Thu, 19 Sep 2019

Package Luminescence updated to version 0.9.4 with previous version 0.9.3 dated 2019-07-31

Title: Comprehensive Luminescence Dating Data Analysis
Description: A collection of various R functions for the purpose of Luminescence dating data analysis. This includes, amongst others, data import, export, application of age models, curve deconvolution, sequence analysis and plotting of equivalent dose distributions.
Author: Sebastian Kreutzer [aut, trl, cre, dtc] (<https://orcid.org/0000-0002-0734-2199>), Christoph Burow [aut, trl, dtc] (<https://orcid.org/0000-0002-5023-4046>), Michael Dietze [aut] (<https://orcid.org/0000-0001-6063-1726>), Margret C. Fuchs [aut], Christoph Schmidt [aut] (<https://orcid.org/0000-0002-2309-3209>), Manfred Fischer [aut, trl], Johannes Friedrich [aut] (<https://orcid.org/0000-0002-0805-9547>), Norbert Mercier [ctb] (<https://orcid.org/0000-0002-6375-9108>), Rachel K. Smedley [ctb] (<https://orcid.org/0000-0001-7773-5193>), Claire Christophe [ctb], Antoine Zink [ctb] (<https://orcid.org/0000-0001-7146-1101>), Julie Durcan [ctb] (<https://orcid.org/0000-0001-8724-8022>), Georgina E. King [ctb, dtc] (<https://orcid.org/0000-0003-1059-8192>), Anne Philippe [ctb], Guillaume Guerin [ctb] (<https://orcid.org/0000-0001-6298-5579>), Svenja Riedesel [ctb] (<https://orcid.org/0000-0003-2936-8776>), Martin Autzen [ctb], Pierre Guibert [ctb] (<https://orcid.org/0000-0001-8969-8684>), Markus Fuchs [ths]
Maintainer: Sebastian Kreutzer <sebastian.kreutzer@u-bordeaux-montaigne.fr>

Diff between Luminescence versions 0.9.3 dated 2019-07-31 and 0.9.4 dated 2019-09-19

 Luminescence-0.9.3/Luminescence/src/src_find_first_larger_value.cpp           |only
 Luminescence-0.9.4/Luminescence/DESCRIPTION                                   |   18 
 Luminescence-0.9.4/Luminescence/MD5                                           |  325 ++++------
 Luminescence-0.9.4/Luminescence/NEWS.md                                       |   99 ++-
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 Luminescence-0.9.4/Luminescence/R/analyse_SAR.CWOSL.R                         |   20 
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 Luminescence-0.9.4/Luminescence/R/calc_MinDose.R                              |   90 ++
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 Luminescence-0.9.4/Luminescence/R/internals_RLum.R                            |   15 
 Luminescence-0.9.4/Luminescence/R/plot_DetPlot.R                              |   18 
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 Luminescence-0.9.4/Luminescence/R/plot_KDE.R                                  |    8 
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 Luminescence-0.9.4/Luminescence/README.md                                     |   33 -
 Luminescence-0.9.4/Luminescence/build/partial.rdb                             |binary
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 Luminescence-0.9.4/Luminescence/inst/doc/HowTo_analyse_Al2O3.html             |  160 ++--
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 Luminescence-0.9.4/Luminescence/man/CW2pHMi.Rd                                |    2 
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 Luminescence-0.9.4/Luminescence/man/set_RLum.Rd                               |    2 
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 Luminescence-0.9.4/Luminescence/man/write_R2BIN.Rd                            |    2 
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New package tidycomm with initial version 0.0.1
Package: tidycomm
Title: Data Modifcation and Analysis for Communication Research
Version: 0.0.1
Authors@R: person(given = "Julian", family = "Unkel", role = c("aut", "cre"), email = "julian.unkel@gmail.com", comment = c(ORCID = "0000-0001-9568-7041"))
Description: Provides convenience functions for common data modification and analysis tasks in communication research. This includes functions for univariate and bivariate data analysis, index generation and reliability computation, and intercoder reliability tests. All functions follow the style and syntax of the tidyverse, and are construed to perform their computations on multiple variables at once. Functions for univariate and bivariate data analysis comprise summary statistics for continouos and categorical variables, as well as several tests of bivariate association including effect sizes. Functions for data modification comprise index generation and automated reliability analysis of index variables. Functions for intercoder reliability comprise tests of several intercoder reliability estimates, including simple and mean pairwise percent agreement, Krippendorff's Alpha, and various Kappa coefficients.
License: GPL-3
URL: https://github.com/joon-e/tidycomm
BugReports: https://github.com/joon-e/tidycomm/issues
Depends: R (>= 2.10)
Imports: broom, dplyr, forcats, glue, magrittr, MBESS, purrr, rlang, stringr, tibble, tidyr, tidyselect
Suggests: covr, knitr, rmarkdown, testthat (>= 2.1.0)
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-09-19 15:51:02 UTC; di98tox
Author: Julian Unkel [aut, cre] (<https://orcid.org/0000-0001-9568-7041>)
Maintainer: Julian Unkel <julian.unkel@gmail.com>
Repository: CRAN
Date/Publication: 2019-09-19 21:50:02 UTC

More information about tidycomm at CRAN
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Package utile.tools updated to version 0.2.1 with previous version 0.2.0 dated 2019-07-01

Title: Summarize Data for Publication
Description: A variety of tools for preparing and summarizing data for publication purposes. Function verbs include 'tabulate' for creating usable tabulated data from models, 'paste' for generating human-readable statistics from a variety of summarizable data types, 'calc' for reliably calculating differences between data points, and 'test' for conducting simple statistical tests which return human-readable results.
Author: Eric Finnesgard [aut, cre]
Maintainer: Eric Finnesgard <finnesgard.eric@mayo.edu>

Diff between utile.tools versions 0.2.0 dated 2019-07-01 and 0.2.1 dated 2019-09-19

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 6 files changed, 44 insertions(+), 28 deletions(-)

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Package DALEXtra (with last version 0.1.7) was removed from CRAN

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

2019-09-19 0.1.7

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Package utile.tables updated to version 0.1.6 with previous version 0.1.5 dated 2019-07-01

Title: Build Tables for Publication
Description: A collection of functions to make building customized ready-to-export tables for publication purposes easier or expedite summarization of a large dataset for review. Includes methods for automatically building a table from data or building the table row-by-row. Key functions include build_row() & build_table() for summarizing columns of data overall or by stratum with appropriate testing and build_event_row() & build_event_table() for creating tables that summarize time-to-event model (Cox Parametric Hazard) parameters, supporting both univariate and multivariate methods.
Author: Eric Finnesgard [aut, cre], Jennifer Grauberger [aut]
Maintainer: Eric Finnesgard <finnesgard.eric@mayo.edu>

Diff between utile.tables versions 0.1.5 dated 2019-07-01 and 0.1.6 dated 2019-09-19

 DESCRIPTION         |   13 ++++++-------
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 R/build_event_row.R |    9 +++++++--
 README.md           |   18 +++++++++---------
 5 files changed, 31 insertions(+), 25 deletions(-)

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Package matrixTests updated to version 0.1.6 with previous version 0.1.5 dated 2019-07-09

Title: Fast Statistical Hypothesis Tests on Rows and Columns of Matrices
Description: Functions to perform fast statistical hypothesis tests on rows/columns of matrices. The main goals are: 1) speed via vectorization, 2) output that is detailed and easy to use, 3) compatibility with tests implemented in R (like those available in the 'stats' package).
Author: Karolis Koncevičius [aut, cre]
Maintainer: Karolis Koncevičius <karolis.koncevicius@gmail.com>

Diff between matrixTests versions 0.1.5 dated 2019-07-09 and 0.1.6 dated 2019-09-19

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 NAMESPACE                                      |    4 +++
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New package tidyquery with initial version 0.1.0
Package: tidyquery
Type: Package
Title: Query 'R' Data Frames with 'SQL'
Version: 0.1.0
Authors@R: c( person("Ian", "Cook", email = "ian@cloudera.com", role = c("aut", "cre")), person(family = "Cloudera", role = c("cph")) )
Maintainer: Ian Cook <ian@cloudera.com>
Description: Use 'SQL' 'SELECT' statements to query 'R' data frames.
URL: https://github.com/ianmcook/tidyquery
BugReports: https://github.com/ianmcook/tidyquery/issues
NeedsCompilation: no
License: Apache License 2.0
Encoding: UTF-8
RoxygenNote: 6.1.1
Imports: dplyr (>= 0.7.4), lubridate (>= 1.6.0), queryparser (>= 0.1.1), stringr (>= 1.0.0), utils
Suggests: nycflights13, testthat (>= 2.1.0)
Collate: 'compat.R' 'query.R' 'quote.R' 'remove.R' 'replace.R' 'unscope.R'
Packaged: 2019-09-07 13:03:22 UTC; icook
Author: Ian Cook [aut, cre], Cloudera [cph]
Repository: CRAN
Date/Publication: 2019-09-19 16:40:02 UTC

More information about tidyquery at CRAN
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Package skpr updated to version 0.61.3 with previous version 0.57.0 dated 2018-11-13

Title: Design of Experiments Suite: Generate and Evaluate Optimal Designs
Description: Generates and evaluates D, I, A, Alias, E, T, and G optimal designs. Supports generation and evaluation of split/split-split/.../N-split plot designs. Includes parametric and Monte Carlo power evaluation functions, and supports calculating power for censored responses. Provides a framework to evaluate power using functions provided in other packages or written by the user. Includes a Shiny graphical user interface that displays the underlying code used to create and evaluate the design to improve ease-of-use and make analyses more reproducible.
Author: Tyler Morgan-Wall [aut, cre], George Khoury [aut]
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>

Diff between skpr versions 0.57.0 dated 2018-11-13 and 0.61.3 dated 2019-09-19

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New package eRTG3D with initial version 0.6.2
Package: eRTG3D
Title: Empirically Informed Random Trajectory Generation in 3-D
Version: 0.6.2
Authors@R: c( person("Merlin", "Unterfinger", email = "info@munterfinger.ch", role = c("aut", "cre")), person("Kamran", "Safi", email = "ksafi@orn.mpg.de", role = c("ctb", "ths")), person("George", "Technitis", email = "george.technitis@gmail.com", role = c("ctb", "ths")), person("Robert", "Weibel", email = "robert.weibel@geo.uzh.ch", role = "ths"))
URL: https://munterfinger.github.io/eRTG3D/, https://github.com/munterfinger/eRTG3D
Description: Creates realistic random trajectories in a 3-D space between two given fix points, so-called conditional empirical random walks (CERWs). The trajectory generation is based on empirical distribution functions extracted from observed trajectories (training data) and thus reflects the geometrical movement characteristics of the mover. A digital elevation model (DEM), representing the Earth's surface, and a background layer of probabilities (e.g. food sources, uplift potential, waterbodies, etc.) can be used to influence the trajectories. Unterfinger M (2018). "3-D Trajectory Simulation in Movement Ecology: Conditional Empirical Random Walk". Master's thesis, University of Zurich. <https://www.geo.uzh.ch/dam/jcr:6194e41e-055c-4635-9807-53c5a54a3be7/MasterThesis_Unterfinger_2018.pdf>. Technitis G, Weibel R, Kranstauber B, Safi K (2016). "An algorithm for empirically informed random trajectory generation between two endpoints". GIScience 2016: Ninth International Conference on Geographic Information Science, 9, online. <doi:10.5167/uzh-130652>.
Depends: R (>= 3.5.0)
Imports: CircStats (>= 0.2-6), ggplot2 (>= 3.1.1), gridExtra (>= 2.3), pbapply (>= 1.4-1), plyr (>= 1.8.4), plotly (>= 4.9.0), raster (>= 2.9-5), rasterVis (>= 0.45), sp (>= 1.3-1), tiff (>= 0.1-5)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr (>= 1.23), pander (>= 0.6.3), rmarkdown (>= 1.13), sf (>= 0.7-4), testthat (>= 2.1.0), covr (>= 3.2.1)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-09-04 14:24:46 UTC; Merlin
Maintainer: Merlin Unterfinger <info@munterfinger.ch>
BugReports: https://github.com/munterfinger/eRTG3D/issues
Author: Merlin Unterfinger [aut, cre], Kamran Safi [ctb, ths], George Technitis [ctb, ths], Robert Weibel [ths]
Repository: CRAN
Date/Publication: 2019-09-19 16:20:02 UTC

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New package DALEXtra with initial version 0.1.7
Package: DALEXtra
Title: Extension for 'DALEX' Package
Version: 0.1.7
Authors@R: c(person(given = "Szymon", family = "Maksymiuk", role = c("aut", "cre"), email = "sz.maksymiuk@gmail.com"), person(given = "Przemyslaw", family = "Biecek", email = "przemyslaw.biecek@gmail.com", role = c("aut"), comment = c(ORCID = "0000-0001-8423-1823")))
Description: Provides wrapper of various machine learning models. In applied machine learning, there is a strong belief that we need to strike a balance between interpretability and accuracy. However, in field of the interpretable machine learning, there are more and more new ideas for explaining black-box models, that are implemented in 'R'. 'DALEXtra' creates 'DALEX' Biecek (2018) <arXiv:1806.08915> explainer for many type of models including those created using 'python' 'scikit-learn' and 'keras' libraries.
Depends: R (>= 3.5.0), DALEX (>= 0.4.7)
License: GPL
LazyData: true
RoxygenNote: 6.1.1
Imports: reticulate
Suggests: gbm, h2o, mljar, mlr, testthat
URL: https://ModelOriented.github.io/DALEXtra/, https://github.com/ModelOriented/DALEXtra
BugReports: https://github.com/ModelOriented/DALEXtra/issues
NeedsCompilation: no
Packaged: 2019-09-03 08:35:55 UTC; szyna
Author: Szymon Maksymiuk [aut, cre], Przemyslaw Biecek [aut] (<https://orcid.org/0000-0001-8423-1823>)
Maintainer: Szymon Maksymiuk <sz.maksymiuk@gmail.com>
Repository: CRAN
Date/Publication: 2019-09-19 16:20:07 UTC

More information about DALEXtra at CRAN
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Package spant updated to version 0.15.0 with previous version 0.14.0 dated 2019-05-28

Title: MR Spectroscopy Analysis Tools
Description: Tools for reading, visualising and processing Magnetic Resonance Spectroscopy data.
Author: Martin Wilson [cre, aut], John Muschelli [ctb]
Maintainer: Martin Wilson <martin@pipegrep.co.uk>

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Package PGRdup updated to version 0.2.3.4 with previous version 0.2.3.3 dated 2018-01-13

Title: Discover Probable Duplicates in Plant Genetic Resources Collections
Description: Provides functions to aid the identification of probable/possible duplicates in Plant Genetic Resources (PGR) collections using 'passport databases' comprising of information records of each constituent sample. These include methods for cleaning the data, creation of a searchable Key Word in Context (KWIC) index of keywords associated with sample records and the identification of nearly identical records with similar information by fuzzy, phonetic and semantic matching of keywords.
Author: J. Aravind [aut, cre] (<https://orcid.org/0000-0002-4791-442X>), J. Radhamani [aut], Kalyani Srinivasan [aut], B. Ananda Subhash [aut], Rishi Kumar Tyagi [aut], ICAR-NBGPR [cph] (www.nbpgr.ernet.in), Maurice Aubrey [ctb] (Double Metaphone), Kevin Atkinson [ctb] (Double Metaphone), Lawrence Philips [ctb] (Double Metaphone)
Maintainer: J. Aravind <j.aravind@icar.gov.in>

Diff between PGRdup versions 0.2.3.3 dated 2018-01-13 and 0.2.3.4 dated 2019-09-19

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Package SimBIID updated to version 0.1.2 with previous version 0.1.1 dated 2019-08-24

Title: Simulation-Based Inference Methods for Infectious Disease Models
Description: Provides some code to run simulations of state-space models, and then use these in the Approximate Bayesian Computation Sequential Monte Carlo (ABC-SMC) algorithm of Toni et al. (2009) <doi:10.1098/rsif.2008.0172> and a bootstrap particle filter based particle Markov chain Monte Carlo (PMCMC) algorithm (Andrieu et al., 2010 <doi:10.1111/j.1467-9868.2009.00736.x>). Also provides functions to plot and summarise the outputs.
Author: Trevelyan J. McKinley [aut, cre], Stefan Widgren [aut] (Author of 'R/mparse.R'), Pavol Bauer [cph] (R/mparse.R), Robin Eriksson [cph] (R/mparse.R), Stefan Engblom [cph] (R/mparse.R)
Maintainer: Trevelyan J. McKinley <t.mckinley@exeter.ac.uk>

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Package epxToR updated to version 0.4-0 with previous version 0.3-0 dated 2017-11-07

Title: Import 'Epidata' XML Files '.epx'
Description: Import data from 'Epidata' XML files '.epx' and convert it to R data structures.
Author: Jean Pierre Decorps [aut, cre], David Whiting [aut], Bruno Granouillac [ctb], Laura March [ctb]
Maintainer: Jean Pierre Decorps <jp.decorps@epiconcept.fr>

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Package sdcTable updated to version 0.30 with previous version 0.29 dated 2019-08-31

Title: Methods for Statistical Disclosure Control in Tabular Data
Description: Methods for statistical disclosure control in tabular data such as primary and secondary cell suppression as described for example in Hundepol et al. (2012) <doi:10.1002/9781118348239> are covered in this package.
Author: Bernhard Meindl
Maintainer: Bernhard Meindl <bernhard.meindl@gmail.com>

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Package onemap updated to version 2.1.2 with previous version 2.1.1 dated 2017-10-18

Title: Construction of Genetic Maps in Experimental Crosses: Full-Sib, RILs, F2 and Backcrosses
Description: Analysis of molecular marker data from model (backcrosses, F2 and recombinant inbred lines) and non-model systems (i. e. outcrossing species). For the later, it allows statistical analysis by simultaneously estimating linkage and linkage phases (genetic map construction) according to Wu et al. (2002) <doi:10.1006/tpbi.2002.1577>. All analysis are based on multipoint approaches using hidden Markov models.
Author: Gabriel Margarido [aut], Marcelo Mollinari [aut], Karl Broman [ctb], Rodrigo Amadeu [ctb], Cristiane Taniguti [ctb, cre], Augusto Garcia [aut, ctb], Getulio Ferreira [ctb]
Maintainer: Cristiane Taniguti <chtaniguti@usp.br>

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New package DivE with initial version 1.1
Package: DivE
Type: Package
Title: Diversity Estimator
Version: 1.1
Date: 2019-09-18
Author: Daniel J. Laydon, Aaron Sim, Charles R.M. Bangham, Becca Asquith
Maintainer: Daniel Laydon <d.laydon@imperial.ac.uk>
Depends: deSolve, FME, rgeos, sp, R (>= 2.15.3)
Description: Contains functions for the 'DivE' estimator <doi:10.1371/journal.pcbi.1003646>. The 'DivE' estimator is a heuristic approach to estimate the number of classes or the number of species (species richness) in a population.
License: GPL (>= 2)
LazyData: TRUE
NeedsCompilation: no
Packaged: 2019-09-19 10:49:40 UTC; dlaydon
Repository: CRAN
Date/Publication: 2019-09-19 13:20:06 UTC

More information about DivE at CRAN
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Package belg updated to version 1.0.0 with previous version 0.2.3 dated 2018-06-17

Title: Boltzmann Entropy of a Landscape Gradient
Description: Calculates the Boltzmann entropy of a landscape gradient. This package uses the analytical method created by Gao, P., Zhang, H. and Li, Z., 2018 (<doi:10.1111/tgis.12315>) and by Gao, P. and Li, Z., 2019 (<doi:10.1007/s10980-019-00854-3>). It also extend the original ideas by allowing calculations on data with missing values.
Author: Jakub Nowosad [aut, cre] (<https://orcid.org/0000-0002-1057-3721>), Space Informatics Lab [cph]
Maintainer: Jakub Nowosad <nowosad.jakub@gmail.com>

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Package spData updated to version 0.3.2 with previous version 0.3.0 dated 2019-01-07

Title: Datasets for Spatial Analysis
Description: Diverse spatial datasets for demonstrating, benchmarking and teaching spatial data analysis. It includes R data of class sf (defined by the package 'sf'), Spatial ('sp'), and nb ('spdep'). Unlike other spatial data packages such as 'rnaturalearth' and 'maps', it also contains data stored in a range of file formats including GeoJSON, ESRI Shapefile and GeoPackage. Some of the datasets are designed to illustrate specific analysis techniques. cycle_hire() and cycle_hire_osm(), for example, is designed to illustrate point pattern analysis techniques.
Author: Roger Bivand [aut] (<https://orcid.org/0000-0003-2392-6140>), Jakub Nowosad [aut, cre] (<https://orcid.org/0000-0002-1057-3721>), Robin Lovelace [aut] (<https://orcid.org/0000-0001-5679-6536>), Mark Monmonier [ctb] (author of the state.vbm dataset), Greg Snow [ctb] (author of the state.vbm dataset)
Maintainer: Jakub Nowosad <nowosad.jakub@gmail.com>

Diff between spData versions 0.3.0 dated 2019-01-07 and 0.3.2 dated 2019-09-19

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Package explore updated to version 0.5.0 with previous version 0.4.4 dated 2019-08-27

Title: Simplifies Exploratory Data Analysis
Description: Interactive data exploration with one line of code or use an easy to remember set of tidy functions for exploratory data analysis. Introduces two main verbs. describe() to describe a variable or table, explore() to graphically explore a variable or table.
Author: Roland Krasser
Maintainer: Roland Krasser <roland.krasser@gmail.com>

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Package compound.Cox updated to version 3.19 with previous version 3.18 dated 2019-07-04

Title: Univariate Feature Selection and Compound Covariate for Predicting Survival
Description: Univariate feature selection and compound covariate methods under the Cox model with high-dimensional features (e.g., gene expressions). Available are survival data for non-small-cell lung cancer patients with gene expressions (Chen et al 2007 New Engl J Med) <DOI:10.1056/NEJMoa060096>, statistical methods in Emura et al (2012 PLoS ONE) <DOI:10.1371/journal.pone.0047627>, Emura & Chen (2016 Stat Methods Med Res) <DOI:10.1177/0962280214533378>, and Emura et al. (2019)<DOI:10.1016/j.cmpb.2018.10.020>. Algorithms for generating correlated gene expressions are also available.
Author: Takeshi Emura, Hsuan-Yu Chen, Shigeyuki Matsui, Yi-Hau Chen
Maintainer: Takeshi Emura <takeshiemura@gmail.com>

Diff between compound.Cox versions 3.18 dated 2019-07-04 and 3.19 dated 2019-09-19

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Package anomaly updated to version 2.0.2 with previous version 2.0.1 dated 2019-09-11

Title: Detecting Anomalies in Data
Description: Implements Collective And Point Anomaly (CAPA) <arXiv:1806.01947>, Multi-Variate Collective And Point Anomaly (MVCAPA) <arXiv:1909.01691>, and Proportion Adaptive Segment Selection (PASS) <doi:10.1093/biomet/ass059> methods for the detection of anomalies in time series data.
Author: Alex Fisch [aut], Daniel Grose [aut, cre], Lawrence Bardwell [ctb], Idris Eckley [ths], Paul Fearnhead [ths]
Maintainer: Daniel Grose <dan.grose@lancaster.ac.uk>

Diff between anomaly versions 2.0.1 dated 2019-09-11 and 2.0.2 dated 2019-09-19

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Package cNORM updated to version 1.2.2 with previous version 1.2.0 dated 2019-07-26

Title: Continuous Norming
Description: Conventional methods for producing standard scores in psychometrics or biometrics are often plagued with "jumps" or "gaps" (i.e., discontinuities) in norm tables and low confidence for assessing extreme scores. The continuous norming method introduced by A. Lenhard et al. (2016, <doi:10.1177/1073191116656437>; 2019, <doi:10.1371/journal.pone.0222279>) and generates continuous test norm scores on the basis of the raw data from standardization samples, without requiring assumptions about the distribution of the raw data: Norm scores are directly established from raw data by modeling the latter ones as a function of both percentile scores and an explanatory variable (e.g., age). The method minimizes bias arising from sampling and measurement error, while handling marked deviations from normality, addressing bottom or ceiling effects and capturing almost all of the variance in the original norm data sample.
Author: Wolfgang Lenhard [cre, aut] (<https://orcid.org/0000-0002-8184-6889>), Alexandra Lenhard [aut], Sebastian Gary [ctb]
Maintainer: Wolfgang Lenhard <wolfgang.lenhard@uni-wuerzburg.de>

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New package backbone with initial version 1.0.0
Package: backbone
Type: Package
Title: Extracts the Backbone from Weighted Graphs
Version: 1.0.0
Authors@R: c( person("Rachel", "Domagalski", email = "domagal9@msu.edu", role = c("aut", "cre")), person("Zachary", "Neal", email = "zpneal@msu.edu", role = "aut"), person("Bruce", "Sagan", email = "bsagan@msu.edu", role = "aut"))
Description: Provides methods for extracting from a weighted graph a binary or signed backbone that retains only the significant edges. The user may input a weighted graph, or a bipartite graph from which a weighted graph is first constructed via projection. Backbone extraction methods include the stochastic degree sequence model (Neal, Z. P. (2014). <doi:10.1016/j.socnet.2014.06.001>), hypergeometric model (Neal, Z. (2013). <doi:10.1007/s13278-013-0107-y>), the fixed degree sequence model (Zweig, K. A., and Kaufmann, M. (2011). <doi:10.1007/s13278-011-0021-0>), as well as a universal threshold method.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 2.10)
Imports: Matrix, utils, stats
Suggests: knitr, rmarkdown, testthat, igraph
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-09-11 21:23:28 UTC; Rachel
Author: Rachel Domagalski [aut, cre], Zachary Neal [aut], Bruce Sagan [aut]
Maintainer: Rachel Domagalski <domagal9@msu.edu>
Repository: CRAN
Date/Publication: 2019-09-19 10:30:02 UTC

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Package amt updated to version 0.0.7 with previous version 0.0.6 dated 2019-03-19

Title: Animal Movement Tools
Description: Manage and analyze animal movement data. The functionality of 'amt' includes methods to calculate track statistics (e.g. step lengths, speed, or turning angles), prepare data for fitting habitat selection analyses (resource and step-selection functions), and simulation of space-use from fitted step-selection functions.
Author: Johannes Signer [aut, cre], Bjoern Reineking [ctb], Ulrike Schlaegel [ctb], Scott LaPoint [dtc]
Maintainer: Johannes Signer <jsigner@gwdg.de>

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Package streambugs updated to version 1.1 with previous version 1.0 dated 2017-11-29

Title: Parametric Ordinary Differential Equations Model of Growth, Death, and Respiration of Macroinvertebrate and Algae Taxa
Description: Numerically solve and plot solutions of a parametric ordinary differential equations model of growth, death, and respiration of macroinvertebrate and algae taxa dependent on pre-defined environmental factors. The model (version 1.0) is introduced in Schuwirth, N. and Reichert, P., (2013) <DOI:10.1890/12-0591.1>. This package includes model extensions and the core functions introduced and used in Schuwirth, N. et al. (2016) <DOI:10.1111/1365-2435.12605>, Kattwinkel, M. et al. (2016) <DOI:10.1021/acs.est.5b04068>, Mondy, C. P., and Schuwirth, N. (2017) <DOI:10.1002/eap.1530>, and Paillex, A. et al. (2017) <DOI:10.1111/fwb.12927>.
Author: Nele Schuwirth, Peter Reichert, Mikolaj Rybinski
Maintainer: Nele Schuwirth <nele.schuwirth@eawag.ch>

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New package bdl with initial version 1.0.0
Package: bdl
Type: Package
Date: 2019-08-21
Title: Interface and Tools for 'BDL' API
Version: 1.0.0
Authors@R: c(person("Krzysztof", "Kania", email = "K.Kania@stat.gov.pl", role = c("aut", "cre")), person(given = "Statistics Poland", role = c("cph", "fnd")))
Description: Interface to Local Data Bank ('Bank Danych Lokalnych' - 'bdl') API <https://api.stat.gov.pl/Home/BdlApi?lang=en> with set of useful tools like quick plotting and map generating using data from bank.
License: GPL-3
Depends: R (>= 3.5.0)
Imports: methods, magrittr, tibble, jsonlite, httr, dplyr, tidyr, utils, stats, ggplot2, ggpubr, randomcoloR, purrr, sf, tmaptools, tmap
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Repository: CRAN
RoxygenNote: 6.1.1
URL: https://github.com/statisticspoland/R_Package_to_API_BDL
BugReports: https://github.com/statisticspoland/R_Package_to_API_BDL/issues
Packaged: 2019-09-11 11:31:21 UTC; Krzysztof
Author: Krzysztof Kania [aut, cre], Statistics Poland [cph, fnd]
Maintainer: Krzysztof Kania <K.Kania@stat.gov.pl>
Date/Publication: 2019-09-19 09:50:02 UTC

More information about bdl at CRAN
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Package tradestatistics updated to version 0.2.5 with previous version 0.2.4 dated 2019-09-17

Title: Open Trade Statistics API Wrapper and Utility Program
Description: Access 'Open Trade Statistics' API from R to download international trade data.
Author: Mauricio Vargas [aut, cre, cph] (<https://orcid.org/0000-0003-1017-7574>), Joshua Kunst [ctb] (contributed to different parts of the pre-release code), Emily Riederer [rev] (reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/274), Mark Padgham [rev] (reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/274), Amanda Dobbyn [rev] (reviewed an archived package that evolved into the current package for rOpenSci, see https://github.com/ropensci/onboarding/issues/217), Jorge Cimentada [rev] (reviewed an archived package that evolved into the current package for rOpenSci, see https://github.com/ropensci/onboarding/issues/217), UN Comtrade [dtc], The World Bank [dtc], Center for International Development at Harvard University [dtc], The Observatory of Economic Complexity [dtc]
Maintainer: Mauricio Vargas <mvargas@dcc.uchile.cl>

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Permanent link

Package smerc updated to version 1.1 with previous version 1.0.1 dated 2019-07-15

Title: Statistical Methods for Regional Counts
Description: Implements statistical methods for analyzing the counts of areal data, with a focus on the detection of spatial clusters and clustering. The package has a heavy emphasis on spatial scan methods, first introduced by Kulldorff and Nagarwalla (1995) <doi:10.1002/sim.4780140809> and Kulldorff (1997) <doi:10.1080/03610929708831995>.
Author: Joshua French
Maintainer: Joshua French <joshua.french@ucdenver.edu>

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Package rlas updated to version 1.3.4 with previous version 1.3.3 dated 2019-08-30

Title: Read and Write 'las' and 'laz' Binary File Formats Used for Remote Sensing Data
Description: Read and write 'las' and 'laz' binary file formats. The LAS file format is a public file format for the interchange of 3-dimensional point cloud data between data users. The LAS specifications are approved by the American Society for Photogrammetry and Remote Sensing <https://www.asprs.org/committee-general/laser-las-file-format-exchange-activities.html>. The LAZ file format is an open and lossless compression scheme for binary LAS format versions 1.0 to 1.3 <https://www.laszip.org/>.
Author: Jean-Romain Roussel [aut, cre, cph], Florian De Boissieu [aut, ctb] (Enable the support of .lax file and extra byte attributes), Martin Isenburg [cph] (Is the author of the LASlib and LASzip libraries), David Auty [ctb] (Reviewed the documentation), Pierrick Marie [ctb] (Helped to compile LASlib code in R), Tiago de Conto [ctb] (Implemented the -thin_with_voxel filter method)
Maintainer: Jean-Romain Roussel <jean-romain.roussel.1@ulaval.ca>

Diff between rlas versions 1.3.3 dated 2019-08-30 and 1.3.4 dated 2019-09-19

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Package pksensi updated to version 1.1.4 with previous version 1.1.3 dated 2019-08-20

Title: Global Sensitivity Analysis in Physiologically Based Kinetic Modeling
Description: Applying the global sensitivity analysis workflow to investigate the parameter uncertainty and sensitivity in physiologically based kinetic (PK) models, especially the physiologically based pharmacokinetic/toxicokinetic model with multivariate outputs. The package also provides some functions to check the convergence and sensitivity of model parameters.
Author: Nan-Hung Hsieh [aut, cre] (<https://orcid.org/0000-0003-0163-2766>), Brad Reisfeld [aut], Weihsueh A. Chiu [aut] (<https://orcid.org/0000-0002-7575-2368>)
Maintainer: Nan-Hung Hsieh <nhsieh@cvm.tamu.edu>

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New package HSROC with initial version 2.1.9
Package: HSROC
Type: Package
Title: Meta-Analysis of Diagnostic Test Accuracy when Reference Test is Imperfect
Version: 2.1.9
Date: 2019-09-18
Author: Ian Schiller and Nandini Dendukuri
Maintainer: Ian Schiller <ian.schiller@rimuhc.ca>
Depends: R (>= 3.5.0), lattice, coda, MASS, MCMCpack
Description: Implements a model for joint meta-analysis of sensitivity and specificity of the diagnostic test under evaluation, while taking into account the possibly imperfect sensitivity and specificity of the reference test. This hierarchical model accounts for both within and between study variability. Estimation is carried out using a Bayesian approach, implemented via a Gibbs sampler. The model can be applied in situations where more than one reference test is used in the selected studies.
License: GPL-2
URL: http://www.nandinidendukuri.com/
Encoding: latin1
NeedsCompilation: yes
Packaged: 2019-09-18 18:01:25 UTC; ischiller
Repository: CRAN
Date/Publication: 2019-09-19 08:40:12 UTC

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Package dtwclust updated to version 5.5.5 with previous version 5.5.4 dated 2019-07-07

Title: Time Series Clustering Along with Optimizations for the Dynamic Time Warping Distance
Description: Time series clustering along with optimized techniques related to the Dynamic Time Warping distance and its corresponding lower bounds. Implementations of partitional, hierarchical, fuzzy, k-Shape and TADPole clustering are available. Functionality can be easily extended with custom distance measures and centroid definitions. Implementations of DTW barycenter averaging, a distance based on global alignment kernels, and the soft-DTW distance and centroid routines are also provided. All included distance functions have custom loops optimized for the calculation of cross-distance matrices, including parallelization support. Several cluster validity indices are included.
Author: Alexis Sarda-Espinosa
Maintainer: Alexis Sarda <alexis.sarda@gmail.com>

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Package concurve updated to version 2.1.0 with previous version 2.0 dated 2019-07-10

Title: Computes and Plots Consonance (Confidence) Intervals, P-Values, and S-Values to Form Consonance and Surprisal Functions
Description: Allows one to compute consonance (confidence) intervals for various statistical tests along with their corresponding P-values and S-values. The intervals can be plotted to create consonance and surprisal functions allowing one to see what effect sizes are compatible with the test model at various consonance levels rather than being limited to one interval estimate such as 95%. These methods are discussed by Poole C. (1987) <doi:10.2105/AJPH.77.2.195>, Schweder T, Hjort NL. (2002) <doi:10.1111/1467-9469.00285>, Singh K, Xie M, Strawderman WE. (2007) <arXiv:0708.0976>, Rothman KJ, Greenland S, Lash TL. (2008, ISBN:9781451190052), Amrhein V, Trafimow D, Greenland S. (2019) <doi:10.1080/00031305.2018.1543137>, Greenland S. (2019) <doi:10.1080/00031305.2018.1529625>, Chow ZR, Greenland S. (2019) <arXiv:1909.08579>, and Greenland S, Chow ZR. (2019) <arXiv:1909.08583>.
Author: Zad R. Chow [aut, cre] (<https://orcid.org/0000-0003-1545-8199>), Andrew D. Vigotsky [aut] (<https://orcid.org/0000-0003-3166-0688>)
Maintainer: Zad R. Chow <zad@lesslikely.com>

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Package compareGroups updated to version 4.2.0 with previous version 4.1.0 dated 2019-05-27

Title: Descriptive Analysis by Groups
Description: Create data summaries for quality control, extensive reports for exploring data, as well as publication-ready univariate or bivariate tables in several formats (plain text, HTML,LaTeX, PDF, Word or Excel. Create figures to quickly visualise the distribution of your data (boxplots, barplots, normality-plots, etc.). Display statistics (mean, median, frequencies, incidences, etc.). Perform the appropriate tests (t-test, Analysis of variance, Kruskal-Wallis, Fisher, log-rank, ...) depending on the nature of the described variable (normal, non-normal or qualitative). Summarize genetic data (Single Nucleotide Polymorphisms) data displaying Allele Frequencies and performing Hardy-Weinberg Equilibrium tests among other typical statistics and tests for these kind of data.
Author: Isaac Subirana [aut, cre] (<https://orcid.org/0000-0003-1676-0197>), Joan Salvador [ctb]
Maintainer: Isaac Subirana <isubirana@imim.es>

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New package colocalized with initial version 0.1.0
Package: colocalized
Type: Package
Title: Clusters of Colocalized Sequences
Version: 0.1.0
Authors@R: person("Stefan", "Golas", email = "stefanmgolas@gmail.com", role = c("cre","aut"))
Description: Finds clusters of colocalized sequences in .bed annotation files up to a specified cut-off distance. Two sequences are colocalized if they are within the cut-off distance of each other, and clusters are sets of sequences where each sequence is colocalized to at least one other sequence in the cluster. For a set of .bed annotation tables provided in a list along with a cut-off distance, the program will output a file containing the locations of each cluster. Annotated .bed files are from the 'pwmscan' application at <https://ccg.epfl.ch/pwmtools/pwmscan.php>. Personal machines might crash or take excessively long depending on the number of annotated sequences in each file and whether chromsearch() or gensearch() is used.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1.9000
Depends: R (>= 3.0.0)
Imports: foreach, doParallel, purrr, utils
NeedsCompilation: no
Packaged: 2019-09-11 11:09:28 UTC; Stefan
Author: Stefan Golas [cre, aut]
Maintainer: Stefan Golas <stefanmgolas@gmail.com>
Repository: CRAN
Date/Publication: 2019-09-19 09:00:10 UTC

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Package projector (with last version 0.0.2) was removed from CRAN

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

2018-02-27 0.0.2
2017-09-28 0.0.1

Permanent link
Package umx updated to version 3.0.0 with previous version 2.10.0 dated 2019-04-25

Title: Structural Equation and Twin Modeling in R
Description: Quickly create, run, and report structural equation and twin models. See '?umx' for help, and umx_open_CRAN_page("umx") for NEWS.
Author: Timothy C Bates [aut, cre] (<https://orcid.org/0000-0002-1153-9007>)
Maintainer: Timothy C Bates <timothy.c.bates@gmail.com>

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 324 files changed, 10607 insertions(+), 7588 deletions(-)

More information about umx at CRAN
Permanent link

Package regressoR updated to version 1.1.8 with previous version 1.1.7 dated 2019-06-11

Title: Regression Data Analysis System
Description: Perform a supervised data analysis on a database through a 'shiny' graphical interface. It includes methods such as linear regression, penalized regression, k-nearest neighbors, decision trees, ada boosting, extreme gradient boosting, random forest, neural networks, deep learning and support vector machines.
Author: Oldemar Rodriguez R. [aut, cre], Andres Navarro D. [ctb, prg], Diego Jimenez A. [ctb, prg]
Maintainer: Oldemar Rodriguez R. <oldemar.rodriguez@ucr.ac.cr>

Diff between regressoR versions 1.1.7 dated 2019-06-11 and 1.1.8 dated 2019-09-19

 DESCRIPTION                              |    6 +++---
 MD5                                      |   11 ++++++-----
 R/code_generate.R                        |    2 +-
 README.md                                |only
 inst/application/server.R                |    9 ++++-----
 inst/application/ui.R                    |    7 ++++---
 inst/application/www/style_regressor.css |    4 ----
 7 files changed, 18 insertions(+), 21 deletions(-)

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Package OPI updated to version 2.9 with previous version 2.7 dated 2017-10-25

Title: Open Perimetry Interface
Description: Implementation of the Open Perimetry Interface (OPI) for simulating and controlling visual field machines using R. The OPI is a standard for interfacing with visual field testing machines (perimeters). It specifies basic functions that allow many visual field tests to be constructed. As of October 2017 it is fully implemented on the Octopus 900 and partially on the Heidelberg Edge Perimeter, the Kowa AP 7000, the CrewT imo and the Centervue Compass. It also has a cousin: the R package 'visualFields', which has tools for analysing and manipulating visual field data.
Author: Andrew Turpin [cre, aut, cph], David Lawson [ctb, cph], Matthias Muller [ctb], Jonathan Dennis [ctb, cph], Astrid Zeman [ctb], Ivan Marin-Franch [ctb]
Maintainer: Andrew Turpin <aturpin@unimelb.edu.au>

Diff between OPI versions 2.7 dated 2017-10-25 and 2.9 dated 2019-09-19

 OPI-2.7/OPI/ChangeLog                |only
 OPI-2.9/OPI/DESCRIPTION              |   24 +++-
 OPI-2.9/OPI/MD5                      |   54 +++++-----
 OPI-2.9/OPI/NAMESPACE                |   13 +-
 OPI-2.9/OPI/NEWS.md                  |only
 OPI-2.9/OPI/R/compassClient.r        |  124 ++++++++++++-----------
 OPI-2.9/OPI/R/daydreamClient.r       |only
 OPI-2.9/OPI/R/imoClient.r            |  134 ++++++++++++-------------
 OPI-2.9/OPI/R/kowaAP7000Client.r     |  169 +++++++++++++++----------------
 OPI-2.9/OPI/R/mocs.r                 |   78 ++++++++++----
 OPI-2.9/OPI/R/octopus600.r           |   52 ++++-----
 OPI-2.9/OPI/R/octopus900Client.r     |  185 +++++++++++++----------------------
 OPI-2.9/OPI/R/opi.r                  |   31 +++--
 OPI-2.9/OPI/R/pix2deg.r              |only
 OPI-2.9/OPI/R/simDisplay.r           |   45 ++++----
 OPI-2.9/OPI/R/simG.r                 |   14 +-
 OPI-2.9/OPI/R/simH.r                 |   51 ++++-----
 OPI-2.9/OPI/R/simH_RT.r              |   60 +++++------
 OPI-2.9/OPI/R/zest.r                 |   50 +++++++--
 OPI-2.9/OPI/README.md                |only
 OPI-2.9/OPI/man/MOCS.Rd              |   34 ++++--
 OPI-2.9/OPI/man/OPI-package.Rd       |    5 
 OPI-2.9/OPI/man/ZEST.Rd              |   27 ++++-
 OPI-2.9/OPI/man/degTopix.Rd          |only
 OPI-2.9/OPI/man/opiClose.Rd          |    6 +
 OPI-2.9/OPI/man/opiInitialize.Rd     |   26 +++-
 OPI-2.9/OPI/man/opiPresent.Rd        |   27 ++---
 OPI-2.9/OPI/man/opiQueryDevice.Rd    |    5 
 OPI-2.9/OPI/man/opiSetBackground.Rd  |   13 ++
 OPI-2.9/OPI/man/opiStaticStimulus.Rd |    6 -
 OPI-2.9/OPI/man/pixTodeg.Rd          |only
 OPI-2.9/OPI/tests/k_test.r           |only
 32 files changed, 680 insertions(+), 553 deletions(-)

More information about OPI at CRAN
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Package inca updated to version 0.0.4 with previous version 0.0.3 dated 2018-02-12

Title: Integer Calibration
Description: Specific functions are provided for rounding real weights to integers and performing an integer programming algorithm for calibration problems. They are useful for census-weights adjustments, or for performing linear regression with integer parameters. This research was supported in part by the U.S. Department of Agriculture, National Agriculture Statistics Service. The findings and conclusions in this publication are those of the authors and should not be construed to represent any official USDA, or US Government determination or policy.
Author: Luca Sartore <luca.sartore@usda.gov> and Kelly Toppin <kelly.toppin@nass.usda.gov>
Maintainer: Luca Sartore <drwolf85@gmail.com>

Diff between inca versions 0.0.3 dated 2018-02-12 and 0.0.4 dated 2019-09-19

 ChangeLog           |  109 ++++++++++++++++++++++++++++++++++++----------------
 DESCRIPTION         |   17 ++++----
 MD5                 |   34 ++++++++--------
 NAMESPACE           |    4 -
 R/inca.R            |   35 ++++++++++------
 R/intcalibrate.R    |    2 
 R/roundWeights.R    |    2 
 README.md           |   20 +++++----
 inst/INSTALL.md     |   12 ++---
 man/inca-package.Rd |   30 ++++++++------
 src/Losses/L1.h     |    2 
 src/Losses/LB1.h    |    2 
 src/Losses/aL1.h    |    2 
 src/Losses/rB1.h    |    2 
 src/Losses/rL1.h    |    2 
 src/bestRound.h     |    4 -
 src/inca.cpp        |   95 +++++++++++++++++++++++++++++++++++++++++++--
 src/intCalib.h      |    8 +--
 18 files changed, 266 insertions(+), 116 deletions(-)

More information about inca at CRAN
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