: Ilja M. Nolte
Maintainer: Ilja M. Nolte <i.m.nolte@umcg.nl>

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Package FRK updated to version 0.1.6 with previous version 0.1.5 dated 2017-08-08

Title: Fixed Rank Kriging
Description: Fixed Rank Kriging is a tool for spatial/spatio-temporal modelling and prediction with large datasets. The approach, discussed in Cressie and Johannesson (2008) <DOI:10.1111/j.1467-9868.2007.00633.x>, decomposes the field, and hence the covariance function, using a fixed set of n basis functions, where n is typically much smaller than the number of data points (or polygons) m. The method naturally allows for non-stationary, anisotropic covariance functions and the use of observations with varying support (with known error variance). The projected field is a key building block of the Spatial Random Effects (SRE) model, on which this package is based. The package FRK provides helper functions to model, fit, and predict using an SRE with relative ease.
Author: Andrew Zammit-Mangion [aut, cre], Timothy Davis [ctb], Patrick Amestoy [ctb], Iain Duff [ctb], John K. Reid [ctb]
Maintainer: Andrew Zammit-Mangion <andrewzm@gmail.com>

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More information about FRK at CRAN
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Package fDMA updated to version 2.1 with previous version 2.0 dated 2017-08-31

Title: Dynamic Model Averaging and Dynamic Model Selection for Continuous Outcomes
Description: Allows to estimate dynamic model averaging, dynamic model selection and median probability model. The original methods are implemented, as well as, selected further modifications of these methods. In particular the user might choose between recursive moment estimation and exponentially moving average for variance updating. Inclusion probabilities might be modified in a way using 'Google Trends'. The code is written in a way which minimises the computational burden (which is quite an obstacle for dynamic model averaging if many variables are used). For example, this package allows for parallel computations and Occam's window approach. The package is designed in a way that is hoped to be especially useful in economics and finance. Main reference: Raftery, A.E., Karny, M., Ettler, P. (2010) <doi:10.1198/TECH.2009.08104>.
Author: Krzysztof Drachal [aut, cre] (Faculty of Economic Sciences, University of Warsaw, Poland)
Maintainer: Krzysztof Drachal <kdrachal@wne.uw.edu.pl>

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Package dave updated to version 2.0 with previous version 1.5 dated 2014-07-21

Title: Functions for "Data Analysis in Vegetation Ecology"
Description: A collection of functions accompanying the book "Data Analysis in Vegetation Ecology". 3rd ed. CABI, Oxfordshire, Boston.
Author: Otto Wildi
Maintainer: Otto Wildi <otto.wildi@wsl.ch>

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Package breathtestcore updated to version 0.4.0 with previous version 0.3.0 dated 2017-05-11

Title: Core Functions to Read and Fit 13c Time Series from Breath Tests
Description: Reads several formats of 13C data (IRIS/Wagner, BreathID) and CSV. Creates artificial sample data for testing. Fits Maes/Ghoos, Bluck-Coward self-correcting formula using 'nls', 'nlme'. See Bluck L J C and Coward W A 2006 <doi:10.1088/0967-3334/27/3/006>. Methods to fit breath test curves with Bayesian Stan methods are refactored to package 'breathteststan'. For a Shiny GUI, see package 'dmenne/breathtestshiny', currently on github only.
Author: Dieter Menne [aut, cre], Menne Biomed Consulting Tuebingen [cph], Benjamin Misselwitz [fnd], Mark Fox [fnd], Andreas Steingoetter [dtc], University Hospital of Zurich, Dep. Gastroenterology [fnd, dtc]
Maintainer: Dieter Menne <dieter.menne@menne-biomed.de>

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Package queueing updated to version 0.2.11 with previous version 0.2.10 dated 2017-05-29

Title: Analysis of Queueing Networks and Models
Description: It provides versatile tools for analysis of birth and death based Markovian Queueing Models and Single and Multiclass Product-Form Queueing Networks. It implements M/M/1, M/M/c, M/M/Infinite, M/M/1/K, M/M/c/K, M/M/c/c, M/M/1/K/K, M/M/c/K/K, M/M/c/K/m, M/M/Infinite/K/K, Multiple Channel Open Jackson Networks, Multiple Channel Closed Jackson Networks, Single Channel Multiple Class Open Networks, Single Channel Multiple Class Closed Networks and Single Channel Multiple Class Mixed Networks. Also it provides a B-Erlang, C-Erlang and Engset calculators. This work is dedicated to the memory of D. Sixto Rios Insua.
Author: Pedro Canadilla
Maintainer: Pedro Canadilla <pedro.canadilla@gmail.com>

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Package RLumModel updated to version 0.2.2 with previous version 0.2.1 dated 2017-04-13

Title: Solving Ordinary Differential Equations to Understand Luminescence
Description: A collection of functions to simulate luminescence signals in quartz and Al2O3 based on published models.
Author: Johannes Friedrich [aut, trl, cre], Sebastian Kreutzer [aut, ths], Christoph Schmidt [aut, ths]
Maintainer: Johannes Friedrich <johannes.friedrich@uni-bayreuth.de>

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Package rucrdtw updated to version 0.1.3 with previous version 0.1.2 dated 2017-05-07

Title: R Bindings for the UCR Suite
Description: R bindings for functions from the UCR Suite by Rakthanmanon et al. (2012) <DOI:10.1145/2339530.2339576>, which enables ultrafast subsequence search for a best match under Dynamic Time Warping and Euclidean Distance.
Author: Philipp Boersch-Supan [aut, cre] (0000-0001-6723-6833), Thanawin Rakthanmanon [aut], Bilson Campana [aut], Abdullah Mueen [aut], Gustavo Batista [aut], Eamonn Keogh [aut]
Maintainer: Philipp Boersch-Supan <pboesu@gmail.com>

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