Tue, 10 Dec 2019

Package optCluster updated to version 1.2.0 with previous version 1.1.1 dated 2017-03-13

Title: Determine Optimal Clustering Algorithm and Number of Clusters
Description: Cluster analysis using statistical and biological validation measures for both continuous and count data.
Author: Michael Sekula <michael.sekula@louisville.edu>, Somnath Datta <somnath.datta@louisville.edu>, and Susmita Datta <susmita.datta@louisville.edu>
Maintainer: Michael Sekula <michael.sekula@louisville.edu>

Diff between optCluster versions 1.1.1 dated 2017-03-13 and 1.2.0 dated 2019-12-10

 DESCRIPTION              |    8 -
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More information about optCluster at CRAN
Permanent link

Package mlr3 updated to version 0.1.5 with previous version 0.1.4 dated 2019-10-28

Title: Machine Learning in R - Next Generation
Description: Efficient, object-oriented programming on the building blocks of machine learning. Provides 'R6' objects for tasks, learners, resamplings, and measures. The package is geared towards scalability and larger datasets by supporting parallelization and out-of-memory data-backends like databases. While 'mlr3' focuses on the core computational operations, add-on packages provide additional functionality.
Author: Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>), Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Jakob Richter [aut] (<https://orcid.org/0000-0003-4481-5554>), Patrick Schratz [aut] (<https://orcid.org/0000-0003-0748-6624>), Giuseppe Casalicchio [ctb] (<https://orcid.org/0000-0001-5324-5966>), Stefan Coors [ctb] (<https://orcid.org/0000-0002-7465-2146>), Quay Au [ctb] (<https://orcid.org/0000-0002-5252-8902>), Martin Binder [aut]
Maintainer: Michel Lang <michellang@gmail.com>

Diff between mlr3 versions 0.1.4 dated 2019-10-28 and 0.1.5 dated 2019-12-10

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More information about mlr3 at CRAN
Permanent link

Package MachineShop updated to version 2.0.0 with previous version 1.6.0 dated 2019-10-10

Title: Machine Learning Models and Tools
Description: Meta-package for statistical and machine learning with a unified interface for model fitting, prediction, performance assessment, and presentation of results. Approaches for model fitting and prediction of numerical, categorical, or censored time-to-event outcomes include traditional regression models, regularization methods, tree-based methods, support vector machines, neural networks, ensembles, data preprocessing, filtering, and model tuning and selection. Performance metrics are provided for model assessment and can be estimated with independent test sets, split sampling, cross-validation, or bootstrap resampling. Resample estimation can be executed in parallel for faster processing and nested in cases of model tuning and selection. Modeling results can be summarized with descriptive statistics; calibration curves; variable importance; partial dependence plots; confusion matrices; and ROC, lift, and other performance curves.
Author: Brian J Smith [aut, cre]
Maintainer: Brian J Smith <brian-j-smith@uiowa.edu>

Diff between MachineShop versions 1.6.0 dated 2019-10-10 and 2.0.0 dated 2019-12-10

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Package lori updated to version 2.2.0 with previous version 2.1.3 dated 2019-03-29

Title: Imputation of Count Data using Side Information
Description: Analysis, imputation, and multiple imputation of count data using covariates. LORI uses a log-linear model where main row and column effects are decomposed as regression terms on known covariates. A residual low-rank interaction term is also fitted. LORI returns estimates of covariate effects and interactions, as well as an imputed count table. The package also contains a multiple imputation procedure.
Author: Genevieve Robin [aut, cre]
Maintainer: Genevieve Robin <genevieve.robin@inria.fr>

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Package isocat updated to version 0.2.4 with previous version 0.2.3 dated 2019-06-07

Title: Isotope Origin Clustering and Assignment Tools
Description: This resource provides tools to create, compare, and post-process spatial isotope assignment models of animal origin. It generates probability-of-origin maps for individuals based on user-provided tissue and environment isotope values (e.g., as generated by IsoMAP, Bowen [2010] <doi:10.1111/2041-210X.12147>) using the framework established in Bowen (2014) <doi:10.1111/2041-210X.12147>. The package 'isocat' can then quantitatively compare and cluster these maps to group individuals by similar origin. It also includes techniques for applying four approaches (cumulative sum, odds ratio, quantile only, and quantile simulation) with which users can summarize geographic origins and probable distance traveled by individuals.
Author: Caitlin Campbell [aut, cre]
Maintainer: Caitlin Campbell <caitjcampbell@gmail.com>

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Package tinytex updated to version 0.18 with previous version 0.17 dated 2019-10-30

Title: Helper Functions to Install and Maintain 'TeX Live', and Compile 'LaTeX' Documents
Description: Helper functions to install and maintain the 'LaTeX' distribution named 'TinyTeX' (<https://yihui.org/tinytex/>), a lightweight, cross-platform, portable, and easy-to-maintain version of 'TeX Live'. This package also contains helper functions to compile 'LaTeX' documents, and install missing 'LaTeX' packages automatically.
Author: Yihui Xie [aut, cre, cph] (<https://orcid.org/0000-0003-0645-5666>), RStudio, Inc. [cph], Fernando Cagua [ctb], Ethan Heinzen [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

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Package rqPen updated to version 2.2 with previous version 2.1 dated 2019-05-01

Title: Penalized Quantile Regression
Description: Performs penalized quantile regression for LASSO, SCAD and MCP functions including group penalties. Provides a function that automatically generates lambdas and evaluates different models with cross validation or BIC, including a large p version of BIC.
Author: Ben Sherwood [aut, cre], Adam Maidman [ctb]
Maintainer: Ben Sherwood <ben.sherwood@ku.edu>

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Package opalr updated to version 1.3.0 with previous version 1.2.0 dated 2019-08-19

Title: 'Opal' Data Repository Client and 'DataSHIELD' Utils
Description: Data integration Web application for biobanks by 'OBiBa'. 'Opal' is the core database application for biobanks. Participant data, once collected from any data source, must be integrated and stored in a central data repository under a uniform model. 'Opal' is such a central repository. It can import, process, validate, query, analyze, report, and export data. 'Opal' is typically used in a research center to analyze the data acquired at assessment centres. Its ultimate purpose is to achieve seamless data-sharing among biobanks. This 'Opal' client allows to interact with 'Opal' web services and to perform operations on the R server side. 'DataSHIELD' administration tools are also provided.
Author: Yannick Marcon [aut, cre] (<https://orcid.org/0000-0003-0138-2023>), Amadou Gaye [ctb] (<https://orcid.org/0000-0002-1180-2792>), OBiBa group [cph]
Maintainer: Yannick Marcon <yannick.marcon@obiba.org>

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Package MEDseq updated to version 1.0.1 with previous version 1.0.0 dated 2019-08-24

Title: Mixtures of Exponential-Distance Models with Covariates
Description: Implements a model-based clustering method for categorical life-course sequences relying on mixtures of exponential-distance models introduced by Murphy et al. (2019) <arXiv:1908.07963>. A range of flexible precision parameter settings corresponding to weighted generalisations of the Hamming distance metric are considered, along with the potential inclusion of a noise component. Gating covariates can be supplied in order to relate sequences to baseline characteristics. Sampling weights are also accommodated. The models are fitted using the EM algorithm and tools for visualising the results are also provided.
Author: Keefe Murphy [aut, cre], Thomas Brendan Murphy [ctb], Raffaella Piccarreta [ctb], Isobel Claire Gormley [ctb]
Maintainer: Keefe Murphy <keefe.murphy@ucd.ie>

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Package sensiPhy updated to version 0.8.4 with previous version 0.8.3 dated 2018-09-11

Title: Sensitivity Analysis for Comparative Methods
Description: An implementation of sensitivity analysis for phylogenetic comparative methods. The package is an umbrella of statistical and graphical methods that estimate and report different types of uncertainty in PCM: (i) Species Sampling uncertainty (sample size; influential species and clades). (ii) Phylogenetic uncertainty (different topologies and/or branch lengths). (iii) Data uncertainty (intraspecific variation and measurement error).
Author: Gustavo Paterno [cre, aut], Gijsbert Werner [aut], Caterina Penone [aut], Pablo Martinez [ctb]
Maintainer: Gustavo Paterno <paternogbc@gmail.com>

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Package matahari updated to version 0.1.2 with previous version 0.1.1 dated 2019-10-09

Title: Spy on Your R Session
Description: Conveniently log everything you type into the R console. Logs are are stored as tidy data frames which can then be analyzed using 'tidyverse' style tools.
Author: Sean Kross [aut, cre] (<https://orcid.org/0000-0001-5215-0316>), Lucy D'Agostino McGowan [aut] (<https://orcid.org/0000-0001-7297-9359>), Jeff Leek [ldr] (<https://orcid.org/0000-0002-2873-2671>)
Maintainer: Sean Kross <sean@seankross.com>

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Package tidycode updated to version 0.1.1 with previous version 0.1.0 dated 2019-05-20

Title: Analyze Lines of R Code the Tidy Way
Description: Analyze lines of R code using tidy principles. This allows you to input lines of R code and output a data frame with one row per function included. Additionally, it facilitates code classification via included lexicons.
Author: Lucy D'Agostino McGowan [aut, cre] (<https://orcid.org/0000-0001-7297-9359>), Jim Hester [ctb], Jeff Leek [ldr]
Maintainer: Lucy D'Agostino McGowan <lucydagostino@gmail.com>

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Package segmented updated to version 1.1-0 with previous version 1.0-0 dated 2019-06-17

Title: Regression Models with Break-Points / Change-Points Estimation
Description: Given a regression model, segmented `updates' it by adding one or more segmented (i.e., piece-wise linear) relationships. Several variables with multiple breakpoints are allowed. The estimation method is discussed in Muggeo (2003, <doi:10.1002/sim.1545>) and illustrated in Muggeo (2008, <https://www.r-project.org/doc/Rnews/Rnews_2008-1.pdf>). An approach for hypothesis testing is presented in Muggeo (2016, <doi:10.1080/00949655.2016.1149855>), and interval estimation for the breakpoint is discussed in Muggeo (2017, <doi:10.1111/anzs.12200>).
Author: Vito M. R. Muggeo [aut, cre]
Maintainer: Vito M. R. Muggeo <vito.muggeo@unipa.it>

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Package periscope updated to version 0.4.7 with previous version 0.4.6 dated 2019-09-26

Title: Enterprise Streamlined 'Shiny' Application Framework
Description: An enterprise-targeted scalable and UI-standardized 'shiny' framework including a variety of developer convenience functions with the goal of both streamlining robust application development while assisting with creating a consistent user experience regardless of application or developer.
Author: Constance Brett [aut, cre], Isaac Neuhaus [aut] (canvasXpress JavaScript Library Maintainer), Ger Inberg [ctb], Bristol-Meyers Squibb (BMS) [cph]
Maintainer: Constance Brett <connie@aggregate-genius.com>

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Package greybox updated to version 0.5.7 with previous version 0.5.6 dated 2019-10-29

Title: Toolbox for Model Building and Forecasting
Description: Implements functions and instruments for regression model building and its application to forecasting. The main scope of the package is in variables selection and models specification for cases of time series data. This includes promotional modelling, selection between different dynamic regressions with non-standard distributions of errors, selection based on cross validation, solutions to the fat regression model problem and more. Models developed in the package are tailored specifically for forecasting purposes. So as a results there are several methods that allow producing forecasts from these models and visualising them.
Author: Ivan Svetunkov [aut, cre] (Lecturer at Centre for Marketing Analytics and Forecasting, Lancaster University, UK)
Maintainer: Ivan Svetunkov <ivan@svetunkov.ru>

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Package dataMaid updated to version 1.4.0 with previous version 1.3.2 dated 2019-07-27

Title: A Suite of Checks for Identification of Potential Errors in a Data Frame as Part of the Data Screening Process
Description: Data screening is an important first step of any statistical analysis. dataMaid auto generates a customizable data report with a thorough summary of the checks and the results that a human can use to identify possible errors. It provides an extendable suite of test for common potential errors in a dataset.
Author: Anne Helby Petersen [aut], Claus Thorn Ekstrøm [aut, cre]
Maintainer: Claus Thorn Ekstrøm <ekstrom@sund.ku.dk>

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Package permubiome updated to version 1.3 with previous version 1.2 dated 2018-08-17

Title: A Permutation Based Test for Biomarker Discovery in Microbiome Data
Description: The permubiome R package was created to perform a permutation-based non-parametric analysis on microbiome data for biomarker discovery aims. This test executes thousands of comparisons in a pairwise manner, after a random shuffling of data into the different groups of study with a prior selection of the microbiome features with the largest variation among groups. Previous to the permutation test itself, data can be normalized according to different methods proposed to handle microbiome data ('proportions' or 'Anders'). The median-based differences between groups resulting from the multiple simulations are fitted to a normal distribution with the aim to calculate their significance. A multiple testing correction based on Benjamini-Hochberg method (fdr) is finally applied to extract the differentially presented features between groups of your dataset. LATEST UPDATES: v1.1 and olders incorporates function to parse COLUMN format; v1.2 and olders incorporates -optimize- function to maximize evaluation of features with largest inter-class variation; v1.3 and olders includes the -size.effect- function to perform estimation statistics using the bootstrap-coupled approach implemented in the 'dabestr' R package.
Author: Alfonso Benitez-Paez
Maintainer: Alfonso Benitez-Paez <abenitez@iata.csic.es>

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Package krm updated to version 2019.12-11 with previous version 2018.8-17 dated 2018-08-18

Title: Kernel Based Regression Models
Description: Implements several methods for testing the variance component parameter in regression models that contain kernel-based random effects, including a maximum of adjusted scores test. Several kernels are supported, including a profile hidden Markov model mutual information kernel for protein sequence.
Author: Youyi Fong [cre], Saheli Datta [aut], Krisztian Sebestyen [aut], Steve Park [ctb], Dave Geyer [ctb]
Maintainer: Youyi Fong <youyifong@gmail.com>

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Package SuperLearner updated to version 2.0-26 with previous version 2.0-25 dated 2019-08-09

Title: Super Learner Prediction
Description: Implements the super learner prediction method and contains a library of prediction algorithms to be used in the super learner.
Author: Eric Polley [aut, cre], Erin LeDell [aut], Chris Kennedy [aut], Sam Lendle [ctb], Mark van der Laan [aut, ths]
Maintainer: Eric Polley <polley.eric@mayo.edu>

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Package SDMtune updated to version 1.0.0 with previous version 0.2.1 dated 2019-12-05

Title: Species Distribution Model Selection
Description: User-friendly framework that enables the training and the evaluation of species distribution models (SDMs). The package implements functions for data driven variable selection and model tuning and includes numerous utilities to display the results. All the functions used to select variables or to tune model hyperparameters have an interactive real-time chart displayed in the 'RStudio' viewer pane during their execution.
Author: Sergio Vignali [aut, cre] (<https://orcid.org/0000-0002-3390-5442>), Arnaud Barras [aut] (<https://orcid.org/0000-0003-0850-6965>), Veronika Braunisch [aut] (<https://orcid.org/0000-0001-7035-4662>), Conservation Biology - University of Bern [fnd]
Maintainer: Sergio Vignali <sergio.vignali@iee.unibe.ch>

Diff between SDMtune versions 0.2.1 dated 2019-12-05 and 1.0.0 dated 2019-12-10

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Package mlr3pipelines updated to version 0.1.2 with previous version 0.1.1 dated 2019-10-29

Title: Preprocessing Operators and Pipelines for 'mlr3'
Description: Dataflow programming toolkit that enriches 'mlr3' with a diverse set of pipelining operators ('PipeOps') that can be composed into graphs. Operations exist for data preprocessing, model fitting, and ensemble learning. Graphs can themselves be treated as 'mlr3' 'Learners' and can therefore be resampled, benchmarked, and tuned.
Author: Martin Binder [aut, cre], Florian Pfisterer [aut] (<https://orcid.org/0000-0001-8867-762X>), Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>), Susanne Dandl [aut]
Maintainer: Martin Binder <mlr.developer@mb706.com>

Diff between mlr3pipelines versions 0.1.1 dated 2019-10-29 and 0.1.2 dated 2019-12-10

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Package HiClimR updated to version 2.1.5 with previous version 2.1.4 dated 2019-01-20

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, contiguity-constrained clustering, 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, multivariate clustering (MVC), cluster validation, visualization of regionalization results, and exporting region map and mean timeseries into NetCDF-4 file.
Author: Hamada S. Badr [aut, cre], Benjamin F. Zaitchik [aut], Amin K. Dezfuli [aut]
Maintainer: Hamada S. Badr <badr@jhu.edu>

Diff between HiClimR versions 2.1.4 dated 2019-01-20 and 2.1.5 dated 2019-12-10

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Package biomartr updated to version 0.9.1 with previous version 0.9.0 dated 2019-05-21

Title: Genomic Data Retrieval
Description: Perform large scale genomic data retrieval and functional annotation retrieval. This package aims to provide users with a standardized way to automate genome, proteome, 'RNA', coding sequence ('CDS'), 'GFF', and metagenome retrieval from 'NCBI RefSeq', 'NCBI Genbank', 'ENSEMBL', 'ENSEMBLGENOMES', and 'UniProt' databases. Furthermore, an interface to the 'BioMart' database (Smedley et al. (2009) <doi:10.1186/1471-2164-10-22>) allows users to retrieve functional annotation for genomic loci. In addition, users can download entire databases such as 'NCBI RefSeq' (Pruitt et al. (2007) <doi:10.1093/nar/gkl842>), 'NCBI nr', 'NCBI nt', 'NCBI Genbank' (Benson et al. (2013) <doi:10.1093/nar/gks1195>), etc. as well as 'ENSEMBL' and 'ENSEMBLGENOMES' with only one command.
Author: Hajk-Georg Drost [aut, cre] (<https://orcid.org/0000-0002-1567-306X>)
Maintainer: Hajk-Georg Drost <hajk-georg.drost@tuebingen.mpg.de>

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Package RndTexExams (with last version 1.5) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2018-10-09 1.5
2018-01-13 1.4.1
2016-06-05 1.4
2016-05-17 1.3.1
2016-05-04 1.3
2016-04-26 1.2
2016-02-20 1.1.1
2016-02-18 1.1
2016-02-06 1.0

Permanent link
Package UKgrid updated to version 0.1.2 with previous version 0.1.1 dated 2019-05-13

Title: The UK National Electricity Transmission System Dataset
Description: A time series of the national grid demand (high-voltage electric power transmission network) in the UK since 2011.
Author: Rami Krispin [aut, cre]
Maintainer: Rami Krispin <rami.krispin@gmail.com>

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Package rym updated to version 0.5.4 with previous version 0.5.2 dated 2019-01-23

Title: R Interface to Yandex Metrica API
Description: Allows work with 'Management API' for load counters, segments, filters, user permissions and goals list from Yandex Metrica, 'Reporting API' allows you to get information about the statistics of site visits and other data without using the web interface, 'Logs API' allows to receive non-aggregated data and 'Compatible with Google Analytics Core Reporting API v3' allows receive information about site traffic and other data using field names from Google Analytics Core API. For more information see official documents <https://tech.yandex.ru/metrika/doc/api2/concept/about-docpage/>.
Author: Alexey Seleznev <selesnow@gmail.com>
Maintainer: Alexey Seleznev <selesnow@gmail.com>

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Package nesRdata updated to version 0.3.0 with previous version 0.2.0 dated 2018-09-10

Title: National Eutrophication Survey Data
Description: Serves data from the United States Environmental Protection Agency (USEPA) National Eutrophication Survey <https://www.epa.gov/national-aquatic-resource-surveys>.
Author: Joseph Stachelek [aut, cre] (<https://orcid.org/0000-0002-5924-2464>)
Maintainer: Joseph Stachelek <stachel2@msu.edu>

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Package ipflasso updated to version 1.1 with previous version 0.2 dated 2019-05-10

Title: Integrative Lasso with Penalty Factors
Description: The core of the package is cvr2.ipflasso(), an extension of glmnet to be used when the (large) set of available predictors is partitioned into several modalities which potentially differ with respect to their information content in terms of prediction. For example, in biomedical applications patient outcome such as survival time or response to therapy may have to be predicted based on, say, mRNA data, miRNA data, methylation data, CNV data, clinical data, etc. The clinical predictors are on average often much more important for outcome prediction than the mRNA data. The ipflasso method takes this problem into account by using different penalty parameters for predictors from different modalities. The ratio between the different penalty parameters can be chosen from a set of optional candidates by cross-validation or alternatively generated from the input data.
Author: Anne-Laure Boulesteix, Mathias Fuchs, Gerhard Schulze
Maintainer: Anne-Laure Boulesteix <boulesteix@ibe.med.uni-muenchen.de>

Diff between ipflasso versions 0.2 dated 2019-05-10 and 1.1 dated 2019-12-10

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Package FADA updated to version 1.3.5 with previous version 1.3.4 dated 2019-04-19

Title: Variable Selection for Supervised Classification in High Dimension
Description: The functions provided in the FADA (Factor Adjusted Discriminant Analysis) package aim at performing supervised classification of high-dimensional and correlated profiles. The procedure combines a decorrelation step based on a factor modeling of the dependence among covariates and a classification method. The available methods are Lasso regularized logistic model (see Friedman et al. (2010)), sparse linear discriminant analysis (see Clemmensen et al. (2011)), shrinkage linear and diagonal discriminant analysis (see M. Ahdesmaki et al. (2010)). More methods of classification can be used on the decorrelated data provided by the package FADA.
Author: Emeline Perthame (Institut Pasteur, Paris, France), Chloe Friguet (Universite de Bretagne Sud, Vannes, France) and David Causeur (Agrocampus Ouest, Rennes, France)
Maintainer: David Causeur <david.causeur@agrocampus-ouest.fr>

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Package Factoshiny updated to version 2.0 with previous version 1.0.7 dated 2018-11-07

Title: Perform Factorial Analysis from 'FactoMineR' with a Shiny Application
Description: Perform factorial analysis with a menu and draw graphs interactively thanks to 'FactoMineR' and a Shiny application.
Author: Pauline Vaissie, Astrid Monge, Francois Husson
Maintainer: Francois Husson <husson@agrocampus-ouest.fr>

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Package Deriv updated to version 4.0 with previous version 3.9.0 dated 2019-09-20

Title: Symbolic Differentiation
Description: R-based solution for symbolic differentiation. It admits user-defined function as well as function substitution in arguments of functions to be differentiated. Some symbolic simplification is part of the work.
Author: Andrew Clausen [aut], Serguei Sokol [aut, cre] (<https://orcid.org/0000-0002-5674-3327>), Andreas Rappold [ctb]
Maintainer: Serguei Sokol <sokol@insa-toulouse.fr>

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Package speaq updated to version 2.6.1 with previous version 2.6.0 dated 2019-05-23

Title: Tools for Nuclear Magnetic Resonance (NMR) Spectra Alignment, Peak Based Processing, Quantitative Analysis and Visualizations
Description: Makes Nuclear Magnetic Resonance spectroscopy (NMR spectroscopy) data analysis as easy as possible by only requiring a small set of functions to perform an entire analysis. 'speaq' offers the possibility of raw spectra alignment and quantitation but also an analysis based on features whereby the spectra are converted to peaks which are then grouped and turned into features. These features can be processed with any number of statistical tools either included in 'speaq' or available elsewhere on CRAN. More details can be found in Vu et al. (2011) <doi:10.1186/1471-2105-12-405> and Beirnaert et al. (2018) <doi:10.1371/journal.pcbi.1006018>.
Author: Charlie Beirnaert, Trung Nghia Vu, Pieter Meysman, Kris Laukens and Dirk Valkenborg
Maintainer: Charlie Beirnaert <charlie_beirnaert@icloud.com>

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Package mstrio updated to version 11.2.0 with previous version 11.1.4.25 dated 2019-10-28

Title: Interface for 'MicroStrategy' REST API
Description: Interface for creating data sets and extracting data through the 'MicroStrategy' REST API. Access the demo API at <https://demo.microstrategy.com/MicroStrategyLibrary/api-docs/index.html>.
Author: Piotr Kowal [cre], Scott Rigney [aut], Zofia Rogala [ctb], Piotr Czyz [ctb], Michał Drzazga [ctb], Oskar Duda [ctb], Filip Godlewski [ctb], Ignacy Hologa [ctb], Adam Piotrowski [ctb]
Maintainer: Piotr Kowal <pkowal@microstrategy.com>

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Package discSurv updated to version 1.4.1 with previous version 1.4.0 dated 2019-04-16

Title: Discrete Time Survival Analysis
Description: Provides data transformations, estimation utilities, predictive evaluation measures and simulation functions for discrete time survival analysis.
Author: Thomas Welchowski <welchow@imbie.meb.uni-bonn.de> and Matthias Schmid <matthias.schmid@imbie.uni-bonn.de>
Maintainer: Thomas Welchowski <welchow@imbie.meb.uni-bonn.de>

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Package mvmeta updated to version 1.0.3 with previous version 1.0.2 dated 2019-12-10

Title: Multivariate and Univariate Meta-Analysis and Meta-Regression
Description: Collection of functions to perform fixed and random-effects multivariate and univariate meta-analysis and meta-regression.
Author: Antonio Gasparrini
Maintainer: Antonio Gasparrini <antonio.gasparrini@lshtm.ac.uk>

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Package mexhaz updated to version 1.7 with previous version 1.6 dated 2019-06-18

Title: Mixed Effect Excess Hazard Models
Description: Fit flexible (excess) hazard regression models with the possibility of including non-proportional effects of covariables and of adding a random effect at the cluster level (corresponding to a shared frailty).
Author: Hadrien Charvat, Aurelien Belot
Maintainer: Hadrien Charvat <chadrien@ncc.go.jp>

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Package adjclust updated to version 0.5.9 with previous version 0.5.7 dated 2018-09-26

Title: Adjacency-Constrained Clustering of a Block-Diagonal Similarity Matrix
Description: Implements a constrained version of hierarchical agglomerative clustering, in which each observation is associated to a position, and only adjacent clusters can be merged. Typical application fields in bioinformatics include Genome-Wide Association Studies or Hi-C data analysis, where the similarity between items is a decreasing function of their genomic distance. Taking advantage of this feature, the implemented algorithm is time and memory efficient. This algorithm is described in Chapter 4 of Alia Dehman (2015) <https://hal.archives-ouvertes.fr/tel-01288568v1>.
Author: Christophe Ambroise [aut], Shubham Chaturvedi [aut], Alia Dehman [aut], Michel Koskas [aut], Pierre Neuvial [aut, cre], Guillem Rigaill [aut], Nathalie Vialaneix [aut]
Maintainer: Pierre Neuvial <pierre.neuvial@math.univ-toulouse.fr>

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Package BatchMap (with last version 1.0.2.0) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2017-11-11 1.0.2.0
2017-03-30 1.0.1.0
2017-03-27 1.0.0.0

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Package SIDES updated to version 1.15 with previous version 1.14 dated 2019-09-27

Title: Subgroup Identification Based on Differential Effect Search
Description: Provides function to apply "Subgroup Identification based on Differential Effect Search" (SIDES) method proposed by Lipkovich et al. (2011) <doi:10.1002/sim.4289>.
Author: Marie-Karelle Riviere
Maintainer: Marie-Karelle Riviere <eldamjh@gmail.com>

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Package EffectLiteR updated to version 0.4-4 with previous version 0.4-3 dated 2019-01-03

Title: Average and Conditional Effects
Description: Use structural equation modeling to estimate average and conditional effects of a treatment variable on an outcome variable, taking into account multiple continuous and categorical covariates.
Author: Axel Mayer [aut, cre], Lisa Dietzfelbinger [ctb]
Maintainer: Axel Mayer <amayer2010@gmail.com>

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Package brinton (with last version 0.1.2) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2019-12-09 0.1.2

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Package uchardet updated to version 1.0.2 with previous version 1.0.1 dated 2019-11-26

Title: The Universal Character Encoding Detector
Description: R bindings of the 'uchardet', encoding detector library from Mozilla (<https://www.freedesktop.org/wiki/Software/uchardet/>). It takes a sequence of bytes in an unknown character encoding and without any additional information, and attempts to get the encoding of the text. All return names of the encodings are iconv-compatible.
Author: Artem Klevtsov [aut, cre] (<https://orcid.org/0000-0003-0492-6647>), Philipp Upravitelev [ctb]
Maintainer: Artem Klevtsov <a.a.klevtsov@gmail.com>

Diff between uchardet versions 1.0.1 dated 2019-11-26 and 1.0.2 dated 2019-12-10

 uchardet-1.0.1/uchardet/inst/examples/ex_detect_file.R |only
 uchardet-1.0.1/uchardet/inst/examples/ex_detect_raw.R  |only
 uchardet-1.0.1/uchardet/inst/examples/ex_detect_str.R  |only
 uchardet-1.0.2/uchardet/DESCRIPTION                    |    8 ++---
 uchardet-1.0.2/uchardet/MD5                            |   23 +++++++----------
 uchardet-1.0.2/uchardet/NEWS.md                        |   17 ++++++++----
 uchardet-1.0.2/uchardet/R/RcppExports.R                |    6 ++--
 uchardet-1.0.2/uchardet/README.md                      |    8 ++---
 uchardet-1.0.2/uchardet/inst/doc/uchardet.html         |    3 --
 uchardet-1.0.2/uchardet/inst/tinytest/setup.R          |    2 -
 uchardet-1.0.2/uchardet/src/Makevars.in                |    3 --
 uchardet-1.0.2/uchardet/src/detect-file.cpp            |    2 -
 uchardet-1.0.2/uchardet/src/detect-raw.cpp             |    2 -
 uchardet-1.0.2/uchardet/src/detect-str.cpp             |    2 -
 14 files changed, 37 insertions(+), 39 deletions(-)

More information about uchardet at CRAN
Permanent link

Package timelineR updated to version 1.0.0 with previous version 0.1.0 dated 2017-05-25

Title: Visualization for Time Series Data
Description: Helps to visualize multi-variate time-series having numeric and factor variables. You can use the package for visual analysis of data by plotting the data for each variable in the desired order and study interaction between a factor and a numeric variable by creating overlapping plots.
Author: Mohsin Vindhani [aut], Alex Joseph [aut, cre], Ananthapadmanabhan [aut], Subramanyam Ravishankar [aut]
Maintainer: Alex Joseph <alex@systeminsights.com>

Diff between timelineR versions 0.1.0 dated 2017-05-25 and 1.0.0 dated 2019-12-10

 DESCRIPTION                        |   22 +--
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 NAMESPACE                          |    2 
 R/data_cleaner.R                   |   24 ++-
 R/plot_helper.R                    |   51 +++++-
 R/visualize.R                      |   20 +-
 README.md                          |  270 +++++++++++++++++++++++++++++++++++++
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 man/plot_timeline.Rd               |   16 +-
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 tests/testthat/test-visualize.R    |   35 ++--
 15 files changed, 496 insertions(+), 198 deletions(-)

More information about timelineR at CRAN
Permanent link

Package spatstat updated to version 1.62-2 with previous version 1.61-0 dated 2019-09-22

Title: Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests
Description: Comprehensive open-source toolbox for analysing Spatial Point Patterns. Focused mainly on two-dimensional point patterns, including multitype/marked points, in any spatial region. Also supports three-dimensional point patterns, space-time point patterns in any number of dimensions, point patterns on a linear network, and patterns of other geometrical objects. Supports spatial covariate data such as pixel images. Contains over 2000 functions for plotting spatial data, exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. Data types include point patterns, line segment patterns, spatial windows, pixel images, tessellations, and linear networks. Exploratory methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported. Parametric models can be fitted to point pattern data using the functions ppm(), kppm(), slrm(), dppm() similar to glm(). Types of models include Poisson, Gibbs and Cox point processes, Neyman-Scott cluster processes, and determinantal point processes. Models may involve dependence on covariates, inter-point interaction, cluster formation and dependence on marks. Models are fitted by maximum likelihood, logistic regression, minimum contrast, and composite likelihood methods. A model can be fitted to a list of point patterns (replicated point pattern data) using the function mppm(). The model can include random effects and fixed effects depending on the experimental design, in addition to all the features listed above. Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise(), AIC()) and variable selection (sdr). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots.
Author: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>, Rolf Turner <r.turner@auckland.ac.nz> and Ege Rubak <rubak@math.aau.dk>, with substantial contributions of code by Kasper Klitgaard Berthelsen; Ottmar Cronie; Tilman Davies; Yongtao Guan; Ute Hahn; Abdollah Jalilian; Marie-Colette van Lieshout; Greg McSwiggan; Tuomas Rajala; Suman Rakshit; Dominic Schuhmacher; Rasmus Waagepetersen; and Hangsheng Wang. Additional contributions by M. Adepeju; C. Anderson; Q.W. Ang; R. Arellano; J. Astrom; M. Austenfeld; S. Azaele; M. Baddeley; C. Beale; M. Bell; R. Bernhardt; T. Bendtsen; A. Bevan; B. Biggerstaff; A. Bilgrau; L. Bischof; C. Biscio; R. Bivand; J.M. Blanco Moreno; F. Bonneu; J. Brown; J. Burgos; S. Byers; Y.M. Chang; J.B. Chen; I. Chernayavsky; Y.C. Chin; B. Christensen; L. Cobo Sanchez; J.-F. Coeurjolly; K. Colyvas; H. Commenges; R. Constantine; R. Corria Ainslie; R. Cotton; M. de la Cruz; P. Dalgaard; M. D'Antuono; S. Das; P.J. Diggle; P. Donnelly; I. Dryden; S. Eglen; A. El-Gabbas; B. Fandohan; O. Flores; E.D. Ford; P. Forbes; S. Frank; J. Franklin; N. Funwi-Gabga; O. Garcia; A. Gault; J. Geldmann; M. Genton; S. Ghalandarayeshi; J. Gilbey; J. Goldstick; P. Grabarnik; C. Graf; U. Hahn; A. Hardegen; M.B. Hansen; M. Hazelton; J. Heikkinen; M. Hering; M. Herrmann; M. Hesselbarth; P. Hewson; H. Heydarian; K. Hingee; K. Hornik; P. Hunziker; J. Hywood; R. Ihaka; C. Icos; A. Jammalamadaka; R. John-Chandran; D. Johnson; M. Khanmohammadi; R. Klaver; P. Kovesi; L. Kozmian-Ledward; M. Kuhn; J. Laake; R.A. Lamb; F. Lavancier; T. Lawrence; T. Lazauskas; J. Lee; G.P. Leser; A. Li; H.T. Li; G. Limitsios; A. Lister; N. Luambua; B. Madin; M. Maechler; J. Marcus; K. Marchikanti; R. Mark; J. Mateu; P. McCullagh; U. Mehlig; F. Mestre; S. Meyer; X.C. Mi; L. De Middeleer; R.K. Milne; E. Miranda; J. Moller; A. Mollie; I. Moncada; M. Moradi; V. Morera Pujol; E. Mudrak; G.M. Nair; N. Najari; N. Nava; L.S. Nielsen; F. Nunes; J.R. Nyengaard; J. Oehlschlaegel; T. Onkelinx; S. O'Riordan; E. Parilov; J. Picka; N. Picard; T. Pollington; M. Porter; S. Protsiv; A. Raftery; S. Rakshit; B. Ramage; P. Ramon; X. Raynaud; N. Read; M. Reiter; I. Renner; T.O. Richardson; B.D. Ripley; E. Rosenbaum; B. Rowlingson; J. Rudokas; J. Rudge; C. Ryan; F. Safavimanesh; A. Sarkka; C. Schank; K. Schladitz; S. Schutte; B.T. Scott; O. Semboli; F. Semecurbe; V. Shcherbakov; G.C. Shen; P. Shi; H.-J. Ship; T.L. Silva; I.-M. Sintorn; Y. Song; M. Spiess; M. Stevenson; K. Stucki; J. Sulavik; M. Sumner; P. Surovy; B. Taylor; T. Thorarinsdottir; L. Torres; B. Turlach; T. Tvedebrink; K. Ummer; M. Uppala; A. van Burgel; T. Verbeke; M. Vihtakari; A. Villers; F. Vinatier; S. Voss; S. Wagner; H. Wang; H. Wendrock; J. Wild; C. Witthoft; S. Wong; M. Woringer; L. Yates; M.E. Zamboni and A. Zeileis.
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

Diff between spatstat versions 1.61-0 dated 2019-09-22 and 1.62-2 dated 2019-12-10

 DESCRIPTION                  |   14 -
 MD5                          |  435 ++++++++++++++++++------------------
 NAMESPACE                    |   46 +++
 NEWS                         |  314 ++++++++++++++++++++++++++
 R/Fest.R                     |   43 ++-
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 R/Iest.R                     |    7 
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 R/Jmulti.R                   |   31 +-
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 R/Kmulti.R                   |   12 -
 R/Kmulti.inhom.R             |   10 
 R/Kscaled.R                  |   10 
 R/Math.linim.R               |    4 
 R/breakpts.R                 |   48 +---
 R/bugtable.R                 |    7 
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 R/bw.diggle.R                |    7 
 R/bw.optim.R                 |   12 -
 R/bw.pcf.R                   |    5 
 R/bw.ppl.R                   |   11 
 R/circarcs.R                 |   27 +-
 R/clickppp.R                 |    6 
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 R/clusterfunctions.R         |    7 
 R/colourtables.R             |   13 -
 R/dclftest.R                 |   62 +++--
 R/density.lpp.R              |   25 +-
 R/densitylppVoronoi.R        |    3 
 R/diagnoseppm.R              |    4 
 R/distanxD.R                 |  186 +++++++++++++++
 R/dppmclass.R                |   34 +-
 R/edgeRipley.R               |   23 +
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 R/envelope3.R                |    6 
 R/envelopelpp.R              |   20 +
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 R/nnfun.R                    |   73 ++++--
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 R/plot.im.R                  |   38 +--
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 225 files changed, 5014 insertions(+), 1846 deletions(-)

More information about spatstat at CRAN
Permanent link

Package restatapi updated to version 0.6.2 with previous version 0.6.0 dated 2019-12-05

Title: Search and Retrieve Data from Eurostat Database
Description: Eurostat is the statistical office of the European Union and provides high quality statistics for Europe. Large set of the data is disseminated through the Eurostat database (<https://ec.europa.eu/eurostat/data/database>). The tools are using the REST API with the Statistical Data and Metadata eXchange (SDMX <https://sdmx.org>) Web Services (<https://ec.europa.eu/eurostat/web/sdmx-web-services/about-this-service>) to search and download data from the Eurostat database using the SDMX standard.
Author: Mátyás Mészáros [aut, cre]
Maintainer: Mátyás Mészáros <matyas.meszaros@ec.europa.eu>

Diff between restatapi versions 0.6.0 dated 2019-12-05 and 0.6.2 dated 2019-12-10

 DESCRIPTION               |    8 ++++----
 MD5                       |   14 +++++++-------
 R/get_eurostat_data.R     |   13 ++++++++++---
 R/load_cfg.R              |    9 +++++----
 R/put_eurostat_cache.R    |    4 +++-
 README.md                 |    4 ++--
 man/get_eurostat_data.Rd  |    7 +++++--
 man/put_eurostat_cache.Rd |    4 +++-
 8 files changed, 39 insertions(+), 24 deletions(-)

More information about restatapi at CRAN
Permanent link

Package rangeBuilder updated to version 1.5 with previous version 1.4 dated 2017-05-31

Title: Occurrence Filtering, Geographic and Taxonomic Standardization and Generation of Species Range Polygons
Description: Provides tools for filtering occurrence records, generating alpha-hull-derived range polygons and mapping species distributions.
Author: Pascal Title
Maintainer: Pascal Title <ptitle@umich.edu>

Diff between rangeBuilder versions 1.4 dated 2017-05-31 and 1.5 dated 2019-12-10

 rangeBuilder-1.4/rangeBuilder/src/rangeBuilder_init.c     |only
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 rangeBuilder-1.5/rangeBuilder/man/acceptedAndSynonyms.Rd  |    4 +-
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 rangeBuilder-1.5/rangeBuilder/src/RcppExports.cpp         |   12 ++++++
 14 files changed, 53 insertions(+), 44 deletions(-)

More information about rangeBuilder at CRAN
Permanent link

Package pubh updated to version 1.1.3 with previous version 1.1.2 dated 2019-12-07

Title: A Toolbox for Public Health and Epidemiology
Description: A toolbox for making R functions and capabilities more accessible to students and professionals from Epidemiology and Public Health related disciplines. Includes a function to report coefficients and confidence intervals from models using robust standard errors (when available), functions that expand 'ggplot2' plots and functions relevant for introductory papers in Epidemiology or Public Health. Please note that use of the provided data sets is for educational purposes only.
Author: Josie Athens [aut, cre], Frank Harell [ctb], John Fox [ctb], R-Core [ctb]
Maintainer: Josie Athens <josie.athens@otago.ac.nz>

Diff between pubh versions 1.1.2 dated 2019-12-07 and 1.1.3 dated 2019-12-10

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Package plyr updated to version 1.8.5 with previous version 1.8.4 dated 2016-06-13

Title: Tools for Splitting, Applying and Combining Data
Description: A set of tools that solves a common set of problems: you need to break a big problem down into manageable pieces, operate on each piece and then put all the pieces back together. For example, you might want to fit a model to each spatial location or time point in your study, summarise data by panels or collapse high-dimensional arrays to simpler summary statistics. The development of 'plyr' has been generously supported by 'Becton Dickinson'.
Author: Hadley Wickham [aut, cre]
Maintainer: Hadley Wickham <hadley@rstudio.com>

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Package multcomp updated to version 1.4-11 with previous version 1.4-10 dated 2019-03-05

Title: Simultaneous Inference in General Parametric Models
Description: Simultaneous tests and confidence intervals for general linear hypotheses in parametric models, including linear, generalized linear, linear mixed effects, and survival models. The package includes demos reproducing analyzes presented in the book "Multiple Comparisons Using R" (Bretz, Hothorn, Westfall, 2010, CRC Press).
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>), Frank Bretz [aut], Peter Westfall [aut], Richard M. Heiberger [ctb], Andre Schuetzenmeister [ctb], Susan Scheibe [ctb]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between multcomp versions 1.4-10 dated 2019-03-05 and 1.4-11 dated 2019-12-10

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Package CMplot updated to version 3.5.1 with previous version 3.4.0 dated 2019-09-05

Title: Circle Manhattan Plot
Description: Manhattan plot, a type of scatter plot, was widely used to display the association results. However, it is usually time-consuming and laborious for a non-specialist user to write scripts and adjust parameters of an elaborate plot. Moreover, the ever-growing traits measured have necessitated the integration of results from different Genome-wide association study researches. Circle Manhattan Plot is the first open R package that can lay out. Genome-wide association study P-value results in both traditional rectangular patterns, QQ-plot and novel circular ones. United in only one bull's eye style plot, association results from multiple traits can be compared interactively, thereby to reveal both similarities and differences between signals. Additional functions include: hightlight signals, a group of SNPs, chromosome visualization and candidate genes around SNPs.
Author: LiLin-Yin
Maintainer: LiLin-Yin <ylilin@163.com>

Diff between CMplot versions 3.4.0 dated 2019-09-05 and 3.5.1 dated 2019-12-10

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Package sna updated to version 2.5 with previous version 2.4 dated 2016-08-08

Title: Tools for Social Network Analysis
Description: A range of tools for social network analysis, including node and graph-level indices, structural distance and covariance methods, structural equivalence detection, network regression, random graph generation, and 2D/3D network visualization.
Author: Carter T. Butts [aut, cre, cph]
Maintainer: Carter T. Butts <buttsc@uci.edu>

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Package RLumModel (with last version 0.2.4) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2019-08-16 0.2.4
2017-11-22 0.2.3
2017-10-13 0.2.2
2017-04-13 0.2.1
2017-01-20 0.2.0
2016-09-02 0.1.2
2016-05-03 0.1.1
2016-02-03 0.1.0

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Package hgam (with last version 0.1-2) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2013-05-13 0.1-2
2013-02-08 0.1-1
2010-02-09 0.1-0

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Package sse updated to version 0.7-15 with previous version 0.7-13 dated 2019-08-28

Title: Sample Size Estimation
Description: Provides functions to evaluate user-defined power functions for a parameter range, and draws a sensitivity plot. It also provides a resampling procedure for semi-parametric sample size estimation and methods for adding information to a Sweave report.
Author: Thomas Fabbro [aut, cre]
Maintainer: Thomas Fabbro <thomas.fabbro@unibas.ch>

Diff between sse versions 0.7-13 dated 2019-08-28 and 0.7-15 dated 2019-12-10

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Package RiverLoad updated to version 1.0.2 with previous version 1.0.1 dated 2019-04-03

Title: Load Estimation of River Compounds with Different Methods
Description: Implements several of the most popular load estimation procedures, including averaging methods, ratio estimators and regression methods. The package provides an easy-to-use tool to rapidly calculate the load for various compounds and to compare different methods. The package also supplies additional functions to easily organize and analyze the data.
Author: Veronica Nava [aut, cre], Martina Patelli [ctb], Marco Rotiroti [ctb], Barbara Leoni [ctb]
Maintainer: Veronica Nava <veronicanava245@gmail.com>

Diff between RiverLoad versions 1.0.1 dated 2019-04-03 and 1.0.2 dated 2019-12-10

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Package MLGL updated to version 0.6 with previous version 0.5 dated 2018-10-14

Title: Multi-Layer Group-Lasso
Description: It implements a new procedure of variable selection in the context of redundancy between explanatory variables, which holds true with high dimensional data (Grimonprez et al. (2018) <https://hal.inria.fr/hal-01857242>).
Author: Quentin Grimonprez [aut, cre], Samuel Blanck [ctb], Alain Celisse [ths], Guillemette Marot [ths], Yi Yang [ctb], Hui Zou [ctb]
Maintainer: Quentin Grimonprez <quentin.grimonprez@inria.fr>

Diff between MLGL versions 0.5 dated 2018-10-14 and 0.6 dated 2019-12-10

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New package dann with initial version 0.1.0
Package: dann
Type: Package
Title: Discriminant Adaptive Nearest Neighbor Classification
Version: 0.1.0
Author: Greg McMahan
Maintainer: Greg McMahan <gmcmacran@gmail.com>
Description: Discriminant Adaptive Nearest Neighbor Classification is a variation of k nearest neighbors where the neighborhood is elongated along class boundaries. This package implements dann and sub_dann from Hastie (1995) <https://web.stanford.edu/~hastie/Papers/dann_IEEE.pdf>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: MASS (>= 7.3), compiler (>= 3.5.3), stats (>= 3.5.3), tibble (>= 2.1.1), dplyr (>= 0.8.0.1), ggplot2 (>= 3.1.1), stringr (>= 1.4.0), purrr (>= 0.3.2), magrittr (>= 1.5), rlang (>= 0.3.4), mlbench (>= 2.1), fpc (>= 2.1-11.1)
RoxygenNote: 6.1.1
Suggests: testthat, knitr, rmarkdown, covr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-12-04 02:59:59 UTC; gmcma
Repository: CRAN
Date/Publication: 2019-12-10 09:20:02 UTC

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New package bnma with initial version 1.0.0
Package: bnma
Type: Package
Title: Bayesian Network Meta-Analysis using 'JAGS'
Version: 1.0.0
Depends: R (>= 2.10)
Imports: rjags (>= 4-6), graphics, stats, utils, coda (>= 0.13), ggplot2, grid, igraph
Authors@R: c( person("Michael", "Seo", email = "swj8874@gmail.com", role = c("aut", "cre")), person("Christopher", "Schmid", email = "christopher_schmid@brown.edu", role = "aut"))
Description: Network meta-analyses using Bayesian framework following Dias et al. (2013) <DOI:10.1177/0272989X12458724>. Based on the data input, creates prior, model file, and initial values needed to run models in 'rjags'. Able to handle binomial, normal and multinomial arm-based data. Can handle multi-arm trials and includes methods to incorporate covariate and baseline risk effects. Includes standard diagnostics and visualization tools to evaluate the results.
License: GPL-3
LazyData: true
RoxygenNote: 7.0.0
Encoding: UTF-8
VignetteBuilder: knitr
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2019-12-04 02:04:30 UTC; mike
Author: Michael Seo [aut, cre], Christopher Schmid [aut]
Maintainer: Michael Seo <swj8874@gmail.com>
Repository: CRAN
Date/Publication: 2019-12-10 09:10:02 UTC

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Package gwsem updated to version 0.1.8 with previous version 0.1.7 dated 2019-12-03

Title: Genome-Wide Structural Equation Modeling
Description: Melds genome-wide association tests with structural equation modeling (SEM) using 'OpenMx'. This package contains low-level C/C++ code to rapidly read genetic data encoded in U.K. Biobank or 'plink' formats. Prebuilt modeling options include one and two factor models. Alternately, analyses may utilize arbitrary, user-provided SEMs. See Verhulst, Maes, & Neale (2017) <doi:10.1007/s10519-017-9842-6> for details. An updated manuscript is in preparation.
Author: Joshua N. Pritikin [aut, cre], Bradley Verhulst [cph], Gavin Band [cph], Yann Collet [cph], Facebook, Inc. [cph], Yuta Mori [cph], Shaun Purcell [cph], Christopher Chang [cph], Wojciech Mula [cph], Kim Walisch [cph]
Maintainer: Joshua N. Pritikin <jpritikin@pobox.com>

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Package venn updated to version 1.8 with previous version 1.7 dated 2018-07-31

Title: Draw Venn Diagrams
Description: Draws and displays Venn diagrams up to 7 sets, and any Boolean union of set intersections.
Author: Adrian Dusa [aut, cre, cph]
Maintainer: Adrian Dusa <dusa.adrian@unibuc.ro>

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Package npreg updated to version 1.0-1 with previous version 1.0-0 dated 2019-08-25

Title: Nonparametric Regression
Description: Multiple and generalized nonparametric regression using smoothing spline ANOVA models and generalized additive models. Includes support for Gaussian and non-Gaussian responses, smoothers for multiple types of predictors, interactions between smoothers of mixed types, and eight different methods for smoothing parameter selection.
Author: Nathaniel E. Helwig <helwig@umn.edu>
Maintainer: Nathaniel E. Helwig <helwig@umn.edu>

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Package nlme updated to version 3.1-143 with previous version 3.1-142 dated 2019-11-07

Title: Linear and Nonlinear Mixed Effects Models
Description: Fit and compare Gaussian linear and nonlinear mixed-effects models.
Author: José Pinheiro [aut] (S version), Douglas Bates [aut] (up to 2007), Saikat DebRoy [ctb] (up to 2002), Deepayan Sarkar [ctb] (up to 2005), EISPACK authors [ctb] (src/rs.f), Siem Heisterkamp [ctb] (Author fixed sigma), Bert Van Willigen [ctb] (Programmer fixed sigma), R-core [aut, cre]
Maintainer: R-core <R-core@R-project.org>

Diff between nlme versions 3.1-142 dated 2019-11-07 and 3.1-143 dated 2019-12-10

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 DESCRIPTION         |    8 ++++----
 MD5                 |    6 +++---
 tests/augPred_lab.R |    2 +-
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Package mvmeta updated to version 1.0.2 with previous version 0.4.11 dated 2018-03-07

Title: Multivariate and Univariate Meta-Analysis and Meta-Regression
Description: Collection of functions to perform fixed and random-effects multivariate and univariate meta-analysis and meta-regression.
Author: Antonio Gasparrini
Maintainer: Antonio Gasparrini <antonio.gasparrini@lshtm.ac.uk>

Diff between mvmeta versions 0.4.11 dated 2018-03-07 and 1.0.2 dated 2019-12-10

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Package forward updated to version 1.0.5 with previous version 1.0.4 dated 2018-07-25

Title: Robust Analysis using Forward Search
Description: Robust analysis using forward search in linear and generalized linear regression models, as described in Atkinson, A.C. and Riani, M. (2000), Robust Diagnostic Regression Analysis, First Edition. New York: Springer.
Author: Originally written for S-Plus by: Kjell Konis <kkonis@insightful.com> and Marco Riani <mriani@unipr.it> Ported to R by Luca Scrucca <luca@stat.unipg.it> Ken Beath <ken.beath@mq.edu.au>
Maintainer: Ken Beath <ken.beath@mq.edu.au>

Diff between forward versions 1.0.4 dated 2018-07-25 and 1.0.5 dated 2019-12-10

 DESCRIPTION |    8 
 MD5         |    6 
 R/forward.R | 5210 ++++++++++++++++++++++++++++++------------------------------
 inst/NEWS   |    4 
 4 files changed, 2616 insertions(+), 2612 deletions(-)

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