Sun, 17 May 2020

Package PoisBinOrd updated to version 1.4.2 with previous version 1.4.1 dated 2019-05-15

Title: Data Generation with Poisson, Binary and Ordinal Components
Description: Generation of multiple count, binary and ordinal variables simultaneously given the marginal characteristics and association structure. Throughout the package, the word 'Poisson' is used to imply count data under the assumption of Poisson distribution. The details of the method are explained in Amatya, A. and Demirtas, H. (2015) <DOI:10.1080/00949655.2014.953534>.
Author: Gul Inan, Hakan Demirtas, Ran Gao
Maintainer: Ran Gao <rgao8@uic.edu>

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Package PoisBinNonNor updated to version 1.3.2 with previous version 1.3.1 dated 2019-05-16

Title: Data Generation with Poisson, Binary and Continuous Components
Description: Generation of multiple count, binary and continuous variables simultaneously given the marginal characteristics and association structure. Throughout the package, the word 'Poisson' is used to imply count data under the assumption of Poisson distribution. The details of the method are explained in Amatya et al. (2015) <DOI:10.1080/00949655.2014.953534>.
Author: Gul Inan, Hakan Demirtas, Ran Gao
Maintainer: Ran Gao <rgao8@uic.edu>

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Package GDAtools updated to version 1.5 with previous version 1.4 dated 2017-03-07

Title: A Toolbox for Geometric Data Analysis and More
Description: Contains functions for 'specific' Multiple Correspondence Analysis, Class Specific Analysis, Multiple Factor Analysis, 'standardized' MCA, computing and plotting structuring factors and concentration ellipses, inductive tests and others tools for Geometric Data Analysis (Le Roux & Rouanet (2005) <doi:10.1007/1-4020-2236-0>). It also provides functions for the translation of logit models coefficients into percentages (Deauvieau (2010) <doi:10.1177/0759106309352586>), weighted contingency tables, an association measure for contingency tables ("Percentages of Maximum Deviation from Independence", aka PEM, see Cibois (1993) <doi:10.1177/075910639304000103>) and some tools to measure bivariate associations between variables (phi, Cram<c3><a9>r V, correlation coefficient, eta-squared...).
Author: Nicolas Robette
Maintainer: Nicolas Robette <nicolas.robette@uvsq.fr>

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Package gdalcubes updated to version 0.2.5 with previous version 0.2.4 dated 2020-02-02

Title: Earth Observation Data Cubes from Satellite Image Collections
Description: Processing collections of Earth observation images as on-demand multispectral, multitemporal raster data cubes. Users define cubes by spatiotemporal extent, resolution, and spatial reference system and let 'gdalcubes' automatically apply cropping, reprojection, and resampling using the 'Geospatial Data Abstraction Library' ('GDAL'). Implemented functions on data cubes include reduction over space and time, applying arithmetic expressions on pixel band values, moving window aggregates over time, filtering by space, time, bands, and predicates on pixel values, exporting data cubes as 'netCDF' or 'GeoTIFF' files, and plotting. The package implements lazy evaluation and multithreading. All computational parts are implemented in C++, linking to the 'GDAL', 'netCDF', 'CURL', and 'SQLite' libraries. See Appel and Pebesma (2019) <doi:10.3390/data4030092> for further details.
Author: Marius Appel [aut, cre] (<https://orcid.org/0000-0001-5281-3896>), Edzer Pebesma [ctb] (<https://orcid.org/0000-0001-8049-7069>), Roger Bivand [ctb], Lewis Van Winkle [cph], Ole Christian Eidheim [cph], Niels Lohmann [cph], Howard Hinnant [cph], Adrian Colomitchi [cph], Florian Dang [cph], Paul Thompson [cph], Tomasz Kamiński [cph]
Maintainer: Marius Appel <marius.appel@uni-muenster.de>

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Package CornerstoneR updated to version 2.0.0 with previous version 1.1.0 dated 2019-02-12

Title: Collection of Scripts for Interface Between 'Cornerstone' and 'R'
Description: Collection of generic 'R' scripts which enable you to use existing 'R' routines in 'Cornerstone'. The desktop application 'Cornerstone' (<https://www.camline.com/en/products/cornerstone/cornerstone-core.html>) is a data analysis software provided by 'camLine' that empowers engineering teams to find solutions even faster. The engineers incorporate intensified hands-on statistics into their projects. They benefit from an intuitive and uniquely designed graphical Workmap concept: you design experiments (DoE) and explore data, analyze dependencies, and find answers you can act upon, immediately, interactively, and without any programming. While 'Cornerstone's' interface to the statistical programming language 'R' has been available since version 6.0, the latest interface with 'R' is even much more efficient. 'Cornerstone' release 7.1.1 allows you to integrate user defined 'R' packages directly into the standard 'Cornerstone' GUI. Your engineering team stays in 'Cornerstone's' graphical working environment and can apply 'R' routines, immediately and without the need to deal with programming code. Additionally, your 'R' programming team develops corresponding 'R' packages detached from 'Cornerstone' in their favorite 'R' environment. Learn how to use 'R' packages in 'Cornerstone' 7.1.1 on 'camLineTV' YouTube channel (<https://www.youtube.com/watch?v=HEQHwq_laXU>) (available in German).
Author: Dirk Surmann [aut, cre] (<https://orcid.org/0000-0003-0873-137X>)
Maintainer: Dirk Surmann <dirk.surmann@camline.academy>

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Package cartograflow updated to version 1.0.1 with previous version 1.0.0 dated 2019-05-10

Title: Filtering Matrix for Flow Mapping
Description: Functions to prepare and filter an origin-destination matrix for thematic flow mapping purposes. This comes after Bahoken, Francoise (2016), Mapping flow matrix a contribution, PhD in Geography - Territorial sciences. See Bahoken (2017) <doi:10.4000/netcom.2565>.
Author: Sylvain Blondeau [aut, cre], Francoise Bahoken [aut]
Maintainer: Sylvain Blondeau <blondeau.sylvain@yahoo.fr>

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Package medfate updated to version 1.0.0 with previous version 0.9.0 dated 2020-03-22

Title: Mediterranean Forest Simulation
Description: Functions to simulate Mediterranean forest functioning and dynamics using cohort-based description of vegetation [De Caceres et al. (2015) <doi:10.1016/j.agrformet.2015.06.012>].
Author: Miquel De Cáceres [aut, cre], Shengli Huang [aut], Víctor Granda [aut], Antoine Cabon [aut], Jordi Martínez-Vilalta [ctb], Maurizio Mencuccini [ctb], Nicolas Martin-StPaul [ctb]
Maintainer: Miquel De Cáceres <miquelcaceres@gmail.com>

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Package gss updated to version 2.2-1 with previous version 2.2-0 dated 2020-05-04

Title: General Smoothing Splines
Description: A comprehensive package for structural multivariate function estimation using smoothing splines.
Author: Chong Gu <chong@purdue.edu>
Maintainer: Chong Gu <chong@purdue.edu>

Diff between gss versions 2.2-0 dated 2020-05-04 and 2.2-1 dated 2020-05-17

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Package ecmwfr updated to version 1.2.3 with previous version 1.2.2 dated 2020-02-13

Title: Interface to 'ECMWF' and 'CDS' Data Web Services
Description: Programmatic interface to the European Centre for Medium-Range Weather Forecasts dataset web services (ECMWF; <https://www.ecmwf.int/>) and Copernicus's Climate Data Store (CDS; <https://cds.climate.copernicus.eu>). Allows for easy downloads of weather forecasts and climate reanalysis data in R.
Author: Koen Hufkens [aut, cre] (<https://orcid.org/0000-0002-5070-8109>), Reto Stauffer [ctb] (<https://orcid.org/0000-0002-3798-5507>), Elio Campitelli [ctb] (<https://orcid.org/0000-0002-7742-9230>)
Maintainer: Koen Hufkens <koen.hufkens@gmail.com>

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Package NNS updated to version 0.5.2 with previous version 0.5.1 dated 2020-04-15

Title: Nonlinear Nonparametric Statistics
Description: Nonlinear nonparametric statistics using partial moments. Partial moments are the elements of variance and asymptotically approximate the area of f(x). These robust statistics provide the basis for nonlinear analysis while retaining linear equivalences. NNS offers: Numerical integration, Numerical differentiation, Clustering, Correlation, Dependence, Causal analysis, ANOVA, Regression, Classification, Seasonality, Autoregressive modeling, Normalization and Stochastic dominance. All routines based on: Viole, F. and Nawrocki, D. (2013), Nonlinear Nonparametric Statistics: Using Partial Moments (ISBN: 1490523995).
Author: Fred Viole
Maintainer: Fred Viole <ovvo.financial.systems@gmail.com>

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Package traitr (with last version 0.14) was removed from CRAN

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

2014-09-01 0.14
2012-01-26 0.13
2011-05-15 0.11
2010-08-16 0.10
2010-07-24 0.9
2010-03-20 0.7
2010-02-05 0.5
2010-02-03 0.4
2010-01-22 0.3
2010-01-15 0.1

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Package simTool updated to version 1.1.6 with previous version 1.1.5 dated 2020-03-15

Title: Conduct Simulation Studies with a Minimal Amount of Source Code
Description: Tool for statistical simulations that have two components. One component generates the data and the other one analyzes the data. The main aims of the package are the reduction of the administrative source code (mainly loops and management code for the results) and a simple applicability of the package that allows the user to quickly learn how to work with it. Parallel computing is also supported. Finally, convenient functions are provided to summarize the simulation results.
Author: Marsel Scheer [aut, cre]
Maintainer: Marsel Scheer <scheer@freescience.de>

Diff between simTool versions 1.1.5 dated 2020-03-15 and 1.1.6 dated 2020-05-17

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Package missDeaths updated to version 2.6 with previous version 2.5.1 dated 2019-04-24

Title: Simulating and Analyzing Time to Event Data in the Presence of Population Mortality
Description: Implements two methods: a nonparametric risk adjustment and a data imputation method that use general population mortality tables to allow a correct analysis of time to disease recurrence. Also includes a powerful set of object oriented survival data simulation functions.
Author: Tomaz Stupnik [aut, cre], Maja Pohar Perme [ctb]
Maintainer: Tomaz Stupnik <tomaz.stupnik@guest.arnes.si>

Diff between missDeaths versions 2.5.1 dated 2019-04-24 and 2.6 dated 2020-05-17

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Package jskm updated to version 0.3.9 with previous version 0.3.8 dated 2019-11-08

Title: Kaplan-Meier Plot with 'ggplot2'
Description: The function 'jskm()' creates publication quality Kaplan-Meier plot with at risk tables below. 'svyjskm()' provides plot for weighted Kaplan-Meier estimator.
Author: Jinseob Kim [aut, cre] (<https://orcid.org/0000-0002-9403-605X>), Zarathu [cph, fnd]
Maintainer: Jinseob Kim <jinseob2kim@gmail.com>

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Package TR8 updated to version 0.9.21 with previous version 0.9.20 dated 2019-04-10

Title: A Tool for Downloading Functional Traits Data for Plant Species
Description: Plant ecologists often need to collect "traits" data about plant species which are often scattered among various databases: TR8 contains a set of tools which take care of automatically retrieving some of those functional traits data for plant species from publicly available databases (Biolflor, The Ecological Flora of the British Isles, LEDA traitbase, Ellenberg values for Italian Flora, Mycorrhizal intensity databases, Catminat, BROT, PLANTS, Jepson Flora Project). The TR8 name, inspired by "car plates" jokes, was chosen since it both reminds of the main object of the package and is extremely short to type.
Author: Gionata Bocci <boccigionata@gmail.com>
Maintainer: Gionata Bocci <boccigionata@gmail.com>

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Package gtrendsR updated to version 1.4.6 with previous version 1.4.5 dated 2020-05-06

Title: Perform and Display Google Trends Queries
Description: An interface for retrieving and displaying the information returned online by Google Trends is provided. Trends (number of hits) over the time as well as geographic representation of the results can be displayed.
Author: Philippe Massicotte [aut, cre], Dirk Eddelbuettel [aut]
Maintainer: Philippe Massicotte <pmassicotte@hotmail.com>

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Package VLTimeCausality updated to version 0.1.1 with previous version 0.1.0 dated 2019-12-20

Title: Variable-Lag Time Series Causality Inference Framework
Description: A framework to infer causality on a pair of time series of real numbers based on variable-lag Granger causality and transfer entropy. Typically, Granger causality and transfer entropy have an assumption of a fixed and constant time delay between the cause and effect. However, for a non-stationary time series, this assumption is not true. For example, considering two time series of velocity of person A and person B where B follows A. At some time, B stops tying his shoes, then running to catch up A. The fixed-lag assumption is not true in this case. We propose a framework that allows variable-lags between cause and effect in Granger causality and transfer entropy to allow them to deal with variable-lag non-stationary time series. Please see Chainarong Amornbunchornvej, Elena Zheleva, and Tanya Berger-Wolf (2019) <arXiv:1912.10829> when referring to this package in publications.
Author: Chainarong Amornbunchornvej [aut, cre] (<https://orcid.org/0000-0003-3131-0370>)
Maintainer: Chainarong Amornbunchornvej <grandca@gmail.com>

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Package fxtract updated to version 0.9.3 with previous version 0.9.2 dated 2019-07-03

Title: Feature Extraction from Grouped Data
Description: An R6 implementation for calculating features from grouped data. The output will be one row for each group. This functionality is often needed in the feature extraction process of machine learning problems. Very large datasets are supported, since data is only read into RAM when needed. Calculation can be done in parallel and the process can be monitored. Global error handling is supported. Results are available in one final dataframe.
Author: Quay Au [aut, cre], Clemens Stachl [ctb], Ramona Schoedel [ctb], Theresa Ullmann [ctb], Andreas Hofheinz [ctb]
Maintainer: Quay Au <quayau@gmail.com>

Diff between fxtract versions 0.9.2 dated 2019-07-03 and 0.9.3 dated 2020-05-17

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Package psychNET (with last version 0.0.4.1) was removed from CRAN

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

2020-04-06 0.0.4.1

Permanent link
Package flare (with last version 1.6.0.2) was removed from CRAN

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

2019-08-02 1.6.0.2
2019-07-02 1.6.0.1
2018-03-25 1.6.0
2014-10-18 1.5.0
2014-07-09 1.4.0
2014-04-26 1.3.0
2014-03-30 1.2.0
2014-03-13 1.1.0
2013-08-27 1.0.0
2013-04-01 0.9.9
2013-01-27 0.9.8
2012-11-29 0.9.7
2012-11-27 0.9.6

Permanent link
Package qut (with last version 2.1) was removed from CRAN

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

2018-05-22 2.1
2018-01-29 2.0
2017-03-12 1.2
2016-09-09 1.1
2015-11-23 1.0.1
2015-09-20 1.0

Permanent link
Package SparseTSCGM (with last version 2.5) was removed from CRAN

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

2016-11-06 2.5
2015-07-16 2.2
2014-08-21 2.1.1

Permanent link
Package DNetFinder (with last version 1.0) was removed from CRAN

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

2018-01-05 1.0

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Package themis updated to version 0.1.1 with previous version 0.1.0 dated 2020-01-13

Title: Extra Recipes Steps for Dealing with Unbalanced Data
Description: A dataset with an uneven number of cases in each class is said to be unbalanced. Many models produce a subpar performance on unbalanced datasets. A dataset can be balanced by increasing the number of minority cases using SMOTE 2011 <arXiv:1106.1813>, BorderlineSMOTE 2005 <doi:10.1007/11538059_91> and ADASYN 2008 <https://ieeexplore.ieee.org/document/4633969>. Or by decreasing the number of majority cases using NearMiss 2003 <https://www.site.uottawa.ca/~nat/Workshop2003/jzhang.pdf> or Tomek link removal 1976 <https://ieeexplore.ieee.org/document/4309452>.
Author: Emil Hvitfeldt [aut, cre] (<https://orcid.org/0000-0002-0679-1945>)
Maintainer: Emil Hvitfeldt <emilhhvitfeldt@gmail.com>

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Permanent link

Package terra updated to version 0.6-8 with previous version 0.5-8 dated 2020-04-14

Title: Spatial Data Analysis
Description: Methods for spatial data analysis, especially raster data. Methods allow for low-level data manipulation as well as high-level global, local, zonal, and focal computation. The predict and interpolate methods facilitate the use of regression type (interpolation, machine learning) models for spatial prediction. Processing of very large files is supported. See the manual and tutorials on <https://rspatial.org/terra/> to get started. The package is similar to the 'raster' package; but it is simpler and faster.
Author: Robert J. Hijmans [cre, aut] (<https://orcid.org/0000-0001-5872-2872>), Edzer Pebesma [ctb] (<https://orcid.org/0000-0001-8049-7069>), Roger Bivand [ctb] (<https://orcid.org/0000-0003-2392-6140>), Karl Forner [ctb]
Maintainer: Robert J. Hijmans <r.hijmans@gmail.com>

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More information about terra at CRAN
Permanent link

New package sinx with initial version 0.0.13
Package: sinx
Version: 0.0.13
Date: 2020-05-16
Title: Sino Xmen Said
Authors@R: c( person("Peng", "Zhao", role = c("aut", "cre"), email = "pzhao@pzhao.net") )
Maintainer: Peng Zhao <pzhao@pzhao.net>
Imports: utils, cowsay, jsonlite, xaringan, pagedown, bookdownplus, rosr, crayon, multicolor, rmsfact, clipr
License: GPL-3
Depends: R (>= 3.1.0)
Suggests: knitr, rmarkdown
Description: Displays a pseudorandom message from a database of quotations. It works as an advanced version of the package 'fortunes', while 'sinx' supports multi-byte languages such as Chinese. The databases of 'sinx' can be given in markdown format, which is easier and more friendly than spread sheets for users.
URL: https://github.com/pzhaonet/sinx
BugReports: https://github.com/pzhaonet/sinx/issues
RoxygenNote: 7.1.0
NeedsCompilation: no
LazyData: true
VignetteBuilder: knitr
Packaged: 2020-05-16 10:01:04 UTC; dapen
Author: Peng Zhao [aut, cre]
Repository: CRAN
Date/Publication: 2020-05-17 07:40:02 UTC

More information about sinx at CRAN
Permanent link

Package semPower updated to version 1.0.1 with previous version 1.0.0 dated 2018-03-27

Title: Power Analyses for SEM
Description: Provides a-priori, post-hoc, and compromise power-analyses for structural equation models (SEM). Moshagen & Erdfelder (2016) <doi:10.1080/10705511.2014.950896>.
Author: Morten Moshagen
Maintainer: Morten Moshagen <morten.moshagen@uni-ulm.de>

Diff between semPower versions 1.0.0 dated 2018-03-27 and 1.0.1 dated 2020-05-17

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Package rgeolocate updated to version 1.3.1 with previous version 1.3.0 dated 2020-05-11

Title: IP Address Geolocation
Description: Connectors to online and offline sources for taking IP addresses and geolocating them to country, city, timezone and other geographic ranges. For individual connectors, see the package index.
Author: Os Keyes [aut, cre], Drew Schmidt [aut], David Robinson [ctb], Chris Davis [ctb], Bob Rudis [ctb], Maxmind, Inc. [cph], Pascal Gloor [cph], IP2Location.com [cph]
Maintainer: Os Keyes <ironholds@gmail.com>

Diff between rgeolocate versions 1.3.0 dated 2020-05-11 and 1.3.1 dated 2020-05-17

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Package HellCor updated to version 1.3 with previous version 1.2 dated 2019-08-19

Title: The Hellinger Correlation
Description: Empirical value of the Hellinger correlation, a measure of dependence between two continuous random variables. More details can be found in Geenens and Lafaye De Micheaux (2019) <arXiv:1810.10276v4>.
Author: Gery Geenens [aut], Pierre Lafaye De Micheaux [aut, cre]
Maintainer: Pierre Lafaye De Micheaux <lafaye@unsw.edu.au>

Diff between HellCor versions 1.2 dated 2019-08-19 and 1.3 dated 2020-05-17

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Package gmp updated to version 0.5-14 with previous version 0.5-13.6 dated 2020-01-24

Title: Multiple Precision Arithmetic
Description: Multiple Precision Arithmetic (big integers and rationals, prime number tests, matrix computation), "arithmetic without limitations" using the C library GMP (GNU Multiple Precision Arithmetic).
Author: Antoine Lucas, Immanuel Scholz, Rainer Boehme <rb-gmp@reflex-studio.de>, Sylvain Jasson <Sylvain.Jasson@inrae.fr>, Martin Maechler <maechler@stat.math.ethz.ch>
Maintainer: Antoine Lucas <antoinelucas@gmail.com>

Diff between gmp versions 0.5-13.6 dated 2020-01-24 and 0.5-14 dated 2020-05-17

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Package DataVisualizations updated to version 1.1.12 with previous version 1.1.11 dated 2020-02-13

Title: Visualizations of High-Dimensional Data
Description: Gives access to data visualisation methods that are relevant from the data scientist's point of view. The flagship idea of 'DataVisualizations' is the mirrored density plot (MD-plot) for either classified or non-classified multivariate data presented in Thrun et al. (2019) <arXiv:1908.06081>. The MD-plot outperforms the box-and-whisker diagram (box plot), violin plot and bean plot. Furthermore, a collection of various visualization methods for univariate data is provided. In the case of exploratory data analysis, 'DataVisualizations' makes it possible to inspect the distribution of each feature of a dataset visually through a combination of four methods. One of these methods is the Pareto density estimation (PDE) of the probability density function (pdf). Additionally, visualizations of the distribution of distances using PDE, the scatter-density plot using PDE for two variables as well as the Shepard density plot and the Bland-Altman plot are presented here. Pertaining to classified high-dimensional data, a number of visualizations are described, such as f.ex. the heat map and silhouette plot. A political map of the world or Germany can be visualized with the additional information defined by a classification of countries or regions. By extending the political map further, an uncomplicated function for a Choropleth map can be used which is useful for measurements across a geographic area. For categorical features, the Pie charts, slope charts and fan plots, improved by the ABC analysis, become usable. More detailed explanations are found in the book by Thrun, M.C.: "Projection-Based Clustering through Self-Organization and Swarm Intelligence" (2018) <doi:10.1007/978-3-658-20540-9>.
Author: Michael Thrun [aut, cre, cph] (<https://orcid.org/0000-0001-9542-5543>), Felix Pape [aut, rev], Onno Hansen-Goos [ctr, ctb], Dirk Eddelbuettel [ctr], Craig Varrichio [ctr], Alfred Ultsch [dtc, ctb]
Maintainer: Michael Thrun <m.thrun@gmx.net>

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Package broom.mixed updated to version 0.2.6 with previous version 0.2.5 dated 2020-04-19

Title: Tidying Methods for Mixed Models
Description: Convert fitted objects from various R mixed-model packages into tidy data frames along the lines of the 'broom' package. The package provides three S3 generics for each model: tidy(), which summarizes a model's statistical findings such as coefficients of a regression; augment(), which adds columns to the original data such as predictions, residuals and cluster assignments; and glance(), which provides a one-row summary of model-level statistics.
Author: Ben Bolker [aut, cre] (<https://orcid.org/0000-0002-2127-0443>), David Robinson [aut], Dieter Menne [ctb], Jonah Gabry [ctb], Paul Buerkner [ctb], Christopher Hua [ctb], William Petry [ctb] (<https://orcid.org/0000-0002-5230-5987>), Joshua Wiley [ctb] (<https://orcid.org/0000-0002-0271-6702>), Patrick Kennedy [ctb], Eduard Szöcs [ctb] (<https://orcid.org/0000-0001-5376-1194>, BASF SE), Indrajeet Patil [ctb]
Maintainer: Ben Bolker <bolker@mcmaster.ca>

Diff between broom.mixed versions 0.2.5 dated 2020-04-19 and 0.2.6 dated 2020-05-17

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Package arulesSequences updated to version 0.2-25 with previous version 0.2-24 dated 2020-02-17

Title: Mining Frequent Sequences
Description: Add-on for arules to handle and mine frequent sequences. Provides interfaces to the C++ implementation of cSPADE by Mohammed J. Zaki.
Author: Christian Buchta and Michael Hahsler, with contributions from Daniel Diaz
Maintainer: Christian Buchta <christian.buchta@wu.ac.at>

Diff between arulesSequences versions 0.2-24 dated 2020-02-17 and 0.2-25 dated 2020-05-17

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Package kpodclustr (with last version 1.0) was removed from CRAN

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

2014-11-26 1.0

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Package nmfem (with last version 1.0.5) was removed from CRAN

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

2019-12-06 1.0.5
2019-04-02 1.0.4
2018-04-24 1.0.3
2018-04-23 1.0.2
2018-04-11 1.0.1
2017-11-17 1.0.0

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Package clues (with last version 0.6.2.1) was removed from CRAN

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

2019-12-03 0.6.2.1
2019-12-03 0.6.2.2
2019-10-13 0.6.1
2016-10-14 0.5.9
2015-02-18 0.5.6
2014-05-21 0.5-4

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Package wavemulcor updated to version 3.1.0 with previous version 2.2.1 dated 2018-06-08

Title: Wavelet Routines for Global and Local Multiple Regression and Correlation
Description: Wavelet routines that calculate single sets of wavelet multiple regressions and correlations, and cross-regressions and cross-correlations from a multivariate time series. Dynamic versions of the routines allow the wavelet local multiple (cross-)regressions and (cross-)correlations to evolve over time.
Author: Javier Fernandez-Macho [aut, cre] (<https://orcid.org/0000-0002-5970-4382>)
Maintainer: Javier Fernandez-Macho <javier.fernandezmacho@ehu.es>

Diff between wavemulcor versions 2.2.1 dated 2018-06-08 and 3.1.0 dated 2020-05-17

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Package xslt updated to version 1.4.2 with previous version 1.4.1 dated 2020-04-15

Title: Extensible Style-Sheet Language Transformations
Description: An extension for the 'xml2' package to transform XML documents by applying an 'xslt' style-sheet.
Author: Jeroen Ooms [aut, cre] (<https://orcid.org/0000-0002-4035-0289>)
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between xslt versions 1.4.1 dated 2020-04-15 and 1.4.2 dated 2020-05-17

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Package TruncatedNormal updated to version 2.2 with previous version 2.1.2 dated 2020-05-02

Title: Truncated Multivariate Normal and Student Distributions
Description: A collection of functions to deal with the truncated univariate and multivariate normal and Student distributions, described in Botev (2017) <doi:10.1111/rssb.12162> and Botev and L'Ecuyer (2015) <doi:10.1109/WSC.2015.7408180>.
Author: Zdravko Botev [aut] (<https://orcid.org/0000-0001-9054-3452>), Leo Belzile [aut, cre] (<https://orcid.org/0000-0002-9135-014X>)
Maintainer: Leo Belzile <belzilel@gmail.com>

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Package spray updated to version 1.0-9 with previous version 1.0-8 dated 2019-10-21

Title: Sparse Arrays and Multivariate Polynomials
Description: Sparse arrays interpreted as multivariate polynomials.
Author: Robin K. S. Hankin [aut, cre] (<https://orcid.org/0000-0001-5982-0415>)
Maintainer: Robin K. S. Hankin <hankin.robin@gmail.com>

Diff between spray versions 1.0-8 dated 2019-10-21 and 1.0-9 dated 2020-05-17

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Package Rpvt updated to version 0.1.1 with previous version 0.1.0 dated 2020-05-08

Title: Estimate the PVT Properties of Reservoir Fluids
Description: Generate the PVT (Pressure-Volume-Temperature) properties of dry gas, wet gas, black oil, and water samples in a tabular format at a constant temperature from the atmospheric pressure up to the pressure of interest using correlations. Spivey, J. P., McCain Jr., W. D. and North, R. (2004) <doi:10.2118/04-07-05>. Sutton, R. P. (2007) <doi:10.2118/97099-PA>. Vasquez, M., and Beggs, H. D. (1980) <doi:10.2118/6719-PA>.
Author: Farshad Tabasinejad [aut, cre]
Maintainer: Farshad Tabasinejad <farshad.tabasinejad@susaenergy.com>

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Package RhpcBLASctl updated to version 0.20-137 with previous version 0.20-17 dated 2020-01-17

Title: Control the Number of Threads on 'BLAS'
Description: Control the number of threads on 'BLAS' (Aka 'GotoBLAS', 'OpenBLAS', 'ACML', 'BLIS' and 'MKL'). And possible to control the number of threads in 'OpenMP'. Get a number of logical cores and physical cores if feasible.
Author: Junji NAKANO <nakanoj@ism.ac.jp> and Ei-ji Nakama <nakama@ki.rim.or.jp>
Maintainer: Ei-ji Nakama <nakama@ki.rim.or.jp>

Diff between RhpcBLASctl versions 0.20-17 dated 2020-01-17 and 0.20-137 dated 2020-05-17

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Package RcppArmadillo updated to version 0.9.880.1.0 with previous version 0.9.870.2.0 dated 2020-04-27

Title: 'Rcpp' Integration for the 'Armadillo' Templated Linear Algebra Library
Description: 'Armadillo' is a templated C++ linear algebra library (by Conrad Sanderson) that aims towards a good balance between speed and ease of use. Integer, floating point and complex numbers are supported, as well as a subset of trigonometric and statistics functions. Various matrix decompositions are provided through optional integration with LAPACK and ATLAS libraries. The 'RcppArmadillo' package includes the header files from the templated 'Armadillo' library. Thus users do not need to install 'Armadillo' itself in order to use 'RcppArmadillo'. From release 7.800.0 on, 'Armadillo' is licensed under Apache License 2; previous releases were under licensed as MPL 2.0 from version 3.800.0 onwards and LGPL-3 prior to that; 'RcppArmadillo' (the 'Rcpp' bindings/bridge to Armadillo) is licensed under the GNU GPL version 2 or later, as is the rest of 'Rcpp'. Note that Armadillo requires a fairly recent compiler; for the g++ family at least version 4.6.* is required.
Author: Dirk Eddelbuettel, Romain Francois, Doug Bates and Binxiang Ni
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between RcppArmadillo versions 0.9.870.2.0 dated 2020-04-27 and 0.9.880.1.0 dated 2020-05-17

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Package pxR updated to version 0.42.3 with previous version 0.42.2 dated 2017-01-12

Title: PC-Axis with R
Description: Provides a set of functions for reading and writing PC-Axis files, used by different statistical organizations around the globe for data dissemination.
Author: Carlos J. Gil Bellosta [cre, aut], Francisco J. Viciana [aut], Oscar Perpinan Lamigueiro [aut], Emilio Torres Manzanera [ctb]
Maintainer: Carlos J. Gil Bellosta <cgb@datanalytics.com>

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Package PAutilities updated to version 1.0.1 with previous version 0.3.1 dated 2019-12-16

Title: Streamline Physical Activity Research
Description: A collection of utilities that are useful for a broad range of tasks that are common in physical activity research, including the following: creation of Bland-Altman plots, formatted descriptive statistics, metabolic calculations (e.g. basal metabolic rate predictions) and conversions, demographic calculations (age and age-for-body-mass-index percentile), bout analysis of moderate-to-vigorous intensity physical activity, and analysis of bout detection algorithm performance.
Author: Paul R. Hibbing [aut, cre], Centers for Disease Control and Prevention [ctb]
Maintainer: Paul R. Hibbing <paulhibbing@gmail.com>

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Package maotai updated to version 0.1.6 with previous version 0.1.5 dated 2020-04-11

Title: Tools for Matrix Algebra, Optimization and Inference
Description: Matrix is an universal and sometimes primary object/unit in applied mathematics and statistics. We provide a number of algorithms for selected problems in optimization and statistical inference. For general exposition to the topic with focus on statistical context, see the book by Banerjee and Roy (2014, ISBN:9781420095388).
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)
Maintainer: Kisung You <kyoustat@gmail.com>

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Package EValue updated to version 2.1.0 with previous version 2.0.0 dated 2019-04-01

Title: Sensitivity Analyses for Unmeasured Confounding or Selection Bias in Observational Studies and Meta-Analyses
Description: Conducts sensitivity analyses for unmeasured confounding for either an observational study or a meta-analysis of observational studies. For a single observational study, the package reports E-values, defined as the minimum strength of association on the risk ratio scale that an unmeasured confounder would need to have with both the treatment and the outcome to fully explain away a specific treatment-outcome association, conditional on the measured covariates. You can use one of the evalues.XX() functions to compute E-values for the relevant outcome types. Outcome types include risk ratios, odds ratio with common or rare outcomes, hazard ratios with common or rare outcomes, and standardized differences in outcomes. Optionally, you can use the bias_plot() function to plot the bias factor as a function of two sensitivity parameters. (See VanderWeele & Ding, 2017 [<http://annals.org/aim/article/2643434>] for details.) For a meta-analysis, use the function confounded_meta to compute point estimates and inference for: (1) the proportion of studies with true causal effect sizes more extreme than a specified threshold of scientific importance; and (2) the minimum bias factor and confounding strength required to reduce to less than a specified threshold the proportion of studies with true effect sizes of scientifically significant size. The functions sens_plot() and sens_table() create plots and tables for visualizing these meta-analysis metrics across a range of bias values. (See Mathur & VanderWeele, 2019 [<https://amstat.tandfonline.com/doi/full/10.1080/01621459.2018.1529598#.XKIJtOtKjdc>] for details.) Most of the analyses available in this package can also be conducted using web-based graphical interfaces (for a single observational study: [<https://evalue.hmdc.harvard.edu>]; for a meta-analysis: [<https://mmathur.shinyapps.io/meta_gui_2/>]).
Author: Maya B. Mathur, Peng Ding, Louisa H. Smith, Tyler J. VanderWeele
Maintainer: Maya B. Mathur <mmathur@stanford.edu>

Diff between EValue versions 2.0.0 dated 2019-04-01 and 2.1.0 dated 2020-05-17

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 man/sens_table.Rd  |    4 ++--
 7 files changed, 89 insertions(+), 19 deletions(-)

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