Mon, 08 Apr 2019

Package essHist updated to version 1.2.1 with previous version 1.2.0 dated 2019-03-10

Title: The Essential Histogram
Description: Provide an optimal histogram, in the sense of probability density estimation and features detection, by means of multiscale variational inference. In other words, the resulting histogram servers as an optimal density estimator, and meanwhile recovers the features, such as increases or modes, with both false positive and false negative controls. Moreover, it provides a parsimonious representation in terms of the number of blocks, which simplifies data interpretation. The only assumption for the method is that data points are independent and identically distributed, so it applies to fairly general situations, including continuous distributions, discrete distributions, and mixtures of both. For details see Li, Munk, Sieling and Walther (2016) <arXiv:1612.07216>.
Author: Housen Li [aut, cre], Hannes Sieling [aut]
Maintainer: Housen Li <housen.li@outlook.com>

Diff between essHist versions 1.2.0 dated 2019-03-10 and 1.2.1 dated 2019-04-08

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More information about essHist at CRAN
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Package taxotools updated to version 0.0.20 with previous version 0.0.11 dated 2019-03-05

Title: Tools to Handle Taxonomic Lists
Description: Some tools to work with taxonomic name lists.
Author: Vijay Barve [aut, cre] (<https://orcid.org/0000-0002-4852-2567>)
Maintainer: Vijay Barve <vijay.barve@gmail.com>

Diff between taxotools versions 0.0.11 dated 2019-03-05 and 0.0.20 dated 2019-04-08

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Package simLife updated to version 0.5.2 with previous version 0.5.1 dated 2018-09-27

Title: Simulation of Fatigue Lifetimes
Description: Provides methods for simulation and analysis of a very general fatigue lifetime model for (metal matrix) composite materials.
Author: Markus Baaske [aut, cre], Felix Ballani [aut, ctb]
Maintainer: Markus Baaske <markus.baaske@uni-jena.de>

Diff between simLife versions 0.5.1 dated 2018-09-27 and 0.5.2 dated 2019-04-08

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More information about simLife at CRAN
Permanent link

Package prioritizr updated to version 4.0.3 with previous version 4.0.2 dated 2018-06-28

Title: Systematic Conservation Prioritization in R
Description: Conservation prioritization using integer programming techniques. To solve large-scale problems, users should install the 'gurobi' optimizer (available from <http://www.gurobi.com/>).
Author: Jeffrey O Hanson [aut], Richard Schuster [aut, cre], Nina Morrell [aut], Matthew Strimas-Mackey [aut], Matthew E Watts [aut], Peter Arcese [aut], Joeseph Bennett [aut], Hugh P Possingham [aut]
Maintainer: Richard Schuster <mail@richard-schuster.com>

Diff between prioritizr versions 4.0.2 dated 2018-06-28 and 4.0.3 dated 2019-04-08

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More information about prioritizr at CRAN
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Package jtools updated to version 2.0.1 with previous version 2.0.0 dated 2019-02-08

Title: Analysis and Presentation of Social Scientific Data
Description: This is a collection of tools that the author (Jacob) has written for the purpose of more efficiently understanding and sharing the results of (primarily) regression analyses. There are also a number of miscellaneous functions for statistical and programming purposes. Just about everything supports models from the survey package.
Author: Jacob A. Long [aut, cre] (<https://orcid.org/0000-0002-1582-6214>)
Maintainer: Jacob A. Long <long.1377@osu.edu>

Diff between jtools versions 2.0.0 dated 2019-02-08 and 2.0.1 dated 2019-04-08

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Package fingertipsR updated to version 0.2.2 with previous version 0.2.1 dated 2019-03-07

Title: Fingertips Data for Public Health
Description: Fingertips (<http://fingertips.phe.org.uk/>) contains data for many indicators of public health in England. The underlying data is now more easily accessible by making use of the API.
Author: Sebastian Fox [aut, cre], Julian Flowers [aut, ctb], Simon Thelwall [ctb] (<https://orcid.org/0000-0002-0434-2724>), Duncan Gormansway [ctb], Carl Ganz [ctb], David Whiting [ctb], Crown Copyright 2018 [cph]
Maintainer: Sebastian Fox <sebastian.fox@phe.gov.uk>

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Package fingertipscharts updated to version 0.0.5 with previous version 0.0.4 dated 2019-02-07

Title: Produce Charts that you See on the Fingertips Website
Description: Use Fingertips charts to recreate the visualisations that are displayed on the Fingertips website (<http://fingertips.phe.org.uk/>).
Author: Sebastian Fox [aut, cre]
Maintainer: Sebastian Fox <sebastian.fox@phe.gov.uk>

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Package L0Learn updated to version 1.1.0 with previous version 1.0.8 dated 2018-10-28

Title: Fast Algorithms for Best Subset Selection
Description: Highly optimized toolkit for approximately solving L0-regularized learning problems (aka best subset selection). The algorithms are based on coordinate descent and local combinatorial search. For more details, check the paper by Hazimeh and Mazumder (2018) <arXiv:1803.01454>; the link is provided in the URL field below.
Author: Hussein Hazimeh, Rahul Mazumder
Maintainer: Hussein Hazimeh <hazimeh@mit.edu>

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Package devtools updated to version 2.0.2 with previous version 2.0.1 dated 2018-10-26

Title: Tools to Make Developing R Packages Easier
Description: Collection of package development tools.
Author: Hadley Wickham [aut], Jim Hester [aut, cre], Winston Chang [aut], RStudio [cph], R Core team [ctb] (Some namespace and vignette code extracted from base R)
Maintainer: Jim Hester <james.hester@rstudio.com>

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Package comf updated to version 0.1.9 with previous version 0.1.8 dated 2019-01-06

Title: Functions for Thermal Comfort Research
Description: Functions to calculate various common and less common thermal comfort indices, convert physical variables, and evaluate the performance of thermal comfort indices.
Author: Marcel Schweiker [aut, cre] and Sophia Mueller [aut] and Michael Kleber [ctr] and Boris Kingma [ctr] and Masanori Shukuya [ctr]
Maintainer: Marcel Schweiker <marcel.schweiker@kit.edu>

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Package sboost updated to version 0.1.1 with previous version 0.1.0 dated 2018-10-28

Title: Machine Learning with AdaBoost on Decision Stumps
Description: Creates classifier for binary outcomes using Adaptive Boosting (AdaBoost) algorithm on decision stumps with a fast C++ implementation. For a description of AdaBoost, see Freund and Schapire (1997) <doi:10.1006/jcss.1997.1504>. This type of classifier is nonlinear, but easy to interpret and visualize. Feature vectors may be a combination of continuous (numeric) and categorical (string, factor) elements. Methods for classifier assessment, predictions, and cross-validation also included.
Author: Jadon Wagstaff [aut, cre]
Maintainer: Jadon Wagstaff <jadonw@gmail.com>

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Package metacoder updated to version 0.3.2 with previous version 0.3.1 dated 2019-01-04

Title: Tools for Parsing, Manipulating, and Graphing Taxonomic Abundance Data
Description: A set of tools for parsing, manipulating, and graphing data classified by a hierarchy (e.g. a taxonomy).
Author: Zachary Foster [aut, cre], Niklaus Grunwald [ths], Rob Gilmore [ctb]
Maintainer: Zachary Foster <zacharyfoster1989@gmail.com>

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Package evolqg updated to version 0.2-6 with previous version 0.2-5 dated 2017-02-01

Title: Tools for Evolutionary Quantitative Genetics
Description: Provides functions for covariance matrix comparisons, estimation of repeatabilities in measurements and matrices, and general evolutionary quantitative genetics tools.
Author: Ana Paula Assis, Diogo Melo, Edgar Zanella, Fabio Machado, Guilherme Garcia
Maintainer: Diogo Melo <diogro@usp.br>

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Package spatialrisk updated to version 0.6.0 with previous version 0.5.1 dated 2019-03-01

Title: Calculating Concentration Risk under Solvency II
Description: Methods for determining spatial risk, in particular calculating the maximum value of insured fire risk policies of all buildings that are partly or fully located within circle of a radius of 200m.
Author: Martin Haringa
Maintainer: Martin Haringa <mtharinga@gmail.com>

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Package GetHFData updated to version 1.7 with previous version 1.6 dated 2018-10-10

Title: Download and Aggregate High Frequency Trading Data from Bovespa
Description: Downloads and aggregates high frequency trading data for Brazilian instruments directly from Bovespa ftp site <ftp://ftp.bmf.com.br/MarketData/>.
Author: Marcelo Perlin [aut, cre], Henrique Ramos [ctb]
Maintainer: Marcelo Perlin <marceloperlin@gmail.com>

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Package damr updated to version 0.3.3 with previous version 0.3.1 dated 2018-05-15

Title: Interface to Drosophila Activity Monitor System Result Files
Description: Loads behavioural data from the widely used Drosophila Activity Monitor System (DAMS, TriKinetics) into the rethomics framework.
Author: Quentin Geissmann [aut, cre], Hadley Wickham [aut]
Maintainer: Quentin Geissmann <qgeissmann@gmail.com>

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Package TreeSim updated to version 2.4 with previous version 2.3 dated 2017-03-20

Title: Simulating Phylogenetic Trees
Description: Simulation methods for phylogenetic trees where (i) all tips are sampled at one time point or (ii) tips are sampled sequentially through time. (i) For sampling at one time point, simulations are performed under a constant rate birth-death process, conditioned on having a fixed number of final tips (sim.bd.taxa()), or a fixed age (sim.bd.age()), or a fixed age and number of tips (sim.bd.taxa.age()). When conditioning on the number of final tips, the method allows for shifts in rates and mass extinction events during the birth-death process (sim.rateshift.taxa()). The function sim.bd.age() (and sim.rateshift.taxa() without extinction) allow the speciation rate to change in a density-dependent way. The LTT plots of the simulations can be displayed using LTT.plot(), LTT.plot.gen() and LTT.average.root(). TreeSim further samples trees with n final tips from a set of trees generated by the common sampling algorithm stopping when a fixed number m>>n of tips is first reached (sim.gsa.taxa()). This latter method is appropriate for m-tip trees generated under a big class of models (details in the sim.gsa.taxa() man page). For incomplete phylogeny, the missing speciation events can be added through simulations (corsim()). (ii) sim.rateshifts.taxa() is generalized to sim.bdsky.stt() for serially sampled trees, where the trees are conditioned on either the number of sampled tips or the age. Furthermore, for a multitype-branching process with sequential sampling, trees on a fixed number of tips can be simulated using sim.bdtypes.stt.taxa(). This function further allows to simulate under epidemiological models with an exposed class. The function sim.genespeciestree() simulates coalescent gene trees within birth-death species trees, and sim.genetree() simulates coalescent gene trees.
Author: Tanja Stadler
Maintainer: Tanja Stadler <tanja.stadler@bsse.ethz.ch>

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Package RobExtremes updated to version 1.2.0 with previous version 1.1.0 dated 2018-08-03

Title: Optimally Robust Estimation for Extreme Value Distributions
Description: Optimally robust estimation for extreme value distributions using S4 classes and methods (based on packages 'distr', 'distrEx', 'distrMod', 'RobAStBase', and 'ROptEst').
Author: Nataliya Horbenko [aut, cph], Bernhard Spangl [ctb] (contributed smoothed grid values of the Lagrange multipliers), Sascha Desmettre [ctb] (contributed smoothed grid values of the Lagrange multipliers), Eugen Massini [ctb] (contributed an interactive smoothing routine for smoothing the Lagrange multipliers and smoothed grid values of the Lagrange multipliers), Daria Pupashenko [ctb] (contributed MDE-estimation for GEV distribution in the framework of her PhD thesis 2011--14), Gerald Kroisandt [ctb] (contributed testing routines), Matthias Kohl [aut, cph], Peter Ruckdeschel [cre, aut, cph]
Maintainer: Peter Ruckdeschel <peter.ruckdeschel@uni-oldenburg.de>

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Package georob updated to version 0.3-9 with previous version 0.3-8 dated 2019-03-29

Title: Robust Geostatistical Analysis of Spatial Data
Description: Provides functions for efficiently fitting linear models with spatially correlated errors by robust and Gaussian (Restricted) Maximum Likelihood and for computing robust and customary point and block external-drift Kriging predictions, along with utility functions for variogram modelling in ad hoc geostatistical analyses, model building, model evaluation by cross-validation, (conditional) simulation of Gaussian processes, unbiased back-transformation of Kriging predictions of log-transformed data.
Author: Andreas Papritz [cre, aut], Cornelia Schwierz [ctb]
Maintainer: Andreas Papritz <andreas.papritz@env.ethz.ch>

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Package emdi updated to version 1.1.5 with previous version 1.1.4 dated 2018-10-10

Title: Estimating and Mapping Disaggregated Indicators
Description: Functions that support estimating, assessing and mapping regional disaggregated indicators. So far, estimation methods comprise direct estimation and the model-based approach Empirical Best Prediction (see "Small area estimation of poverty indicators" by Molina and Rao (2010) <doi:10.1002/cjs.10051>), as well as their precision estimates. The assessment of the used model is supported by a summary and diagnostic plots. For a suitable presentation of estimates, map plots can be easily created. Furthermore, results can easily be exported to excel.
Author: Ann-Kristin Kreutzmann [aut], Soeren Pannier [aut, cre], Natalia Rojas-Perilla [aut], Timo Schmid [aut], Matthias Templ [aut], Nikos Tzavidis [aut]
Maintainer: Soeren Pannier <soeren.pannier@fu-berlin.de>

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Package tvReg updated to version 0.4.1 with previous version 0.4.0 dated 2019-03-27

Title: Time-Varying Coefficient Linear Regression for Single and Multi-Equations
Description: Fitting time-varying coefficient models both for single and multi-equation regressions, using kernel smoothing techniques.
Author: Isabel Casas [aut, cre], Ruben Fernandez-Casal [aut]
Maintainer: Isabel Casas <casasis@gmail.com>

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Package SMUT updated to version 1.0.1 with previous version 1.0 dated 2018-10-08

Title: Multi-SNP Mediation Intersection-Union Test
Description: Testing the mediation effect of multiple SNPs on an outcome through a mediator.
Author: Wujuan Zhong
Maintainer: Wujuan Zhong <zhongwujuan@gmail.com>

Diff between SMUT versions 1.0 dated 2018-10-08 and 1.0.1 dated 2019-04-08

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Package MANOVA.RM updated to version 0.3.2 with previous version 0.3.1 dated 2018-08-14

Title: Analysis of Multivariate Data and Repeated Measures Designs
Description: Implemented are various tests for semi-parametric repeated measures and general MANOVA designs that do neither assume multivariate normality nor covariance homogeneity, i.e., the procedures are applicable for a wide range of general multivariate factorial designs. Furthermore, post-hoc comparisons are provided for the multivariate analyses. Friedrich, S., Konietschke, F. and Pauly, M. (2018) <arXiv:1801.08002>.
Author: Sarah Friedrich, Frank Konietschke, Markus Pauly
Maintainer: Sarah Friedrich <sarah.friedrich@alumni.uni-ulm.de>

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Package KenSyn updated to version 0.3 with previous version 0.2 dated 2017-12-10

Title: Knowledge Synthesis in Agriculture - From Experimental Network to Meta-Analysis
Description: Demo and dataset accompaying the books : De l'analyse des réseaux expérimentaux à la méta-analyse: Méthodes et applications avec le logiciel R pour les sciences agronomiques et environnementales (Published 2018-06-28, Quae, for french version) by David Makowski, Francois Piraux and Francois Brun - <https://www.quae.com/produit/1514/9782759228164/de-l-analyse-des-reseaux-experimentaux-a-la-meta-analyse> Knowledge Synthesis in Agriculture : from Experimental Network to Meta-Analysis (in preparation for 2018-06, Springer , for English version) by David Makowski, Francois Piraux and Francois Brun A full description of all the material is in both books. ACKNOWLEDGMENTS : The French network "RMT modeling and data analysis for agriculture" (<http://www.modelia.org>) have contributed to the development of this R package. This project and network are lead by ACTA (French Technical Institute for Agriculture) and was funded by a grant from the Ministry of Agriculture and Fishing of France.
Author: David Makowski (INRA) [aut], Francois Piraux (Arvalis) [aut], Francois Brun (ACTA) [aut, cre]
Maintainer: Francois Brun (ACTA) <francois.brun@acta.asso.fr>

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Package IncDTW updated to version 1.1.0 with previous version 1.0.5 dated 2019-01-03

Title: Incremental Calculation of Dynamic Time Warping
Description: The Dynamic Time Warping (DTW) distance measure for time series allows non-linear alignments of time series to match similar patterns in time series of different lengths and or different speeds. IncDTW is characterized by (1) the incremental calculation of DTW (reduces runtime complexity to a linear level for updating the DTW distance) - especially for life data streams or subsequence matching, (2) the vector based implementation of DTW which is faster because no matrices are allocated (reduces the space complexity from a quadratic to a linear level in the number of observations) - for all runtime intensive DTW computations, (3) the subsequence matching algorithm runDTW, that efficiently finds the k-NN to a query pattern in a long time series, and (4) C++ in the heart. For details about DTW see the original paper "Dynamic programming algorithm optimization for spoken word recognition" by Sakoe and Chiba (1978) <DOI:10.1109/TASSP.1978.1163055>.
Author: Maximilian Leodolter
Maintainer: Maximilian Leodolter <maximilian.leodolter@gmail.com>

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Package cgraph updated to version 4.0.3 with previous version 4.0.2 dated 2019-04-06

Title: Computational Graphs
Description: Allows to create, evaluate, and differentiate computational graphs in R. A computational graph is a graph representation of a multivariate function decomposed by its (elementary) operations. Nodes in the graph represent arrays while edges represent dependencies among the arrays. An advantage of expressing a function as a computational graph is that this enables to differentiate the function by automatic differentiation. The 'cgraph' package supports various operations including basic arithmetic, trigonometry operations, and linear algebra operations. It differentiates computational graphs by reverse automatic differentiation. The flexible architecture of the package makes it applicable to solve a variety of problems including local sensitivity analysis, gradient-based optimization, and machine learning.
Author: Ron Triepels
Maintainer: Ron Triepels <dev@cgraph.org>

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Package openair updated to version 2.6-5 with previous version 2.6-4 dated 2019-03-28

Title: Tools for the Analysis of Air Pollution Data
Description: Tools to analyse, interpret and understand air pollution data. Data are typically hourly time series and both monitoring data and dispersion model output can be analysed. Many functions can also be applied to other data, including meteorological and traffic data.
Author: David Carslaw [aut, cre], Karl Ropkins [aut]
Maintainer: David Carslaw <david.carslaw@york.ac.uk>

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Package lslx updated to version 0.6.5 with previous version 0.6.4 dated 2018-11-10

Title: Semi-Confirmatory Structural Equation Modeling via Penalized Likelihood
Description: Fits semi-confirmatory structural equation modeling (SEM) via penalized likelihood (PL) with LASSO or minimax concave penalty (MCP).
Author: Po-Hsien Huang [cre, aut], Wen-Hsin Hu [aut]
Maintainer: Po-Hsien Huang <psyphh@gmail.com>

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Package Spectrum updated to version 0.5 with previous version 0.4 dated 2019-03-15

Title: Fast Adaptive Spectral Clustering for Single and Multi-View Data
Description: A self-tuning spectral clustering method for single or multi-view data. 'Spectrum' uses a new type of adaptive density aware kernel that strengthens local connections in the graph. It uses a tensor product graph data integration and diffusion procedure to integrate different data sources and reduce noise. 'Spectrum' analyses eigenvector variance or distribution to determine the number of clusters. The method is well suited for a wide range of data, including both Gaussian and non-Gaussian structures.
Author: Christopher R John, David Watson
Maintainer: Christopher R John <chris.r.john86@gmail.com>

Diff between Spectrum versions 0.4 dated 2019-03-15 and 0.5 dated 2019-04-08

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New package PDFEstimator with initial version 0.1-2
Package: PDFEstimator
Version: 0.1-2
Date: 2019-04-07
Title: Nonparametric Probability Density Estimator
Author: Jenny Farmer <jfarmer6@uncc.edu> and Donald Jacobs <djacobs1@uncc.ecu>
Maintainer: Jenny Farmer <jfarmer6@uncc.edu>
Description: Farmer, J., D. Jacobs (2108) <DOI:10.1371/journal.pone.0196937>. A nonparametric density estimator based on the maximum-entropy method. Accurately predicts a probability density function (PDF) for random data using a novel iterative scoring function to determine the best fit without overfitting to the sample.
License: GPL (>= 2)
NeedsCompilation: yes
Packaged: 2019-04-08 01:15:27 UTC; jenny
Repository: CRAN
Date/Publication: 2019-04-08 12:02:46 UTC

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Package huge updated to version 1.3.2 with previous version 1.3.1 dated 2019-03-11

Title: High-Dimensional Undirected Graph Estimation
Description: Provides a general framework for high-dimensional undirected graph estimation. It integrates data preprocessing, neighborhood screening, graph estimation, and model selection techniques into a pipeline. In preprocessing stage, the nonparanormal(npn) transformation is applied to help relax the normality assumption. In the graph estimation stage, the graph structure is estimated by Meinshausen-Buhlmann graph estimation or the graphical lasso, and both methods can be further accelerated by the lossy screening rule preselecting the neighborhood of each variable by correlation thresholding. We target on high-dimensional data analysis usually d >> n, and the computation is memory-optimized using the sparse matrix output. We also provide a computationally efficient approach, correlation thresholding graph estimation. Three regularization/thresholding parameter selection methods are included in this package: (1)stability approach for regularization selection (2) rotation information criterion (3) extended Bayesian information criterion which is only available for the graphical lasso.
Author: Haoming Jiang, Xinyu Fei, Han Liu, Kathryn Roeder, John Lafferty, Larry Wasserman, Xingguo Li, and Tuo Zhao
Maintainer: Haoming Jiang <jianghm.ustc@gmail.com>

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Package ProjectManagement updated to version 1.2.1 with previous version 1.1 dated 2019-01-07

Title: Management of Deterministic and Stochastic Projects
Description: Management problems of deterministic and stochastic projects. It obtains the duration of a project and the appropriate slack for each activity in a deterministic context. In addition it obtains a schedule of activities' time (Castro, Gómez & Tejada (2007) <doi:10.1016/j.orl.2007.01.003>). It also allows the management of resources. When the project is done, and the actual duration for each activity is known, then it can know how long the project is delayed and make a fair delivery of the delay between each activity (Bergantiños, Valencia-Toledo & Vidal-Puga (2018) <doi:10.1016/j.dam.2017.08.012>). In a stochastic context it can estimate the average duration of the project and plot the density of this duration, as well as, the density of the early and last times of the chosen activities. As in the deterministic case, it can make a distribution of the delay generated by observing the project already carried out.
Author: Juan Carlos Gonçalves Dosantos [aut, cre], Ignacio García Jurado [aut], Julián Costa Bouzas [aut]
Maintainer: Juan Carlos Gonçalves Dosantos <juan.carlos.goncalves@udc.es>

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Package KFAS updated to version 1.3.5 with previous version 1.3.4 dated 2019-02-03

Title: Kalman Filter and Smoother for Exponential Family State Space Models
Description: State space modelling is an efficient and flexible framework for statistical inference of a broad class of time series and other data. KFAS includes computationally efficient functions for Kalman filtering, smoothing, forecasting, and simulation of multivariate exponential family state space models, with observations from Gaussian, Poisson, binomial, negative binomial, and gamma distributions. See the paper by Helske (2017) <doi:10.18637/jss.v078.i10> for details.
Author: Jouni Helske [aut, cre] (<https://orcid.org/0000-0001-7130-793X>)
Maintainer: Jouni Helske <jouni.helske@iki.fi>

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Package gprofiler2 updated to version 0.1.2 with previous version 0.1.1 dated 2019-03-25

Title: Interface to the 'g:Profiler' Toolset
Description: A toolset for functional enrichment analysis and visualization, gene/protein/SNP identifier conversion and mapping orthologous genes across species via 'g:Profiler' (<https://biit.cs.ut.ee/gprofiler>). The main tools are: (1) 'g:GOSt' - functional enrichment analysis and visualization of gene lists; (2) 'g:Convert' - gene/protein/transcript identifier conversion across various namespaces; (3) 'g:Orth' - orthology search across species; (4) 'g:SNPense' - mapping SNP rs identifiers to chromosome positions, genes and variant effects This package is an R interface corresponding to the 2019 update of 'g:Profiler' and provides access to 'g:Profiler' for versions 'e94_eg41_p11' and higher. See the package 'gProfileR' for accessing older versions from the 'g:Profiler' toolset.
Author: Liis Kolberg <liis.kolberg@ut.ee>, Uku Raudvere <uku.raudvere@ut.ee>
Maintainer: Liis Kolberg <liis.kolberg@ut.ee>

Diff between gprofiler2 versions 0.1.1 dated 2019-03-25 and 0.1.2 dated 2019-04-08

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Package LeArEst updated to version 1.0.0 with previous version 0.2.0 dated 2018-05-08

Title: Border and Area Estimation of Data Measured with Additive Error
Description: Provides methods for estimating borders of uniform distribution on the interval (one-dimensional) and on the elliptical domain (two-dimensional) under measurement errors. For one-dimensional case, it also estimates the length of underlying uniform domain and tests the hypothesized length against two-sided or one-sided alternatives. For two-dimensional case, it estimates the area of underlying uniform domain. It works with numerical inputs as well as with pictures in JPG format.
Author: Mirta Bensic [aut], Safet Hamedovic [aut], Kristian Sabo [aut], Petar Taler [aut, cre]
Maintainer: Petar Taler <petar@mathos.hr>

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New package bayestestR with initial version 0.1.0
Package: bayestestR
Type: Package
Title: Understand and Describe Bayesian Models and Posterior Distributions
Version: 0.1.0
Authors@R: c( person("Dominique", "Makowski", email = "dom.makowski@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5375-9967")), person("Daniel", "Lüdecke", role = c("aut"), email = "d.luedecke@uke.de", comment = c(ORCID = "0000-0002-8895-3206")) )
Maintainer: Dominique Makowski <dom.makowski@gmail.com>
URL: https://github.com/easystats/bayestestR
BugReports: https://github.com/easystats/bayestestR/issues
Description: Provides utilities to describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion (Highest Density Interval - HDI; Kruschke, 2014 <doi:10.1016/B978-0-12-405888-0.09999-2>) and indices used for null-hypothesis testing (such as ROPE percentage and pd).
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0), stats
Imports: insight
Suggests: brms, broom, covr, dplyr, tidyr, ggplot2, ggridges, knitr, rmarkdown, rstanarm, stringr, testthat
RoxygenNote: 6.1.1
Language: en-GB
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-08 07:48:00 UTC; Dom
Author: Dominique Makowski [aut, cre] (<https://orcid.org/0000-0001-5375-9967>), Daniel Lüdecke [aut] (<https://orcid.org/0000-0002-8895-3206>)
Repository: CRAN
Date/Publication: 2019-04-08 09:42:41 UTC

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Package shinydashboardPlus updated to version 0.7.0 with previous version 0.6.0 dated 2018-09-20

Title: Add More 'AdminLTE2' Components to 'shinydashboard'
Description: Extend 'shinydashboard' with 'AdminLTE2' components. 'AdminLTE2' is a free 'Bootstrap 3' dashboard template available at <https://adminlte.io>. Customize boxes, add timelines and a lot more.
Author: David Granjon [aut, cre], RinteRface [cph], Almasaeed Studio [ctb, cph] (AdminLTE2 theme for Bootstrap 3), Guang Yang [ctb, cph] (ygdashboard original template), Winston Chang [ctb, cph] (Functions from shinydashboard), Petr Tichy [ctb, cph] (CSS preloader), Victor Perrier [ctb] (improved the shinydashboardPlusGallery)
Maintainer: David Granjon <dgranjon@ymail.com>

Diff between shinydashboardPlus versions 0.6.0 dated 2018-09-20 and 0.7.0 dated 2019-04-08

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Package rhub updated to version 1.1.1 with previous version 1.1.0 dated 2019-03-25

Title: Connect to 'R-hub'
Description: Run 'R CMD check' on any of the 'R-hub' (<https://builder.r-hub.io/>) architectures, from the command line. The current architectures include 'Windows', 'macOS', 'Solaris' and various 'Linux' distributions.
Author: Gábor Csárdi [aut, cre], Maëlle Salmon [aut] (<https://orcid.org/0000-0002-2815-0399>), R Consortium [fnd]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>

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Package mombf updated to version 2.2.1 with previous version 2.1.2 dated 2018-06-22

Title: Bayesian Model Selection and Averaging for Non-Local and Local Priors
Description: Bayesian model selection and averaging for regression and mixtures for non-local and selected local priors.
Author: David Rossell, John D. Cook, Donatello Telesca, P. Roebuck
Maintainer: David Rossell <rosselldavid@gmail.com>

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Package lagsarlmtree updated to version 1.0-1 with previous version 1.0-0 dated 2017-10-04

Title: Spatial Lag Model Trees
Description: Model-based linear model trees adjusting for spatial correlation using a simultaneous autoregressive spatial lag, Wagner and Zeileis (2019) <doi:10.1111/geer.12146>.
Author: Martin Wagner [aut], Achim Zeileis [aut, cre] (<https://orcid.org/0000-0003-0918-3766>), Roger Bivand [ctb] (<https://orcid.org/0000-0003-2392-6140>)
Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org>

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New package BayesSenMC with initial version 0.1.0
Package: BayesSenMC
Title: Different Models of Posterior Distributions of Adjusted Odds Ratio
Version: 0.1.0
Author: Jinhui Yang
Maintainer: Jinhui Yang <yangj2@carleton.edu>
Description: Generates different posterior distributions of adjusted odds ratio under different priors of sensitivity and specificity, and plots the models for comparison. It also provides estimations for the specifications of the models using diagnostics of exposure status with a non-linear mixed effects model. It implements the methods that are first proposed by Chu et al. (2006) <doi:10.1016/j.annepidem.2006.04.001> and Chu et al. (2010) <doi:10.1177/0272989X09353452>.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: dplyr, ggplot2, rstan (>= 2.16.2), lme4,
Depends: Rcpp (>= 0.12.19)
Suggests: gridExtra
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-08 03:46:58 UTC; james
Repository: CRAN
Date/Publication: 2019-04-08 08:52:53 UTC

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Package attempt updated to version 0.3.0 with previous version 0.2.1 dated 2018-04-20

Title: Tools for Defensive Programming
Description: Tools for defensive programming, inspired by 'purrr' mappers and based on 'rlang'.'attempt' extends and facilitates defensive programming by providing a consistent grammar, and provides a set of easy to use functions for common tests and conditions. 'attempt' only depends on 'rlang', and focuses on speed, so it can be easily integrated in other functions and used in data analysis.
Author: Colin Fay [aut, cre] (<https://orcid.org/0000-0001-7343-1846>)
Maintainer: Colin Fay <contact@colinfay.me>

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Package unival updated to version 1.0.2 with previous version 1.0.1 dated 2019-03-06

Title: Assessing Essential Unidimensionality Using External Validity Information
Description: Assess essential unidimensionality using external validity information using the procedure proposed by Ferrando & Lorenzo-Seva (2019) <doi:10.1177/0013164418824755>. Provides two indices for assessing differential and incremental validity, both based on a second-order modelling schema for the general factor.
Author: Pere Joan Ferrando, David Navarro-Gonzalez, Urbano Lorenzo-Seva
Maintainer: David Navarro-Gonzalez <david.navarro@urv.cat>

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Package icesTAF updated to version 2.3-0 with previous version 2.2-0 dated 2019-02-22

Title: Functions to Support the ICES Transparent Assessment Framework
Description: Functions to support the ICES Transparent Assessment Framework <http://taf.ices.dk> to organize data, methods, and results used in ICES assessments. ICES is an organization facilitating international collaboration in marine science.
Author: Arni Magnusson [aut, cre], Colin Millar [aut], Alexandros Kokkalis [ctb]
Maintainer: Arni Magnusson <arni.magnusson@ices.dk>

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Package ksNN (with last version 0.1.1) was removed from CRAN

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

2019-03-26 0.1.1
2019-03-24 0.1.0

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Package reinforcelearn (with last version 0.2.0) was removed from CRAN

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

2019-03-20 0.2.0
2018-01-03 0.1.0

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Package reportROC updated to version 3.3 with previous version 3.2 dated 2018-09-02

Title: An Easy Way to Report ROC Analysis
Description: Provides an easy way to report the results of ROC analysis, including: 1. an ROC curve. 2. the value of Cutoff, AUC (Area Under Curve), ACC (accuracy), SEN (sensitivity), SPE (specificity), PLR (positive likelihood ratio), NLR (negative likelihood ratio), PPV (positive predictive value), NPV (negative predictive value).
Author: Zhicheng Du, Yuantao Hao
Maintainer: Zhicheng Du<dgdzc@hotmail.com>

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Package pbdSLAP updated to version 0.2-5 with previous version 0.2-4 dated 2018-04-05

Title: Programming with Big Data -- Scalable Linear Algebra Packages
Description: Utilizing scalable linear algebra packages mainly including 'BLACS', 'PBLAS', and 'ScaLAPACK' in double precision via 'pbdMPI' based on 'ScaLAPACK' version 2.0.2.
Author: Wei-Chen Chen [aut, cre], Drew Schmidt [aut], George Ostrouchov [aut], Pragneshkumar Patel [aut], Brian Ripley [ctb] (Solaris & Mac)
Maintainer: Wei-Chen Chen <wccsnow@gmail.com>

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Package foretell updated to version 0.2.0 with previous version 0.1.0 dated 2019-04-01

Title: Projecting Customer Retention Based on Fader and Hardie Probability Models
Description: Project Customer Retention based on Beta Geometric, Beta Discrete Weibull and Latent Class Discrete Weibull Models.This package is based on Fader and Hardie (2007) <doi:10.1002/dir.20074> and Fader and Hardie et al. (2018) <doi:10.1016/j.intmar.2018.01.002>.
Author: Srihari Jaganathan
Maintainer: Srihari Jaganathan <sriharitn@gmail.com>

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Package WVPlots updated to version 1.1.0 with previous version 1.0.9 dated 2019-02-20

Title: Common Plots for Analysis
Description: Select data analysis plots, under a standardized calling interface implemented on top of 'ggplot2' and 'plotly'. Plots of interest include: 'ROC', gain curve, scatter plot with marginal distributions, conditioned scatter plot with marginal densities, box and stem with matching theoretical distribution, and density with matching theoretical distribution.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

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Package Brq updated to version 2.4 with previous version 2.3 dated 2019-01-25

Title: Bayesian Analysis of Quantile Regression Models
Description: Bayesian estimation and variable selection for quantile regression models.
Author: Rahim Alhamzawi
Maintainer: Rahim Alhamzawi (University of Al-Qadisiyah) <rahim.alhamzawi@qu.edu.iq>

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