Wed, 25 Mar 2020

Package semEff updated to version 0.3.0 with previous version 0.2.1 dated 2020-01-15

Title: Automatic Calculation of Effects for Piecewise Structural Equation Models
Description: Provides functionality to automatically calculate direct, indirect, and total effects from piecewise structural equation models, comprising lists of fitted models representing structured equations (Lefcheck 2016 <doi:10/f8s8rb>). Confidence intervals are provided via bootstrapping.
Author: Mark Murphy [aut, cre]
Maintainer: Mark Murphy <murphymv@gmail.com>

Diff between semEff versions 0.2.1 dated 2020-01-15 and 0.3.0 dated 2020-03-25

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Package TSrepr updated to version 1.0.4 with previous version 1.0.3 dated 2019-05-31

Title: Time Series Representations
Description: Methods for representations (i.e. dimensionality reduction, preprocessing, feature extraction) of time series to help more accurate and effective time series data mining. Non-data adaptive, data adaptive, model-based and data dictated (clipped) representation methods are implemented. Also min-max and z-score normalisations, and forecasting accuracy measures are implemented.
Author: Peter Laurinec [aut, cre] (<https://orcid.org/0000-0002-3501-8783>)
Maintainer: Peter Laurinec <tsreprpackage@gmail.com>

Diff between TSrepr versions 1.0.3 dated 2019-05-31 and 1.0.4 dated 2020-03-25

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Package Rwofost updated to version 0.6-3 with previous version 0.6-1 dated 2020-03-22

Title: WOFOST Crop Growth Simulation Model
Description: An implementation of the WOFOST ("World Food Studies") crop growth model. WOFOST is a dynamic simulation model that uses daily weather data, and crop, soil and management parameters to simulate crop growth and development. See De Wit et al. (2019) <doi:10.1016/j.agsy.2018.06.018> for a recent review of the history and use of the model.
Author: Robert J. Hijmans [cre, aut], Huang Fang [ctb], C.A. van Diepen [ctb], Allard de Wit [ctb], Daniel van Kraalingen [ctb], Tamme van der Wal [ctb], C. Rappoldt [ctb], Hendrik Boogard [ctb], I.G.A.M. Noy [ctb], Alterra, Wageningen-UR [cph]
Maintainer: Robert J. Hijmans <r.hijmans@gmail.com>

Diff between Rwofost versions 0.6-1 dated 2020-03-22 and 0.6-3 dated 2020-03-25

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 16 files changed, 365 insertions(+), 367 deletions(-)

More information about Rwofost at CRAN
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Package pkgdown updated to version 1.5.0 with previous version 1.4.1 dated 2019-09-14

Title: Make Static HTML Documentation for a Package
Description: Generate an attractive and useful website from a source package. 'pkgdown' converts your documentation, vignettes, 'README', and more to 'HTML' making it easy to share information about your package online.
Author: Hadley Wickham [aut, cre] (<https://orcid.org/0000-0003-4757-117X>), Jay Hesselberth [aut] (<https://orcid.org/0000-0002-6299-179X>), RStudio [cph, fnd]
Maintainer: Hadley Wickham <hadley@rstudio.com>

Diff between pkgdown versions 1.4.1 dated 2019-09-14 and 1.5.0 dated 2020-03-25

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More information about pkgdown at CRAN
Permanent link

Package GGally updated to version 1.5.0 with previous version 1.4.0 dated 2018-05-17

Title: Extension to 'ggplot2'
Description: The R package 'ggplot2' is a plotting system based on the grammar of graphics. 'GGally' extends 'ggplot2' by adding several functions to reduce the complexity of combining geometric objects with transformed data. Some of these functions include a pairwise plot matrix, a two group pairwise plot matrix, a parallel coordinates plot, a survival plot, and several functions to plot networks.
Author: Barret Schloerke [aut, cre] (author for ggpairs, ggduo, ggnostic, ggts, ggfacet, and ggally_*. Contributor for all functions.), Jason Crowley [aut] (ggparcoord), Di Cook [aut, ths] (ggscatmat, gglyph), Heike Hofmann [ths], Hadley Wickham [ths], Francois Briatte [aut] (ggcorr, ggnet, ggnet2), Moritz Marbach [aut] (ggnet, ggnet2), Edwin Thoen [aut] (ggsurv), Amos Elberg [aut] (ggnetworkmap), Joseph Larmarange [aut] (ggcoef), Ott Toomet [ctb]
Maintainer: Barret Schloerke <schloerke@gmail.com>

Diff between GGally versions 1.4.0 dated 2018-05-17 and 1.5.0 dated 2020-03-25

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More information about GGally at CRAN
Permanent link

Package fasterize updated to version 1.0.2 with previous version 1.0.0 dated 2018-03-22

Title: Fast Polygon to Raster Conversion
Description: Provides a drop-in replacement for rasterize() from the 'raster' package that takes 'sf'-type objects, and is much faster. There is support for the main options provided by the rasterize() function, including setting the field used and background value, and options for aggregating multi-layer rasters. Uses the scan line algorithm attributed to Wylie et al. (1967) <doi:10.1145/1465611.1465619>.
Author: Noam Ross [aut, cre] (<https://orcid.org/0000-0002-2136-0000>), Michael Sumner [ctb] (<https://orcid.org/0000-0002-2471-7511>), EcoHealth Alliance [cph], USAID PREDICT [fnd]
Maintainer: Noam Ross <ross@ecohealthalliance.org>

Diff between fasterize versions 1.0.0 dated 2018-03-22 and 1.0.2 dated 2020-03-25

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Package DriftBurstHypothesis updated to version 0.4.0 with previous version 0.3.0 dated 2019-11-28

Title: Calculates the Test-Statistic for the Drift Burst Hypothesis
Description: Calculates the T-Statistic for the drift burst hypothesis from the working paper Christensen, Oomen and Reno (2018) <DOI:10.2139/ssrn.2842535>. The authors' MATLAB code is available upon request, see: <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2842535>.
Author: Emil Sjoerup
Maintainer: Emil Sjoerup <emilsjoerup@live.dk>

Diff between DriftBurstHypothesis versions 0.3.0 dated 2019-11-28 and 0.4.0 dated 2020-03-25

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 DESCRIPTION               |   10 
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 NAMESPACE                 |   31 +-
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Package datetimeutils updated to version 0.4-0 with previous version 0.3-0 dated 2019-03-21

Title: Utilities for Dates and Times
Description: Utilities for handling dates and times, such as selecting particular days of the week or month, formatting timestamps as required by RSS feeds, or converting timestamp representations of other software (such as 'MATLAB' and 'Excel') to R. The package is lightweight (no dependencies, pure R implementations) and relies only on R's standard classes to represent dates and times ('Date' and 'POSIXt'); it aims to provide efficient implementations, through vectorisation and the use of R's native numeric representations of timestamps where possible.
Author: Enrico Schumann [aut, cre] (<https://orcid.org/0000-0001-7601-6576>), Unicode, Inc. [dtc, cph] (source of timezone names in 'tznames')
Maintainer: Enrico Schumann <es@enricoschumann.net>

Diff between datetimeutils versions 0.3-0 dated 2019-03-21 and 0.4-0 dated 2020-03-25

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New package comparer with initial version 0.2.1
Package: comparer
Type: Package
Title: Compare Output and Run Time
Version: 0.2.1
Authors@R: c( person("Collin", "Erickson", , "collinberickson@gmail.com", c("aut", "cre")) )
Description: Quickly run experiments to compare the run time and output of code blocks. The function mbc() can make fast comparisons of code, and will calculate statistics comparing the resulting outputs. It can be used to compare model fits to the same data or see which function runs faster. The function ffexp() runs a function using all possible combinations of selected inputs. This is useful for comparing the effect of different parameter values. It can also run in parallel and automatically save intermediate results, which is very useful for long computations.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: R6
Suggests: plyr, progress, testthat, covr, knitr, ggplot2, parallel, snow, rmarkdown, reshape, tibble, microbenchmark
RoxygenNote: 7.1.0
URL: https://github.com/CollinErickson/comparer
BugReports: https://github.com/CollinErickson/comparer/issues
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2020-03-25 01:00:29 UTC; collin
Author: Collin Erickson [aut, cre]
Maintainer: Collin Erickson <collinberickson@gmail.com>
Repository: CRAN
Date/Publication: 2020-03-25 18:20:03 UTC

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Package cold updated to version 2.0-1 with previous version 2.0-0 dated 2019-07-22

Title: Count Longitudinal Data
Description: Performs regression analysis for longitudinal count data, allowing for serial dependence among observations from a given individual and two dimensional random effects on the linear predictor. Estimation is via maximization of the exact likelihood of a suitably defined model. Missing values and unbalanced data are allowed; M. Helena Goncalves et al.(2007) <doi:10.1016/j.csda.2007.03.002>.
Author: M. Helena Goncalves and M. Salome Cabral, apart from a set of Fortran-77 subroutines written by R. Piessens and E. de Doncker, belonging to the suite "Quadpack".
Maintainer: M. Helena Goncalves <mhgoncal@ualg.pt>

Diff between cold versions 2.0-0 dated 2019-07-22 and 2.0-1 dated 2020-03-25

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New package coinmarketcapr with initial version 0.3.2
Package: coinmarketcapr
Type: Package
Title: Get 'Cryptocurrencies' Market Cap Prices from Coin Market Cap
Version: 0.3.2
Authors@R: c( person("AbdulMajedRaja","RS", email = "amrrs.data@gmail.com", role = c("aut", "cre")), person("Sebastian","Gatscha", email = "sebastian_gatscha@gmx.at", role = c("aut", "ctb")) )
Description: Extract and monitor price and market cap of 'Cryptocurrencies' from 'Coin Market Cap' <https://coinmarketcap.com/api/>.
URL: http://github.com/amrrs/coinmarketcapr
License: MIT + file LICENSE
LazyData: true
Imports: jsonlite, ggplot2, data.table, curl, cli, crayon
Suggests: testthat, knitr, rmarkdown, ggthemes, dplyr
RoxygenNote: 7.1.0
Encoding: UTF-8
BugReports: https://github.com/amrrs/coinmarketcapr/issues
NeedsCompilation: no
Packaged: 2020-03-25 18:02:44 UTC; abdrs
Author: AbdulMajedRaja RS [aut, cre], Sebastian Gatscha [aut, ctb]
Maintainer: AbdulMajedRaja RS <amrrs.data@gmail.com>
Repository: CRAN
Date/Publication: 2020-03-25 18:20:09 UTC

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Package causaloptim updated to version 0.6.5 with previous version 0.6.4 dated 2020-03-20

Title: An Interface to Specify Causal Graphs and Compute Bounds on Causal Effects
Description: When causal quantities are not identifiable from the observed data, it still may be possible to bound these quantities using the observed data. We outline a class of problems for which the derivation of tight bounds is always a linear programming problem and can therefore, at least theoretically, be solved using a symbolic linear optimizer. We extend and generalize the approach of Balke and Pearl (1994) <doi:10.1016/B978-1-55860-332-5.50011-0> and we provide a user friendly graphical interface for setting up such problems via directed acyclic graphs (DAG), which only allow for problems within this class to be depicted. The user can then define linear constraints to further refine their assumptions to meet their specific problem, and then specify a causal query using a text interface. The program converts this user defined DAG, query, and constraints, and returns tight bounds. The bounds can be converted to R functions to evaluate them for specific datasets, and to latex code for publication. The methods and proofs of tightness and validity of the bounds are described in a preprint by Sachs, Gabriel, and Sjölander (2020) <https://sachsmc.github.io/causaloptim/articles/CausalBoundsMethods.pdf>.
Author: Michael C Sachs [aut, cre], Erin E Gabriel [aut], Arvid Sjölander [aut], Alexander A Balke [ctb] ((C++ code)), Colorado Reed [ctb] ((graph-creator.js))
Maintainer: Michael C Sachs <sachsmc@gmail.com>

Diff between causaloptim versions 0.6.4 dated 2020-03-20 and 0.6.5 dated 2020-03-25

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Package seagull updated to version 1.0.6 with previous version 1.0.5 dated 2020-01-31

Title: Lasso, Group Lasso, and Sparse-Group Lasso for Mixed Models
Description: Proximal gradient descent solver for the operators lasso, group lasso, and sparse-group lasso. The implementation involves backtracking line search and warm starts. Input data needs to be clustered/grouped for the (sparse-)group lasso before calling these algorithms.
Author: Jan Klosa [aut, cre], Noah Simon [ths], Dörte Wittenburg [ths]
Maintainer: Jan Klosa <klosa@fbn-dummerstorf.de>

Diff between seagull versions 1.0.5 dated 2020-01-31 and 1.0.6 dated 2020-03-25

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Package nonmemica updated to version 0.9.1 with previous version 0.9.0 dated 2019-04-25

Title: Create and Evaluate NONMEM Models in a Project Context
Description: Systematically creates and modifies NONMEM(R) control streams. Harvests NONMEM output, builds run logs, creates derivative data, generates diagnostics. NONMEM (ICON Development Solutions <http://www.iconplc.com/>) is software for nonlinear mixed effects modeling. See 'package?nonmemica'.
Author: Tim Bergsma
Maintainer: Tim Bergsma <bergsmat@gmail.com>

Diff between nonmemica versions 0.9.0 dated 2019-04-25 and 0.9.1 dated 2020-03-25

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Package ipaddress updated to version 0.2.0 with previous version 0.1.2 dated 2020-03-10

Title: Tidy IP Addresses
Description: Classes and functions for working with IP (Internet Protocol) addresses and networks, inspired by the Python 'ipaddress' module. Offers full support for both IPv4 and IPv6 (Internet Protocol versions 4 and 6) address spaces. It is specifically designed to work well with the 'tidyverse'.
Author: David Hall [aut, cre] (<https://orcid.org/0000-0002-2193-0480>)
Maintainer: David Hall <david.hall.physics@gmail.com>

Diff between ipaddress versions 0.1.2 dated 2020-03-10 and 0.2.0 dated 2020-03-25

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 ipaddress-0.2.0/ipaddress/src/IpNetworkVector.h                 |   74 -
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New package YRmisc with initial version 0.1.6
Package: YRmisc
Type: Package
Title: Y&R Miscellaneous R Functions
Version: 0.1.6
Author: Manuel Russon <RUSSONM@stjohns.edu>, Xuanhua (Peter) Yin <peteryin.sju@hotmail.com>
Maintainer: Xuanhua (Peter) Yin <peteryin.sju@hotmail.com>
Imports: ggplot2, grid, gridExtra
Description: Miscellaneous functions for data analysis, portfolio management, graphics, data manipulation, statistical investigation, including descriptive statistics, creating leading and lagging variables, portfolio return analysis, time series difference and percentage change calculation, stacking data for higher efficient analysis.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-03-25 16:01:47 UTC; peter
Repository: CRAN
Date/Publication: 2020-03-25 16:30:05 UTC

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New package wflo with initial version 1.2
Package: wflo
Title: Data Set and Helper Functions for Wind Farm Layout Optimization Problems
Version: 1.2
Authors@R: c(person("Carsten", "Croonenbroeck", email = "carsten.croonenbroeck@uni-rostock.de", role = c("aut", "cre")), person("David", "Hennecke", email = "david.hennecke@uni-rostock.de", role = "ctb"))
Description: Provides a convenient data set, a set of helper functions and a benchmark function for economically (profit) driven wind farm layout optimization. This enables researchers in the field of the NP-hard (non-deterministic polynomial-time hard) problem of wind farm layout optimization to focus on their optimization methodology contribution and also provides a realistic benchmark setting for comparability among contributions.
Depends: R (>= 3.1.0)
Suggests: MASS, nloptr, pso, rgenoud
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2020-03-24 15:29:34 UTC; ccroo
Author: Carsten Croonenbroeck [aut, cre], David Hennecke [ctb]
Maintainer: Carsten Croonenbroeck <carsten.croonenbroeck@uni-rostock.de>
Repository: CRAN
Date/Publication: 2020-03-25 16:10:02 UTC

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Package RiemStiefel updated to version 0.1.1 with previous version 0.1.0 dated 2020-03-15

Title: Inference, Learning, and Optimization on Stiefel Manifold
Description: Stiefel manifold is a set of orthonormal frames in Euclidean space. We provide algorithms for statistical inference, optimization, and learning over the Stiefel manifold. For general exposition to the statistics on the manifold, see the book by Chikuse (2003) <doi:10.1007/978-0-387-21540-2>.
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)
Maintainer: Kisung You <kyoustat@gmail.com>

Diff between RiemStiefel versions 0.1.0 dated 2020-03-15 and 0.1.1 dated 2020-03-25

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Package RGCxGC updated to version 1.1-1 with previous version 1.1.0 dated 2019-12-12

Title: Preprocessing and Multivariate Analysis of Bidimensional Gas Chromatography Data
Description: Toolbox for chemometrics analysis of bidimensional gas chromatography data. This package import data for common scientific data format (NetCDF) and fold it to 2D chromatogram. Then, it can perform preprocessing and multivariate analysis. In the preprocessing algorithms, baseline correction, smoothing, and peak alignment are available. While in multivariate analysis, multiway principal component analysis is incorporated.
Author: Cristian Quiroz-Moreno [aut, cre], Guilherme L. Alexandrino [aut], Noroska G.S. Mogollón [aut]
Maintainer: Cristian Quiroz-Moreno <cristianquirozd1997@gmail.com>

Diff between RGCxGC versions 1.1.0 dated 2019-12-12 and 1.1-1 dated 2020-03-25

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 R/batchTwoDCOW.R               |   12 +++---
 R/dephase_chrom.R              |    9 +++-
 R/import_mixOmics.R            |   22 ++++--------
 R/join_chromatograms.R         |    2 -
 R/m_prcomp.R                   |    2 -
 R/make_loadings.R              |    4 +-
 R/plot.R                       |    2 -
 R/print.R                      |    7 ++-
 R/read_chrom.R                 |    4 +-
 R/reference_chrom.R            |    2 -
 R/scores.R                     |    2 -
 R/wsmooth.R                    |   25 ++++++++++++-
 build/partial.rdb              |binary
 build/vignette.rds             |binary
 inst/CITATION                  |only
 inst/doc/Explanation.html      |   10 ++---
 man/GCxGC-class.Rd             |    6 +--
 man/MPCA-class.Rd              |    4 +-
 man/MTBLS579.Rd                |    6 ++-
 man/Myrothecium.Rd             |    6 ++-
 man/aligned_GCxGC-class.Rd     |    4 +-
 man/baseline_corr.Rd           |    4 +-
 man/batch_2DCOW.Rd             |   12 +++---
 man/dephase_chrom-methods.Rd   |    7 ++-
 man/import_mixOmics-methods.Rd |   17 +++------
 man/join_chromatograms.Rd      |    2 -
 man/m_prcomp.Rd                |    2 -
 man/make_loadings.Rd           |    2 -
 man/plot-methods.Rd            |    2 -
 man/plot_loading-methods.Rd    |    3 -
 man/print-methods.Rd           |    7 ++-
 man/read_chrom.Rd              |   13 +++++--
 man/scores-methods.Rd          |    2 -
 man/wsmooth.Rd                 |   16 +++++++-
 vignettes/RGCxGC.png           |only
 39 files changed, 187 insertions(+), 144 deletions(-)

More information about RGCxGC at CRAN
Permanent link

Package pcds updated to version 0.1.1 with previous version 0.1.0 dated 2020-02-29

Title: Proximity Catch Digraphs and Their Applications
Description: Contains the functions for generating patterns of segregation, association, CSR (complete spatial randomness) and Uniform data in one, two and three dimensional cases, for testing these patterns based on two invariants of various families of the proximity catch digraphs (PCDs) (see (Ceyhan (2005) ISBN:978-3-639-19063-2). The graph invariants used in testing spatial point data are the domination number (Ceyhan (2011) <doi: 10.1080/03610921003597211>) and arc density (Ceyhan et al. (2006) <doi:10.1016/j.csda.2005.03.002>; Ceyhan et al. (2007) <doi:10.1002/cjs.5550350106>) of for two-dimensional data for visualization of PCDs for one, two and three dimensional data. The PCD families considered are Arc-Slice PCDs, Proportional-Edge PCDs and Central Similarity PCDs.
Author: Elvan Ceyhan
Maintainer: Elvan Ceyhan <elvanceyhan@gmail.com>

Diff between pcds versions 0.1.0 dated 2020-02-29 and 0.1.1 dated 2020-03-25

 pcds-0.1.0/pcds/man/Pg2PE1D.asy.Rd         |only
 pcds-0.1.0/pcds/man/Pg2PEtri.Rd            |only
 pcds-0.1.1/pcds/DESCRIPTION                |   12 
 pcds-0.1.1/pcds/MD5                        |  558 ++--
 pcds-0.1.1/pcds/NAMESPACE                  |  544 ++--
 pcds-0.1.1/pcds/R/AuxRFuncs4PCDClasses.r   |   72 
 pcds-0.1.1/pcds/R/PCDFunctions.r           | 3312 +++++++++++++++--------------
 pcds-0.1.1/pcds/R/pcds.R                   |only
 pcds-0.1.1/pcds/build/partial.rdb          |binary
 pcds-0.1.1/pcds/man/ASarcdens.tri.Rd       |   10 
 pcds-0.1.1/pcds/man/ArcsASMT.Rd            |   17 
 pcds-0.1.1/pcds/man/ArcsAStri.Rd           |   17 
 pcds-0.1.1/pcds/man/ArcsCS1D.Rd            |   17 
 pcds-0.1.1/pcds/man/ArcsCSMI.Rd            |   17 
 pcds-0.1.1/pcds/man/ArcsCSMT.Rd            |   17 
 pcds-0.1.1/pcds/man/ArcsCSend1D.Rd         |   15 
 pcds-0.1.1/pcds/man/ArcsCSmid1D.Rd         |   17 
 pcds-0.1.1/pcds/man/ArcsCStri.Rd           |   17 
 pcds-0.1.1/pcds/man/ArcsPE1D.Rd            |   18 
 pcds-0.1.1/pcds/man/ArcsPEMI.Rd            |   18 
 pcds-0.1.1/pcds/man/ArcsPEMT.Rd            |   18 
 pcds-0.1.1/pcds/man/ArcsPEend1D.Rd         |   16 
 pcds-0.1.1/pcds/man/ArcsPEmid1D.Rd         |   18 
 pcds-0.1.1/pcds/man/ArcsPEtri.Rd           |   18 
 pcds-0.1.1/pcds/man/CSarcdens.tri.Rd       |   16 
 pcds-0.1.1/pcds/man/Dist.Rd                |    2 
 pcds-0.1.1/pcds/man/Gam1ASbastri.Rd        |   19 
 pcds-0.1.1/pcds/man/Gam1AStri.Rd           |   14 
 pcds-0.1.1/pcds/man/Gam1CS.Te.onesixth.Rd  |   10 
 pcds-0.1.1/pcds/man/Gam1CS1D.Rd            |   15 
 pcds-0.1.1/pcds/man/Gam1CSTe.Rd            |    8 
 pcds-0.1.1/pcds/man/Gam1CSTet1.Rd          |   14 
 pcds-0.1.1/pcds/man/Gam1PE1D.Rd            |   16 
 pcds-0.1.1/pcds/man/Gam1PEbastri.Rd        |   15 
 pcds-0.1.1/pcds/man/Gam1PEstdTetra.Rd      |   17 
 pcds-0.1.1/pcds/man/Gam1PEtetra.Rd         |   19 
 pcds-0.1.1/pcds/man/Gam1PEtri.Rd           |   15 
 pcds-0.1.1/pcds/man/Gam2ASbastri.Rd        |   17 
 pcds-0.1.1/pcds/man/Gam2AStri.Rd           |   15 
 pcds-0.1.1/pcds/man/Gam2CS.Te.onesixth.Rd  |   10 
 pcds-0.1.1/pcds/man/Gam2PEbastri.Rd        |   18 
 pcds-0.1.1/pcds/man/Gam2PEstdTetra.Rd      |   16 
 pcds-0.1.1/pcds/man/Gam2PEtetra.Rd         |   20 
 pcds-0.1.1/pcds/man/Gam2PEtri.Rd           |   16 
 pcds-0.1.1/pcds/man/Gam3PEstdTetra.Rd      |   19 
 pcds-0.1.1/pcds/man/Gam3PEtetra.Rd         |   23 
 pcds-0.1.1/pcds/man/IncMatASMT.Rd          |    8 
 pcds-0.1.1/pcds/man/IncMatAStri.Rd         |    8 
 pcds-0.1.1/pcds/man/IncMatCS1D.Rd          |    6 
 pcds-0.1.1/pcds/man/IncMatCSMT.Rd          |    8 
 pcds-0.1.1/pcds/man/IncMatCSTe.Rd          |    8 
 pcds-0.1.1/pcds/man/IncMatCStri.Rd         |    8 
 pcds-0.1.1/pcds/man/IncMatPE1D.Rd          |    7 
 pcds-0.1.1/pcds/man/IncMatPEMT.Rd          |    9 
 pcds-0.1.1/pcds/man/IncMatPETe.Rd          |    7 
 pcds-0.1.1/pcds/man/IncMatPEtetra.Rd       |   11 
 pcds-0.1.1/pcds/man/IncMatPEtri.Rd         |    9 
 pcds-0.1.1/pcds/man/IndASdomUBtri.Rd       |   10 
 pcds-0.1.1/pcds/man/IndCS.Te.onesixth.Rd   |    2 
 pcds-0.1.1/pcds/man/IndCSTe.Rd             |    6 
 pcds-0.1.1/pcds/man/IndCSTe.domset.Rd      |    8 
 pcds-0.1.1/pcds/man/IndCSTeSet.Rd          |    4 
 pcds-0.1.1/pcds/man/IndCSTet1.Rd           |    2 
 pcds-0.1.1/pcds/man/IndCSdomUBTe.Rd        |    8 
 pcds-0.1.1/pcds/man/IndCSdomUBtri.Rd       |   11 
 pcds-0.1.1/pcds/man/IndNASbastri.Rd        |    8 
 pcds-0.1.1/pcds/man/IndNAStri.Rd           |    8 
 pcds-0.1.1/pcds/man/IndNAStri.domset.Rd    |    2 
 pcds-0.1.1/pcds/man/IndNAStriSet.Rd        |    8 
 pcds-0.1.1/pcds/man/IndNCSend1D.Rd         |   10 
 pcds-0.1.1/pcds/man/IndNCSint.Rd           |   10 
 pcds-0.1.1/pcds/man/IndNCSmid1D.Rd         |   11 
 pcds-0.1.1/pcds/man/IndNCStri.Rd           |    9 
 pcds-0.1.1/pcds/man/IndNCStri.alt.Rd       |   14 
 pcds-0.1.1/pcds/man/IndNCStri.domset.Rd    |   10 
 pcds-0.1.1/pcds/man/IndNCStriSet.Rd        |    6 
 pcds-0.1.1/pcds/man/IndNPETe.Rd            |    7 
 pcds-0.1.1/pcds/man/IndNPETe.domset.Rd     |    8 
 pcds-0.1.1/pcds/man/IndNPETeSet.Rd         |    4 
 pcds-0.1.1/pcds/man/IndNPEbastri.Rd        |    6 
 pcds-0.1.1/pcds/man/IndNPEend1D.Rd         |    9 
 pcds-0.1.1/pcds/man/IndNPEint.Rd           |   11 
 pcds-0.1.1/pcds/man/IndNPEmid1D.Rd         |   10 
 pcds-0.1.1/pcds/man/IndNPEstdtetra.Rd      |    5 
 pcds-0.1.1/pcds/man/IndNPEtetra.Rd         |   10 
 pcds-0.1.1/pcds/man/IndNPEtri.Rd           |   10 
 pcds-0.1.1/pcds/man/IndNPEtri.domset.Rd    |   10 
 pcds-0.1.1/pcds/man/IndNPEtriSet.Rd        |    6 
 pcds-0.1.1/pcds/man/IndUBdom.Rd            |    6 
 pcds-0.1.1/pcds/man/Kfr2vTbVRCC.Rd         |   25 
 pcds-0.1.1/pcds/man/Kfr2vVRCC.Rd           |   15 
 pcds-0.1.1/pcds/man/Line.Rd                |   13 
 pcds-0.1.1/pcds/man/Line3D.Rd              |   18 
 pcds-0.1.1/pcds/man/NASbastri.Rd           |   13 
 pcds-0.1.1/pcds/man/NAStri.Rd              |   16 
 pcds-0.1.1/pcds/man/NCSint.Rd              |    8 
 pcds-0.1.1/pcds/man/NCStri.Rd              |   11 
 pcds-0.1.1/pcds/man/NPEbastri.Rd           |   12 
 pcds-0.1.1/pcds/man/NPEint.Rd              |    9 
 pcds-0.1.1/pcds/man/NPEstdtetra.Rd         |    8 
 pcds-0.1.1/pcds/man/NPEtetra.Rd            |   11 
 pcds-0.1.1/pcds/man/NPEtri.Rd              |   12 
 pcds-0.1.1/pcds/man/NumArcsASMT.Rd         |    8 
 pcds-0.1.1/pcds/man/NumArcsAStri.Rd        |    8 
 pcds-0.1.1/pcds/man/NumArcsCSMT.Rd         |   10 
 pcds-0.1.1/pcds/man/NumArcsCSTe.Rd         |    8 
 pcds-0.1.1/pcds/man/NumArcsCSend1D.Rd      |    6 
 pcds-0.1.1/pcds/man/NumArcsCSint.Rd        |    8 
 pcds-0.1.1/pcds/man/NumArcsCSmid1D.Rd      |    8 
 pcds-0.1.1/pcds/man/NumArcsCStri.Rd        |    8 
 pcds-0.1.1/pcds/man/NumArcsPEMT.Rd         |   11 
 pcds-0.1.1/pcds/man/NumArcsPETe.Rd         |    7 
 pcds-0.1.1/pcds/man/NumArcsPEend1D.Rd      |    7 
 pcds-0.1.1/pcds/man/NumArcsPEint.Rd        |    9 
 pcds-0.1.1/pcds/man/NumArcsPEmid1D.Rd      |    9 
 pcds-0.1.1/pcds/man/NumArcsPEtri.Rd        |    9 
 pcds-0.1.1/pcds/man/NumDelTri.Rd           |    5 
 pcds-0.1.1/pcds/man/PEarcdens.tri.Rd       |   16 
 pcds-0.1.1/pcds/man/PEdom.tetra.Rd         |    9 
 pcds-0.1.1/pcds/man/PEdom1D.Rd             |    3 
 pcds-0.1.1/pcds/man/PEdomMT.Rd             |    9 
 pcds-0.1.1/pcds/man/PEdomMTnd.Rd           |    7 
 pcds-0.1.1/pcds/man/PEdomtri.Rd            |    9 
 pcds-0.1.1/pcds/man/PG2PE1D.asy.Rd         |only
 pcds-0.1.1/pcds/man/PG2PEtri.Rd            |only
 pcds-0.1.1/pcds/man/Plane.Rd               |    9 
 pcds-0.1.1/pcds/man/TSArcDensCS1D.Rd       |   16 
 pcds-0.1.1/pcds/man/TSArcDensCSMT.Rd       |   16 
 pcds-0.1.1/pcds/man/TSArcDensPE1D.Rd       |   18 
 pcds-0.1.1/pcds/man/TSArcDensPEMT.Rd       |   17 
 pcds-0.1.1/pcds/man/TSDomPEBin.Rd          |   20 
 pcds-0.1.1/pcds/man/TSDomPEBin1D.Rd        |   21 
 pcds-0.1.1/pcds/man/TSDomPENor.Rd          |   20 
 pcds-0.1.1/pcds/man/XinCHY.Rd              |    4 
 pcds-0.1.1/pcds/man/angle.str2end.Rd       |   16 
 pcds-0.1.1/pcds/man/area.polygon.Rd        |    4 
 pcds-0.1.1/pcds/man/as.bastri.Rd           |    4 
 pcds-0.1.1/pcds/man/cent.nondeg.Rd         |    4 
 pcds-0.1.1/pcds/man/centMc.Rd              |    6 
 pcds-0.1.1/pcds/man/centersMc.Rd           |    6 
 pcds-0.1.1/pcds/man/circ.cent.bastri.Rd    |    2 
 pcds-0.1.1/pcds/man/circ.cent.tetra.Rd     |    2 
 pcds-0.1.1/pcds/man/circ.cent.tri.Rd       |    2 
 pcds-0.1.1/pcds/man/cl2CC.TbVR.Rd          |   21 
 pcds-0.1.1/pcds/man/cl2CC.VR.Rd            |   13 
 pcds-0.1.1/pcds/man/cl2Mc.int.Rd           |   15 
 pcds-0.1.1/pcds/man/cl2eTbVRcent.Rd        |   17 
 pcds-0.1.1/pcds/man/cl2eVRCC.Rd            |   13 
 pcds-0.1.1/pcds/man/cl2eVRCM.Rd            |   13 
 pcds-0.1.1/pcds/man/cl2eVRcent.Rd          |   15 
 pcds-0.1.1/pcds/man/cl2eVRcent.alt.Rd      |   17 
 pcds-0.1.1/pcds/man/cl2edgesTe.Rd          |   11 
 pcds-0.1.1/pcds/man/cl2fVRth.Rd            |   13 
 pcds-0.1.1/pcds/man/cp2e.bastri.Rd         |    4 
 pcds-0.1.1/pcds/man/cp2e.tri.Rd            |    4 
 pcds-0.1.1/pcds/man/cp2edges.nd.Rd         |    6 
 pcds-0.1.1/pcds/man/dist.pt2set.Rd         |    6 
 pcds-0.1.1/pcds/man/dom.exact.Rd           |    4 
 pcds-0.1.1/pcds/man/dom.greedy.Rd          |    4 
 pcds-0.1.1/pcds/man/dp2l.Rd                |    2 
 pcds-0.1.1/pcds/man/dp2pl.Rd               |    5 
 pcds-0.1.1/pcds/man/fr2eTeER.Rd            |   16 
 pcds-0.1.1/pcds/man/fr2vTbVRCC.Rd          |   18 
 pcds-0.1.1/pcds/man/fr2vVRCC.Rd            |   13 
 pcds-0.1.1/pcds/man/funsAB2CMTe.Rd         |   15 
 pcds-0.1.1/pcds/man/funsAB2MTe.Rd          |   15 
 pcds-0.1.1/pcds/man/funsCSEdgeRegs.Rd      |   18 
 pcds-0.1.1/pcds/man/funsCSGamTe.Rd         |   38 
 pcds-0.1.1/pcds/man/funsCSt1EdgeRegs.Rd    |   12 
 pcds-0.1.1/pcds/man/funsCartBary.Rd        |   10 
 pcds-0.1.1/pcds/man/funsIndDelTri.Rd       |   19 
 pcds-0.1.1/pcds/man/funsMuVarCS1D.Rd       |   10 
 pcds-0.1.1/pcds/man/funsMuVarCS2D.Rd       |    8 
 pcds-0.1.1/pcds/man/funsMuVarCSend1D.Rd    |   11 
 pcds-0.1.1/pcds/man/funsMuVarPE1D.Rd       |   19 
 pcds-0.1.1/pcds/man/funsMuVarPE2D.Rd       |    9 
 pcds-0.1.1/pcds/man/funsMuVarPEend1D.Rd    |    9 
 pcds-0.1.1/pcds/man/funsPG2PE1D.Rd         |   88 
 pcds-0.1.1/pcds/man/funsRankOrderTe.Rd     |   21 
 pcds-0.1.1/pcds/man/funsTbMid2CC.Rd        |    8 
 pcds-0.1.1/pcds/man/in.circle.Rd           |    6 
 pcds-0.1.1/pcds/man/in.tetrahedron.Rd      |   18 
 pcds-0.1.1/pcds/man/in.triangle.Rd         |    2 
 pcds-0.1.1/pcds/man/inTriAll.Rd            |    4 
 pcds-0.1.1/pcds/man/int.2lines.Rd          |    4 
 pcds-0.1.1/pcds/man/int.circ.line.Rd       |    6 
 pcds-0.1.1/pcds/man/int.line.plane.Rd      |    4 
 pcds-0.1.1/pcds/man/is.in.data.Rd          |    6 
 pcds-0.1.1/pcds/man/is.point.Rd            |    2 
 pcds-0.1.1/pcds/man/isStdEqTri.Rd          |    2 
 pcds-0.1.1/pcds/man/paraline.Rd            |    7 
 pcds-0.1.1/pcds/man/paraline3D.Rd          |   12 
 pcds-0.1.1/pcds/man/paraplane.Rd           |   11 
 pcds-0.1.1/pcds/man/pcds.Rd                |only
 pcds-0.1.1/pcds/man/perp.ln2pl.Rd          |   13 
 pcds-0.1.1/pcds/man/perpline.Rd            |    7 
 pcds-0.1.1/pcds/man/plot.Extrema.Rd        |    6 
 pcds-0.1.1/pcds/man/plot.Lines.Rd          |    6 
 pcds-0.1.1/pcds/man/plot.Lines3D.Rd        |    4 
 pcds-0.1.1/pcds/man/plot.PCDs.Rd           |    6 
 pcds-0.1.1/pcds/man/plot.Patterns.Rd       |    6 
 pcds-0.1.1/pcds/man/plot.Planes.Rd         |    4 
 pcds-0.1.1/pcds/man/plot.TriLines.Rd       |    6 
 pcds-0.1.1/pcds/man/plot.Uniform.Rd        |    6 
 pcds-0.1.1/pcds/man/plotASarcsMT.Rd        |   21 
 pcds-0.1.1/pcds/man/plotASarcsTri.Rd       |   21 
 pcds-0.1.1/pcds/man/plotASregsMT.Rd        |   15 
 pcds-0.1.1/pcds/man/plotASregsTri.Rd       |   15 
 pcds-0.1.1/pcds/man/plotCSarcs1D.Rd        |   21 
 pcds-0.1.1/pcds/man/plotCSarcsMT.Rd        |   16 
 pcds-0.1.1/pcds/man/plotCSarcsTri.Rd       |   21 
 pcds-0.1.1/pcds/man/plotCSregsInt.Rd       |   20 
 pcds-0.1.1/pcds/man/plotCSregsMI.Rd        |   21 
 pcds-0.1.1/pcds/man/plotCSregsMT.Rd        |   21 
 pcds-0.1.1/pcds/man/plotCSregsTri.Rd       |   20 
 pcds-0.1.1/pcds/man/plotDeltri.Rd          |   10 
 pcds-0.1.1/pcds/man/plotIntervals.Rd       |    7 
 pcds-0.1.1/pcds/man/plotPEarcs1D.Rd        |   22 
 pcds-0.1.1/pcds/man/plotPEarcsMT.Rd        |   21 
 pcds-0.1.1/pcds/man/plotPEarcsTri.Rd       |   22 
 pcds-0.1.1/pcds/man/plotPEregsInt.Rd       |   19 
 pcds-0.1.1/pcds/man/plotPEregsMI.Rd        |   22 
 pcds-0.1.1/pcds/man/plotPEregsMT.Rd        |   21 
 pcds-0.1.1/pcds/man/plotPEregsStdTH.Rd     |   13 
 pcds-0.1.1/pcds/man/plotPEregsTH.Rd        |   17 
 pcds-0.1.1/pcds/man/plotPEregsTri.Rd       |   21 
 pcds-0.1.1/pcds/man/print.TriLines.Rd      |    2 
 pcds-0.1.1/pcds/man/radii.Rd               |    2 
 pcds-0.1.1/pcds/man/radius.Rd              |    2 
 pcds-0.1.1/pcds/man/rasc.disc.Rd           |   16 
 pcds-0.1.1/pcds/man/rasc.matern.Rd         |   10 
 pcds-0.1.1/pcds/man/rasc.tri.Rd            |    7 
 pcds-0.1.1/pcds/man/rascIITe.Rd            |    9 
 pcds-0.1.1/pcds/man/rascMT.Rd              |   11 
 pcds-0.1.1/pcds/man/rascTe.Rd              |    9 
 pcds-0.1.1/pcds/man/re.bastri.cent.Rd      |    7 
 pcds-0.1.1/pcds/man/re.bastriCM.Rd         |    5 
 pcds-0.1.1/pcds/man/re.tri.cent.Rd         |    6 
 pcds-0.1.1/pcds/man/re.triCM.Rd            |    4 
 pcds-0.1.1/pcds/man/reTeCM.Rd              |    2 
 pcds-0.1.1/pcds/man/redge.triCM.Rd         |    6 
 pcds-0.1.1/pcds/man/redges.tri.cent.Rd     |    6 
 pcds-0.1.1/pcds/man/redges.triCM.Rd        |    4 
 pcds-0.1.1/pcds/man/rel.six.Te.Rd          |    6 
 pcds-0.1.1/pcds/man/rseg.disc.Rd           |   13 
 pcds-0.1.1/pcds/man/rseg.tri.Rd            |    7 
 pcds-0.1.1/pcds/man/rsegIITe.Rd            |    9 
 pcds-0.1.1/pcds/man/rsegMT.Rd              |   11 
 pcds-0.1.1/pcds/man/rsegTe.Rd              |    9 
 pcds-0.1.1/pcds/man/runif.bastri.Rd        |   12 
 pcds-0.1.1/pcds/man/runif.stdtetra.Rd      |    7 
 pcds-0.1.1/pcds/man/runif.tetra.Rd         |   11 
 pcds-0.1.1/pcds/man/runif.tri.Rd           |    9 
 pcds-0.1.1/pcds/man/runifMT.Rd             |   12 
 pcds-0.1.1/pcds/man/runifTe.Rd             |    7 
 pcds-0.1.1/pcds/man/runifTe.onesixth.Rd    |   13 
 pcds-0.1.1/pcds/man/rv.bastri.cent.Rd      |    6 
 pcds-0.1.1/pcds/man/rv.bastriCC.Rd         |    5 
 pcds-0.1.1/pcds/man/rv.bastriCM.Rd         |    5 
 pcds-0.1.1/pcds/man/rv.end.int.Rd          |    4 
 pcds-0.1.1/pcds/man/rv.mid.int.Rd          |    4 
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New package leastcostpath with initial version 1.2.1
Package: leastcostpath
Title: Modelling Pathways and Movement Potential Within a Landscape
Version: 1.2.1
Date: 2020-03-18
Authors@R: person("Joseph", "Lewis", email = "josephlewis1992@gmail.com", role = c("aut", "cre"))
Maintainer: Joseph Lewis <josephlewis1992@gmail.com>
URL: josephlewis.github.io
Description: Provides functionality to calculate cost surfaces based on slope (e.g. Herzog, 2010; Llobera and Sluckin, 2007 <doi:10.1016/j.jtbi.2007.07.020>; París Roche, 2002; Tobler, 1993), traversing slope (Bell and Lock, 2000), and landscape features (Llobera, 2000) to be used when modelling pathways and movement potential within a landscape (e.g. Llobera, 2015; Verhagen, 2013; White and Barber, 2012 <doi:10.1016/j.jas.2012.04.017>).
Depends: R (>= 3.4.0)
Imports: gdistance (>= 1.2-2), raster (>= 2.6-7), rgdal (>= 1.3-3), rgeos (>= 0.3-28), sp (>= 1.3-1), parallel (>= 3.4-1), pbapply (>= 1.4-2), methods, stats
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-03-23 19:10:48 UTC; Joe
Author: Joseph Lewis [aut, cre]
Repository: CRAN
Date/Publication: 2020-03-25 16:30:02 UTC

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Package fuzzyforest updated to version 1.0.8 with previous version 1.0.7 dated 2020-02-05

Title: Fuzzy Forests
Description: Fuzzy forests, a new algorithm based on random forests, is designed to reduce the bias seen in random forest feature selection caused by the presence of correlated features. Fuzzy forests uses recursive feature elimination random forests to select features from separate blocks of correlated features where the correlation within each block of features is high and the correlation between blocks of features is low. One final random forest is fit using the surviving features. This package fits random forests using the 'randomForest' package and allows for easy use of 'WGCNA' to split features into distinct blocks. See D. Conn, Ngun, T., C. Ramirez, and G. Li (2019) <doi:10.18637/jss.v091.i09> for further details.
Author: Daniel Conn [aut, cre], Tuck Ngun [aut], Christina M. Ramirez [aut]
Maintainer: Daniel Conn <djconn17@gmail.com>

Diff between fuzzyforest versions 1.0.7 dated 2020-02-05 and 1.0.8 dated 2020-03-25

 DESCRIPTION           |    6 +++---
 MD5                   |   14 +++++++-------
 R/ff.R                |    1 -
 R/tuning_parameters.R |    5 -----
 R/wff.R               |   32 ++------------------------------
 build/partial.rdb     |binary
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 8 files changed, 14 insertions(+), 74 deletions(-)

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New package Ghost with initial version 0.1.0
Package: Ghost
Type: Package
Title: Missing Data Segments Imputation in Multivariate Streams
Version: 0.1.0
Author: Siyavash Shabani, Reza Rawassizadeh
Maintainer: Siyavash Shabani <s.shabani.aut@gmail.com>
Description: Helper functions provide an accurate imputation algorithm for reconstructing the missing segment in a multi-variate data streams. Inspired by single-shot learning, it reconstructs the missing segment by identifying the first similar segment in the stream. Nevertheless, there should be one column of data available, i.e. a constraint column. The values of columns can be characters (A, B, C, etc.). The result of the imputed dataset will be returned a .csv file. For more details see Reza Rawassizadeh (2019) <doi:10.1109/TKDE.2019.2914653>.
URL: https://www.researchgate.net/publication/332779980_Ghost_Imputation_Accurately_Reconstructing_Missing_Data_of_the_Off_Period
Depends: R (>= 2.10)
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2020-03-23 22:25:06 UTC; lorman
Imports: R6
RoxygenNote: 7.0.1
Repository: CRAN
Date/Publication: 2020-03-25 16:50:05 UTC

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Package CGE updated to version 0.3.1 with previous version 0.3.0 dated 2020-02-01

Title: Computing General Equilibrium
Description: Developing general equilibrium models, computing general equilibrium and simulating economic dynamics with structural dynamic models in LI (2019, ISBN: 9787521804225) "General Equilibrium and Structural Dynamics: Perspectives of New Structural Economics. Beijing: Economic Science Press".
Author: LI Wu <liwu@staff.shu.edu.cn>
Maintainer: LI Wu <liwu@staff.shu.edu.cn>

Diff between CGE versions 0.3.0 dated 2020-02-01 and 0.3.1 dated 2020-03-25

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Package AlphaPart updated to version 0.8.1 with previous version 0.8.0 dated 2020-03-17

Title: Partition/Decomposition of Breeding Values by Paths of Information
Description: A software that implements a method for partitioning genetic trends to quantify the sources of genetic gain in breeding programmes. The partitioning method is described in Garcia-Cortes et al. (2008) <doi:10.1017/S175173110800205X>. The package includes the main function AlphaPart for partitioning breeding values and auxiliary functions for manipulating data and summarizing, visualizing, and saving results.
Author: Gregor Gorjanc, Jana Obsteter
Maintainer: Jana Obšteter <jana.obsteter@kis.si>

Diff between AlphaPart versions 0.8.0 dated 2020-03-17 and 0.8.1 dated 2020-03-25

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New package aPCoA with initial version 1.0
Package: aPCoA
Type: Package
Title: Covariate Adjusted PCoA Plot
Version: 1.0
Date: 2020-03-23
Author: Yushu Shi
Maintainer: Yushu Shi <shiyushu2006@gmail.com>
Description: In fields such as ecology, microbiology, and genomics, non-Euclidean distances are widely applied to describe pairwise dissimilarity between samples. Given these pairwise distances, principal coordinates analysis (PCoA) is commonly used to construct a visualization of the data. However, confounding covariates can make patterns related to the scientific question of interest difficult to observe. We provide 'aPCoA' as an easy-to-use tool to improve data visualization in this context, enabling enhanced presentation of the effects of interest. Details are described in Yushu Shi, Liangliang Zhang, Kim-Anh Do, Christine Peterson and Robert Jenq (2020) <arXiv:2003.09544>.
License: GPL (>= 2)
Imports: vegan, randomcoloR, mvabund, ape, car, cluster
NeedsCompilation: no
Repository: CRAN
Packaged: 2020-03-24 02:46:28 UTC; yshi7
Date/Publication: 2020-03-25 16:50:02 UTC

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New package spathial with initial version 0.1.1
Package: spathial
Type: Package
Title: Evolutionary Analysis
Version: 0.1.1
Authors@R: c(person("Erika", "Gardini", email = "erika.gardini4@unibo.it", role = c("aut", "cre")), person("Federico M.", "Giorgi", email = "federico.giorgi@unibo.it", role = c("aut")), person("Sergio", "Decherchi", email = "sergio.decherchi@iit.it", role = c("aut")))
Author: Erika Gardini [aut, cre], Federico M. Giorgi [aut], Sergio Decherchi [aut]
Maintainer: Erika Gardini <erika.gardini4@unibo.it>
Description: A generic tool for manifold analysis. It allows to infer a relevant transition or evolutionary path which can highlights the features involved in a specific process. 'spathial' can be useful in all the scenarios where the temporal (or pseudo-temporal) evolution is the main problem (e.g. tumor progression). The algorithm for finding the principal path is described in: Ferrarotti et al., (2019) <doi:10.1109/TNNLS.2018.2884792>."
License: GPL-3
Encoding: UTF-8
LazyData: TRUE
RoxygenNote: 7.0.2
Depends: R (>= 3.5)
NeedsCompilation: no
Imports: pracma, igraph, matrixStats, MASS, Rtsne, class, utils, knitr, rmarkdown
VignetteBuilder: utils, knitr, rmarkdown
Packaged: 2020-03-23 11:28:37 UTC; erikagardini
Repository: CRAN
Date/Publication: 2020-03-25 15:30:02 UTC

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New package RiemGrassmann with initial version 0.1.0
Package: RiemGrassmann
Type: Package
Title: Inference, Learning, and Optimization on Grassmann Manifold
Version: 0.1.0
Authors@R: c(person("Kisung", "You", role = c("aut", "cre"), email = "kyoustat@gmail.com",comment=c(ORCID="0000-0002-8584-459X")))
Description: Grassmann manifold is a set of k-planes or linear subspaces in Euclidean space. We provide algorithms for statistical inference, optimization, and learning over the Grassmann manifold. For general exposition to the statistics on the manifold, see the book by Chikuse (2003) <doi:10.1007/978-0-387-21540-2>.
Encoding: UTF-8
License: GPL (>= 3)
Imports: Rcpp, RiemBase, RiemBaseExt, utils, stats
LinkingTo: Rcpp, RcppArmadillo, RiemBase
RoxygenNote: 7.0.2
NeedsCompilation: yes
Packaged: 2020-03-25 15:26:03 UTC; kisung
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)
Maintainer: Kisung You <kyoustat@gmail.com>
Repository: CRAN
Date/Publication: 2020-03-25 15:50:06 UTC

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New package rainette with initial version 0.1
Package: rainette
Type: Package
Title: The Reinert Method for Textual Data Clustering
Version: 0.1
Date: 2020-03-16
Authors@R: c(person("Julien", "Barnier", email="julien.barnier@cnrs.fr", role=c("aut","cre")), person("Florian", "Privé", email="florian.prive.21@gmail.com", role="ctb"))
Maintainer: Julien Barnier <julien.barnier@cnrs.fr>
Description: An R implementation of the Reinert text clustering method. For more details about the algorithm see the included vignettes or Reinert (1990) <doi:10.1177/075910639002600103>.
License: GPL (>= 3)
VignetteBuilder: knitr
URL: https://juba.github.io/rainette/
BugReports: https://github.com/juba/rainette/issues
Encoding: UTF-8
Imports: dplyr (>= 0.8.3), tidyr, purrr, ggplot2, stringr, quanteda (>= 1.5), RSpectra, dendextend, ggwordcloud, gridExtra, rlang, RColorBrewer, shiny, miniUI, formatR, highr, future, future.apply, progressr, Rcpp (>= 1.0.3)
Suggests: testthat, knitr, rmarkdown, covr, vdiffr, tm, FNN, quanteda.textmodels
RoxygenNote: 7.1.0
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2020-03-23 09:38:40 UTC; julien
Author: Julien Barnier [aut, cre], Florian Privé [ctb]
Repository: CRAN
Date/Publication: 2020-03-25 15:30:05 UTC

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Package PHInfiniteEstimates updated to version 1.2 with previous version 1.1 dated 2020-03-09

Title: Tools for Inference in the Presence of a Monotone Likelihood
Description: Proportional hazards estimation in the presence of a partially monotone likelihood has difficulties, in that finite estimators do not exist. These difficulties are related to those arising from logistic and multinomial regression. References for methods are given in the separate function documents.
Author: John E. Kolassa and Juan Zhang
Maintainer: John E. Kolassa <kolassa@stat.rutgers.edu>

Diff between PHInfiniteEstimates versions 1.1 dated 2020-03-09 and 1.2 dated 2020-03-25

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 10 files changed, 31 insertions(+), 24 deletions(-)

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New package neptune with initial version 0.1.0
Package: neptune
Type: Package
Title: Interface to 'Neptune' Experiment Tracking and Management Tool
Version: 0.1.0
Authors@R: c( person("Mateusz", "Dominiak", role = c("aut")), person("Jakub", "Czakon", email = "jakub.czakon@neptune.ai", role = c("aut","cre")) )
Maintainer: Jakub Czakon <jakub.czakon@neptune.ai>
Description: Interface to 'Neptune', experiment tracking tool that helps you organize your machine learning experiments. You can log your hyperparameter, metrics, model binaries and performance charts, organize them with tags and names and share everything easily in the app. For more information see <https://neptune.ai/>.
License: Apache License 2.0
URL: https://github.com/neptune-ai/neptune-r
BugReports: https://github.com/neptune-ai/neptune-r/issues
Encoding: UTF-8
LazyData: true
SystemRequirements: Python (>= 3.0.0), Neptune (https://neptune.ai/)
Imports: reticulate
NeedsCompilation: no
Packaged: 2020-03-25 13:08:56 UTC; kuba
Author: Mateusz Dominiak [aut], Jakub Czakon [aut, cre]
Repository: CRAN
Date/Publication: 2020-03-25 15:10:02 UTC

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New package milorGWAS with initial version 0.3
Package: milorGWAS
Type: Package
Title: Mixed Logistic Regression for Genome-Wide Analysis Studies (GWAS)
Version: 0.3
Date: 2020-03-13
Encoding: UTF-8
Author: Hervé Perdry and Jacqueline Milet
Maintainer: Hervé Perdry <herve.perdry@u-psud.fr>
Description: Fast approximate methods for mixed logistic regression in genome-wide analysis studies (GWAS). Milet et al 2020 <doi:10.1101/2020.01.17.910109>.
License: GPL-3
Imports: Rcpp (>= 1.0.2)
Depends: gaston (>= 1.5.6)
LinkingTo: Rcpp, RcppEigen, gaston
Suggests: knitr, rmarkdown, png
VignetteBuilder: knitr
NeedsCompilation: yes
RoxygenNote: 7.0.2
Packaged: 2020-03-23 10:07:14 UTC; rv
Repository: CRAN
Date/Publication: 2020-03-25 15:30:08 UTC

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New package L2DensityGoFtest with initial version 0.1.0
Encoding: UTF-8
Package: L2DensityGoFtest
Type: Package
Title: Density Goodness-of-Fit Test
Version: 0.1.0
Authors@R: c(person("Dimitrios", "Bagkavos", role = c("aut", "cre"), email = "dimitrios.bagkavos@gmail.com") )
Author: Dimitrios Bagkavos [aut, cre]
Maintainer: Dimitrios Bagkavos <dimitrios.bagkavos@gmail.com>
Description: Provides functions for the implementation of a density goodness-of-fit test, based on piecewise approximation of the L2 distance.
Imports: fGarch, kedd, nor1mix
License: GPL (>= 2)
LazyData: true
NeedsCompilation: no
Packaged: 2020-03-22 22:15:17 UTC; Dimitris
Repository: CRAN
Date/Publication: 2020-03-25 15:30:16 UTC

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New package IsoCheck with initial version 0.1.0
Package: IsoCheck
Title: Isomorphism Check for Multi-Stage Factorial Designs with Randomization Restrictions
Version: 0.1.0
Date: 2020-03-20
Author: Neil Spencer [aut, cre], Pritam Ranjan [aut,cre], Franklin Mendivil [ctb]
Maintainer: Pritam Ranjan <pritam.ranjan@gmail.com>
Description: Contains functions to check the isomorphism of multi-stage factorial designs with randomisation restrictions based on balanced spreads and balanced covering stars of PG(n-1,2) as described in Spencer, Ranjan and Mendivil (2019) <doi:10.1007/s42519-019-0064-5>.
License: GPL-2
Imports: gtools, dplyr, plyr
NeedsCompilation: no
Packaged: 2020-03-23 12:41:47 UTC; pritam-2
Repository: CRAN
Date/Publication: 2020-03-25 15:40:02 UTC

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Package incidence updated to version 1.7.1 with previous version 1.7.0 dated 2019-03-14

Title: Compute, Handle, Plot and Model Incidence of Dated Events
Description: Provides functions and classes to compute, handle and visualise incidence from dated events for a defined time interval. Dates can be provided in various standard formats. The class 'incidence' is used to store computed incidence and can be easily manipulated, subsetted, and plotted. In addition, log-linear models can be fitted to 'incidence' objects using 'fit'. This package is part of the RECON (<http://www.repidemicsconsortium.org/>) toolkit for outbreak analysis.
Author: Thibaut Jombart [aut], Zhian N. Kamvar [aut, cre] (<https://orcid.org/0000-0003-1458-7108>), Rich FitzJohn [aut], Jun Cai [ctb] (<https://orcid.org/0000-0001-9495-1226>), Sangeeta Bhatia [ctb], Jakob Schumacher [ctb], Juliet R.C. Pulliam [ctb] (<https://orcid.org/0000-0003-3314-8223>)
Maintainer: Zhian N. Kamvar <zkamvar@gmail.com>

Diff between incidence versions 1.7.0 dated 2019-03-14 and 1.7.1 dated 2020-03-25

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 man/plot.incidence.Rd             |   23 
 man/subset.Rd                     |    3 
 tests/testthat/test-conversions.R |    6 
 26 files changed, 2041 insertions(+), 1867 deletions(-)

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New package fsMTS with initial version 0.1.4
Package: fsMTS
Type: Package
Title: Feature Selection for Multivariate Time Series
Version: 0.1.4
Authors@R: person("Dmitry", "Pavlyuk", email = "Dmitry.Pavlyuk@tsi.lv",comment = c(ORCID = "0000-0003-3710-9678"), role = c("aut", "cre"))
Description: Implements feature selection routines for multivariate time series (MTS). The list of implemented algorithms includes: own lags (independent MTS components), distance-based (using external structure, e.g. Pfeifer and Deutsch (1980) <doi:10.2307/1268381>), cross-correlation (see Schelter et al. (2006, ISBN:9783527406234)), graphical LASSO (see Haworth and Cheng (2014) <https://www.gla.ac.uk/media/Media_401739_smxx.pdf>), random forest (see Pavlyuk (2020) "Random Forest Variable Selection for Sparse Vector Autoregressive Models" in Contributions to Statistics, in production), least angle regression (see Gelper and Croux (2008) <https://lirias.kuleuven.be/retrieve/16024>), mutual information (see Schelter et al. (2006, ISBN:9783527406234), Liu et al. (2016) <doi:10.1109/ChiCC.2016.7554480>), and partial spectral coherence (see Davis et al.(2016) <doi:10.1080/10618600.2015.1092978>). In addition, the package implements functions for ensemble feature selection (using feature ranking and majority voting). The package is implemented within Dmitry Pavlyuk's research project No. 1.1.1.2/VIAA/1/16/112 "Spatiotemporal urban traffic modelling using big data".
License: GPL-3
Depends: R (>= 3.6)
Imports: glasso,lars,mpmi,freqdom,randomForestSRC
Suggests: knitr, rmarkdown, sparsevar, plot.matrix, svMisc, MTS
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Author: Dmitry Pavlyuk [aut, cre] (<https://orcid.org/0000-0003-3710-9678>)
Maintainer: Dmitry Pavlyuk <Dmitry.Pavlyuk@tsi.lv>
Repository: CRAN
Repository/R-Forge/Project: fsmts
Repository/R-Forge/Revision: 14
Repository/R-Forge/DateTimeStamp: 2020-03-25 12:58:38
Date/Publication: 2020-03-25 15:10:05 UTC
NeedsCompilation: no
Packaged: 2020-03-25 13:11:34 UTC; rforge

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New package ecospat with initial version 3.1
Package: ecospat
Version: 3.1
Date: 2020-03-23
Title: Spatial Ecology Miscellaneous Methods
Authors@R: c( person("Olivier", "Broennimann", role = c("cre","aut","ctb"), email = "olivier.broennimann@unil.ch"), person("Valeria", "Di Cola", role = c("aut","ctb"), email = "valeriadicola@gmail.com"), person("Blaise", "Petitpierre", role = "ctb"), person("Frank", "Breiner", role = "ctb"), person("Daniel", "Scherrer", role = "ctb"), person("Manuela", "D`Amen", role = "ctb"), person("Christophe", "Randin", role = "ctb"), person("Robin", "Engler", role = "ctb"), person("Wim", "Hordijk", role = "ctb"), person("Heidi", "Mod", role = "ctb"), person("Julien", "Pottier", role = "ctb"), person("Mirko", "Di Febbraro", role = "ctb"), person("Loic", "Pellissier", role = "ctb"), person("Dorothea", "Pio", role = "ctb"), person("Ruben", "Garcia Mateo", role = "ctb"), person("Anne", "Dubuis", role = "ctb"), person("Luigi", "Maiorano", role = "ctb"), person("Achilleas", "Psomas", role = "ctb"), person("Charlotte", "Ndiribe", role = "ctb"), person("Nicolas", "Salamin", role = "ctb"), person("Niklaus", "Zimmermann", role = "ctb"), person("Antoine", "Guisan", role = "aut", email = "antoine.guisan@unil.ch"))
Author: Olivier Broennimann [cre, aut, ctb], Valeria Di Cola [aut, ctb], Blaise Petitpierre [ctb], Frank Breiner [ctb], Daniel Scherrer [ctb], Manuela D`Amen [ctb], Christophe Randin [ctb], Robin Engler [ctb], Wim Hordijk [ctb], Heidi Mod [ctb], Julien Pottier [ctb], Mirko Di Febbraro [ctb], Loic Pellissier [ctb], Dorothea Pio [ctb], Ruben Garcia Mateo [ctb], Anne Dubuis [ctb], Luigi Maiorano [ctb], Achilleas Psomas [ctb], Charlotte Ndiribe [ctb], Nicolas Salamin [ctb], Niklaus Zimmermann [ctb], Antoine Guisan [aut]
Maintainer: Olivier Broennimann <olivier.broennimann@unil.ch>
VignetteBuilder: knitr
Depends: ade4 (>= 1.6-2), ape (>= 3.2), gbm (>= 2.1.1), sp (>= 1.0-15)
Imports: adehabitatHR (>= 0.4.11), adehabitatMA (>= 0.3.8), biomod2 (>= 3.1-64), dismo (>= 0.9-3), ecodist (>= 1.2.9), maptools (>= 0.8-39), randomForest (>= 4.6-7), spatstat (>= 1.37-0), raster (>= 2.5-8), rms (>= 4.5-0), gtools (>= 3.4.1), PresenceAbsence (>= 1.1.9), methods (>= 3.1.1), doParallel (>= 1.0.10), foreach (>= 1.4.3), iterators (>= 1.0.8), parallel, classInt (>= 0.1-23), vegan (>= 2.4-1), poibin (>= 1.3), snowfall (>= 1.61), matrixStats (>= 0.53.1), maps (>= 3.0.0)
Suggests: rgdal (>= 1.2-15), rJava (>= 0.9-6), XML (>= 3.98-1.1), knitr (>= 1.14), alphahull (>= 2.1), rgeos (>= 0.3-28), igraph (>= 1.2.1), markdown (>= 1.1)
LazyData: true
URL: http://www.unil.ch/ecospat/home/menuguid/ecospat-resources/tools.html
Description: Collection of R functions and data sets for the support of spatial ecology analyses with a focus on pre, core and post modelling analyses of species distribution, niche quantification and community assembly. Written by current and former members and collaborators of the ecospat group of Antoine Guisan, Department of Ecology and Evolution (DEE) and Institute of Earth Surface Dynamics (IDYST), University of Lausanne, Switzerland. Read Di Cola et al. (2016) <doi:10.1111/ecog.02671> for details.
License: GPL
BugReports: https://github.com/ecospat/ecospat
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-03-23 07:55:03 UTC; obroenni
Repository: CRAN
Date/Publication: 2020-03-25 15:20:03 UTC

More information about ecospat at CRAN
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New package detectseparation with initial version 0.1
Package: detectseparation
Title: Detect and Check for Separation and Infinite Maximum Likelihood Estimates
Version: 0.1
Authors@R: c(person(given = "Ioannis", family = "Kosmidis", role = c("aut", "cre"), email = "ioannis.kosmidis@warwick.ac.uk", comment = c(ORCID = "0000-0003-1556-0302")), person(given = "Dirk", family = "Schumacher", role = "aut", email = "mail@dirk-schumacher.net"), person(given = "Kjell", family = "Konis", role = "ctb", email = "kjell.konis@me.com"))
Description: Provides pre-fit and post-fit methods for detecting separation and infinite maximum likelihood estimates in generalized linear models with categorical responses. The pre-fit methods apply on binomial-response generalized liner models such as logit, probit and cloglog regression, and can be directly supplied as fitting methods to the glm() function. They solve the linear programming problems for the detection of separation developed in Konis (2007, <https://ora.ox.ac.uk/objects/uuid:8f9ee0d0-d78e-4101-9ab4-f9cbceed2a2a>) using 'ROI' <https://cran.r-project.org/package=ROI> or 'lpSolveAPI' <https://cran.r-project.org/package=lpSolveAPI>. The post-fit methods apply to models with categorical responses, including binomial-response generalized linear models and multinomial-response models, such as baseline category logits and adjacent category logits models; for example, the models implemented in the 'brglm2' <https://cran.r-project.org/package=brglm2> package. The post-fit methods successively refit the model with increasing number of iteratively reweighted least squares iterations, and monitor the ratio of the estimated standard error for each parameter to what it has been in the first iteration. According to the results in Lesaffre & Albert (1989, <https://www.jstor.org/stable/2345845>), divergence of those ratios indicates data separation.
URL: https://github.com/ikosmidis/detectseparation
BugReports: https://github.com/ikosmidis/detectseparation/issues
Imports: ROI, ROI.plugin.lpsolve, lpSolveAPI, pkgload
Depends: R (>= 3.3.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Suggests: testthat, knitr, rmarkdown, covr, brglm2, AER, ROI.plugin.ecos, ROI.plugin.glpk, ROI.plugin.neos, ROI.plugin.alabama
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-03-23 17:11:43 UTC; yiannis
Author: Ioannis Kosmidis [aut, cre] (<https://orcid.org/0000-0003-1556-0302>), Dirk Schumacher [aut], Kjell Konis [ctb]
Maintainer: Ioannis Kosmidis <ioannis.kosmidis@warwick.ac.uk>
Repository: CRAN
Date/Publication: 2020-03-25 16:00:02 UTC

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New package CONCUR with initial version 1.2
Package: CONCUR
Type: Package
Title: Copy Number Profile Curve-Based Association Test
Version: 1.2
Date: 2020-3-01
Author: Amanda Brucker, Shannon T. Holloway, Jung-Ying Tzeng
Maintainer: Shannon T. Holloway <sthollow@ncsu.edu>
Description: Implements a kernel-based association test for copy number variation (CNV) aggregate analysis in a certain genomic region (e.g., gene set, chromosome, or genome) that is robust to the within-locus and across-locus etiological heterogeneity, and bypass the need to define a "locus" unit for CNVs. Brucker, A., et al. (2020) <doi:10.1101/666875>.
License: GPL-2
NeedsCompilation: no
Repository: CRAN
Encoding: UTF-8
Depends: CompQuadForm, dplyr, mgcv
RoxygenNote: 6.1.1
Collate: 'commonAUC.R' 'segLength.R' 'popFunc.R' 'uniqueCombinations.R' 'createDF.R' 'deldup.R' 'CAUCkernel.R' 'cnvData.R' 'compFunc.R' 'dataChecks.R' 'test.qt.R' 'test.bt.R' 'pv_func.R' 'concur.R'
Packaged: 2020-03-22 20:53:35 UTC; sthollow
Date/Publication: 2020-03-25 15:40:05 UTC

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New package BSW with initial version 0.1.0
Package: BSW
Type: Package
Title: Fitting a Log-Binomial Model using the Bekhit-Schöpe-Wagenpfeil (BSW) Algorithm
Version: 0.1.0
Date: 2020-03-20
Author: Adam Bekhit, Jakob Schöpe, Stefan Wagenpfeil
Maintainer: Adam Bekhit <adam.bekhit@uni-saarland.de>
Description: Implements a modified Newton-type algorithm (BSW algorithm) for solving the maximum likelihood estimation problem in fitting a log-binomial model under linear inequality constraints.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/adam-bec/BSW
BugReports: https://github.com/adam-bec/BSW/issues
Depends: Matrix, matrixStats, quadprog
Imports: methods
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-03-20 10:06:05 UTC; jakobschoepe
Repository: CRAN
Date/Publication: 2020-03-25 15:30:19 UTC

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New package bbricks with initial version 0.1.1
Type: Package
Package: bbricks
Title: Bayesian Methods and Graphical Model Structures for Statistical Modeling
Version: 0.1.1
Authors@R: person(given = "Haotian", family = "Chen", role = c("aut", "cre"), email = "chenhaotian.jtt@gmail.com", comment = structure("0000-0001-9751-2093", .Names = "ORCID"))
Description: A class of frequently used Bayesian parametric and nonparametric model structures, as well as a set of tools for common analytical tasks. Structures include Gaussian and Normal-Inverse-Wishart conjugate structure, Gaussian and Normal-Inverse-Gamma conjugate structure, Categorical and Dirichlet conjugate structure, Dirichlet Process on positive integers, Dirichlet Process in general, Hierarchical Dirichlet Process ... Tasks include updating posteriors, calculating marginal likelihood, calculating posterior predictive densities, sampling from posterior predictive distributions, calculating "Maximum A Posteriori" (MAP) estimates ... See Murphy (2012, <doi:10.1080/09332480.2014.914768>), Koller and Friedman (2009, <doi:10.1017/s0269888910000275>) and Andrieu, de Freitas, Doucet and Jordan (2003, <doi:10.1023/A:1020281327116>) for more information. See <https://chenhaotian.github.io/Bayesian-Bricks/> to get started.
License: MIT + file LICENSE
URL: https://github.com/chenhaotian/Bayesian-Bricks
BugReports: https://github.com/chenhaotian/Bayesian-Bricks/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Collate: 'Bayesian_Bricks.r' 'Categorical_Inference.r' 'Gaussian_Inference.r' 'Dirichlet_Process.r' 'MCMC.r' 'bbricks-package.R' 'testData.r'
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-03-23 10:14:29 UTC; hch
Author: Haotian Chen [aut, cre] (<https://orcid.org/0000-0001-9751-2093>)
Maintainer: Haotian Chen <chenhaotian.jtt@gmail.com>
Repository: CRAN
Date/Publication: 2020-03-25 15:30:11 UTC

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Package xgboost updated to version 1.0.0.2 with previous version 1.0.0.1 dated 2020-03-23

Title: Extreme Gradient Boosting
Description: Extreme Gradient Boosting, which is an efficient implementation of the gradient boosting framework from Chen & Guestrin (2016) <doi:10.1145/2939672.2939785>. This package is its R interface. The package includes efficient linear model solver and tree learning algorithms. The package can automatically do parallel computation on a single machine which could be more than 10 times faster than existing gradient boosting packages. It supports various objective functions, including regression, classification and ranking. The package is made to be extensible, so that users are also allowed to define their own objectives easily.
Author: Tianqi Chen [aut], Tong He [aut, cre], Michael Benesty [aut], Vadim Khotilovich [aut], Yuan Tang [aut] (<https://orcid.org/0000-0001-5243-233X>), Hyunsu Cho [aut], Kailong Chen [aut], Rory Mitchell [aut], Ignacio Cano [aut], Tianyi Zhou [aut], Mu Li [aut], Junyuan Xie [aut], Min Lin [aut], Yifeng Geng [aut], Yutian Li [aut], XGBoost contributors [cph] (base XGBoost implementation)
Maintainer: Tong He <hetong007@gmail.com>

Diff between xgboost versions 1.0.0.1 dated 2020-03-23 and 1.0.0.2 dated 2020-03-25

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Package spherepc updated to version 0.1.3 with previous version 0.1.2 dated 2020-03-24

Title: Spherical Principal Curves
Description: Fitting a principal curve to data lying in the spherical surface. This package provides principal circle, principal geodesic analysis, Hauberg's principal curves, and spherical principal curves. Moreover, it partially offers locally defined principal geodesics which are currently under study. The detailed procedure is described in Jang-Hyun Kim, Jongmin Lee and Hee-Seok Oh (2020) <arXiv:2003.02578>.
Author: Jongmin Lee [aut, cre], Jang-Hyun Kim [ctb], Hee-Seok Oh [aut]
Maintainer: Jongmin Lee <jongminlee9218@gmail.com>

Diff between spherepc versions 0.1.2 dated 2020-03-24 and 0.1.3 dated 2020-03-25

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New package streamDepletr with initial version 0.1.1
Package: streamDepletr
Title: Estimate Streamflow Depletion Due to Groundwater Pumping
Version: 0.1.1
Description: Implementation of analytical models for estimating streamflow depletion due to groundwater pumping, and other related tools. Functions are broadly split into two groups: (1) analytical streamflow depletion models, which estimate streamflow depletion for a single stream reach resulting from groundwater pumping; and (2) depletion apportionment equations, which distribute estimated streamflow depletion among multiple stream reaches within a stream network. See Zipper et al. (2018) <doi:10.1029/2018WR022707> for more information on depletion apportionment equations and Zipper et al. (2019) <doi:10.1029/2018WR024403> for more information on analytical depletion functions, which combine analytical models and depletion apportionment equations.
Authors@R: c( person("Samuel C.", "Zipper", email = "samzipper@ku.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-8735-5757")), person("Ben", "Kerr", email = "ben@foundryspatial.com", role = "ctb"), person("Tom", "Gleeson", email = "tgleeson@uvic.ca", role = "ctb", comment = c(ORCID = "0000-0001-9493-7707")), person("Qiang", "Li", email = "liqiang1205@gmail.com", role = "rev", comment = c(ORCID = "0000-0003-2221-6905")), person("Foundry Spatial Ltd.", role = "cph") )
Maintainer: Samuel C. Zipper <samzipper@ku.edu>
Copyright: Foundry Spatial Ltd.
URL: https://github.com/FoundrySpatial/streamDepletr
BugReports: https://github.com/FoundrySpatial/streamDepletr/issues
Depends: R (>= 3.5)
License: BSD_3_clause + file LICENSE
Imports: Rmpfr, dplyr, magrittr, sp
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Suggests: knitr, rmarkdown, dismo, raster, deldir, rgeos, ggplot2, reshape2, scales
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-03-24 15:59:10 UTC; samzipper
Author: Samuel C. Zipper [aut, cre] (<https://orcid.org/0000-0002-8735-5757>), Ben Kerr [ctb], Tom Gleeson [ctb] (<https://orcid.org/0000-0001-9493-7707>), Qiang Li [rev] (<https://orcid.org/0000-0003-2221-6905>), Foundry Spatial Ltd. [cph]
Repository: CRAN
Date/Publication: 2020-03-25 15:00:02 UTC

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Package SampleSize4ClinicalTrials updated to version 0.2.2 with previous version 0.2.1 dated 2020-02-27

Title: Sample Size Calculation for the Comparison of Means or Proportions in Phase III Clinical Trials
Description: There are four categories of Phase III clinical trials according to different research goals, including (1) Testing for equality, (2) Superiority trial, (3) Non-inferiority trial, and (4) Equivalence trial. This package aims to help researchers to calculate sample size when comparing means or proportions in Phase III clinical trials with different research goals.
Author: Hongchao Qi, Fang Zhu
Maintainer: Hongchao Qi <hcqi.biostat@gmail.com>

Diff between SampleSize4ClinicalTrials versions 0.2.1 dated 2020-02-27 and 0.2.2 dated 2020-03-25

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Package RLRsim updated to version 3.1-6 with previous version 3.1-3 dated 2016-11-04

Title: Exact (Restricted) Likelihood Ratio Tests for Mixed and Additive Models
Description: Rapid, simulation-based exact (restricted) likelihood ratio tests for testing the presence of variance components/nonparametric terms for models fit with nlme::lme(),lme4::lmer(), lmeTest::lmer(), gamm4::gamm4(), mgcv::gamm() and SemiPar::spm().
Author: Fabian Scheipl [aut, cre] (<https://orcid.org/0000-0001-8172-3603>), Ben Bolker [ctb] (<https://orcid.org/0000-0002-2127-0443>)
Maintainer: Fabian Scheipl <fabian.scheipl@stat.uni-muenchen.de>

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Package Rcan updated to version 1.3.81 with previous version 1.3.80 dated 2019-11-29

Title: Cancer Registry Data Analysis and Visualisation
Description: Tools for basic and advance cancer statistics and graphics. Groups individual data, merges registry data and population data, calculates age-specific rate, age-standardized rate, cumulative risk, estimated annual percentage rate with standards error. Creates graphics across variable and time, such as age-specific trends, bar chart and period-cohort trends.
Author: Mathieu Laversanne [aut, cre], Jerome Vignat [aut], Cancer Surveillance Unit [cph]
Maintainer: Mathieu Laversanne <laversannem@iarc.fr>

Diff between Rcan versions 1.3.80 dated 2019-11-29 and 1.3.81 dated 2020-03-25

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Package locfit updated to version 1.5-9.4 with previous version 1.5-9.2 dated 2020-03-23

Title: Local Regression, Likelihood and Density Estimation
Description: Local regression, likelihood and density estimation methods as described in the 1999 book by Loader.
Author: Catherine Loader [aut], Jiayang Sun [ctb], Lucent Technologies [cph], Andy Liaw [cre]
Maintainer: Andy Liaw <andy_liaw@merck.com>

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Package hdf5r updated to version 1.3.2 with previous version 1.3.1 dated 2020-01-10

Title: Interface to the 'HDF5' Binary Data Format
Description: 'HDF5' is a data model, library and file format for storing and managing large amounts of data. This package provides a nearly feature complete, object oriented wrapper for the 'HDF5' API <https://support.hdfgroup.org/HDF5/doc/RM/RM_H5Front.html> using R6 classes. Additionally, functionality is added so that 'HDF5' objects behave very similar to their corresponding R counterparts.
Author: Holger Hoefling [aut, cre], Mario Annau [aut], Novartis Institute for BioMedical Research (NIBR) [cph]
Maintainer: Holger Hoefling <hhoeflin@gmail.com>

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Package expss updated to version 0.10.2 with previous version 0.10.1 dated 2019-11-27

Title: Tables, Labels and Some Useful Functions from Spreadsheets and 'SPSS' Statistics
Description: Package computes and displays tables with support for 'SPSS'-style labels, multiple and nested banners, weights, multiple-response variables and significance testing. There are facilities for nice output of tables in 'knitr', 'Shiny', '*.xlsx' files, R and 'Jupyter' notebooks. Methods for labelled variables add value labels support to base R functions and to some functions from other packages. Additionally, the package brings popular data transformation functions from 'SPSS' Statistics and 'Excel': 'RECODE', 'COUNT', 'COMPUTE', 'DO IF', 'COUNTIF', 'VLOOKUP' and etc. These functions are very useful for data processing in marketing research surveys. Package intended to help people to move data processing from 'Excel' and 'SPSS' to R.
Author: Gregory Demin [aut, cre], Sebastian Jeworutzki [ctb] (<https://orcid.org/0000-0002-2671-5253>)
Maintainer: Gregory Demin <gdemin@gmail.com>

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Package violinplotter updated to version 1.0.1 with previous version 1.0.0 dated 2020-03-24

Title: Plotting and Comparing Means with Violin Plots
Description: Produces violin plots with optional mean comparison with Tukey's honest significant difference and linear regression. This package aims to be a simple and quick visualization tool for comparing means and assessing trends of categorical factors.
Author: Jefferson Paril [aut, cre] (<https://orcid.org/0000-0002-5693-4123>)
Maintainer: Jefferson Paril <jeffersonparil@gmail.com>

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New package RobMixReg with initial version 0.1.0
Package: RobMixReg
Type: Package
Title: Robust Mixture Regression
Version: 0.1.0
Date: 2020-02-25
Authors@R: c(person("Sha", "Cao", email = "shacao@iu.edu", role = c("aut", "cph","ths")), person("Wennan", "Chang", email = "wnchang@iu.edu", role = c("aut", "cre")), person("Chi", "Zhang", email = "czhang87@iu.edu", role = c("aut", "ctb","ths")) )
Author: Sha Cao [aut, cph, ths], Wennan Chang [aut, cre], Chi Zhang [aut, ctb, ths]
Maintainer: Wennan Chang <wnchang@iu.edu>
Description: Finite mixture models are a popular technique for modelling unobserved heterogeneity or to approximate general distribution functions in a semi-parametric way. They are used in a lot of different areas such as astronomy, biology, economics, marketing or medicine. This package is the implementation of popular robust mixture regression methods based on different algorithms including: fleximix, finite mixture models and latent class regression; CTLE, component-wise adaptive trimming likelihood estimation; mixbi, bi-square estimation; mixL, Laplacian distribution; mixt, t-distribution; TLE, trimmed likelihood estimation. The implemented algorithms includes: CTLE stands for Component-wise adaptive Trimming Likelihood Estimation based mixture regression; mixbi stands for mixture regression based on bi-square estimation; mixLstands for mixture regression based on Laplacian distribution; TLE stands for Trimmed Likelihood Estimation based mixture regression. For more detail of the algorithms, please refer to below references. Reference: Chun Yu, Weixin Yao, Kun Chen (2017) <doi:10.1002/cjs.11310>. NeyKov N, Filzmoser P, Dimova R et al. (2007) <doi:10.1016/j.csda.2006.12.024>. Bai X, Yao W. Boyer JE (2012) <doi:10.1016/j.csda.2012.01.016>. Wennen Chang, Sha Cao, Chi Zhang (2019) <doi:10.1101/426593>.
Depends: R (>= 3.5.0)
License: GPL
Encoding: UTF-8
LazyData: true
Imports: flexmix, robustbase, gtools, MASS, methods
RoxygenNote: 6.1.1
URL: https://github.com/changwn/RobMixReg
BugReports: https://github.com/changwn/RobMixReg/issues
NeedsCompilation: no
Packaged: 2020-03-23 04:11:49 UTC; wnchang
Repository: CRAN
Date/Publication: 2020-03-25 13:10:02 UTC

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New package RchivalTag with initial version 0.1.1
Package: RchivalTag
Type: Package
Title: Analyzing Archival Tagging Data
Version: 0.1.1
Date: 2020-03-23
Author: Robert Bauer
Maintainer: Robert Bauer <marine.biologging@gmail.com>
Description: A set of functions to generate, access and analyze standard data products from archival tagging data.
Depends: R (>= 3.5.0)
Imports: plyr, maptools, graphics, stats, raster, readr, rgeos, ncdf4, pracma, maps, mapdata, grDevices, oceanmap, sp, methods, PBSmapping
License: GPL (>= 3)
LazyLoad: yes
Packaged: 2020-03-24 18:42:37 UTC; work
Repository: CRAN
Date/Publication: 2020-03-25 14:00:02 UTC
NeedsCompilation: no

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Package openblender updated to version 0.5.6 with previous version 0.4.6 dated 2020-03-05

Title: Request <https://openblender.io> API Services
Description: Interface to make HTTP requests to 'OpenBlender' API services. Go to <https://openblender.io> for more information.
Author: Open Blender Inc. [cph], Daniel V. Pinacho [aut, cre]
Maintainer: Daniel V. Pinacho <danielvpinacho@gmail.com>

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Package nc updated to version 2020.3.23 with previous version 2020.2.27 dated 2020-03-04

Title: Named Capture to Data Tables
Description: User-friendly functions for extracting a data table (row for each match, column for each group) from non-tabular text data using regular expressions, and for melting columns that match a regular expression. Patterns are defined using a readable syntax that makes it easy to build complex patterns in terms of simpler, re-usable sub-patterns. Named R arguments are translated to column names in the output; capture groups without names are used internally in order to provide a standard interface to three regular expression C libraries (PCRE, RE2, ICU). Output can also include numeric columns via user-specified type conversion functions. RE2 engine (re2r package) was removed from CRAN in Mar 2020 so must be installed from github.
Author: Toby Dylan Hocking
Maintainer: Toby Dylan Hocking <toby.hocking@r-project.org>

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Package ggupset updated to version 0.2.0 with previous version 0.1.0 dated 2019-03-06

Title: Combination Matrix Axis for 'ggplot2' to Create 'UpSet' Plots
Description: Replace the standard x-axis in 'ggplots' with a combination matrix to visualize complex set overlaps. 'UpSet' has introduced a new way to visualize the overlap of sets as an alternative to Venn diagrams. This package provides a simple way to produce such plots using 'ggplot2'. In addition it can convert any categorical axis into a combination matrix axis.
Author: Constantin Ahlmann-Eltze [aut, cre] (<https://orcid.org/0000-0002-3762-068X>)
Maintainer: Constantin Ahlmann-Eltze <artjom31415@googlemail.com>

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Package edina updated to version 0.1.1 with previous version 0.1.0 dated 2020-03-23

Title: Bayesian Estimation of an Exploratory Deterministic Input, Noisy and Gate Model
Description: Perform a Bayesian estimation of the exploratory deterministic input, noisy and gate (EDINA) cognitive diagnostic model described by Chen et al. (2018) <doi:10.1007/s11336-017-9579-4>.
Author: James Joseph Balamuta [aut, cre, cph] (<https://orcid.org/0000-0003-2826-8458>), Steven Andrew Culpepper [aut, cph] (<https://orcid.org/0000-0003-4226-6176>), Jeffrey A. Douglas [aut]
Maintainer: James Joseph Balamuta <balamut2@illinois.edu>

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Package drake updated to version 7.12.0 with previous version 7.11.0 dated 2020-03-01

Title: A Pipeline Toolkit for Reproducible Computation at Scale
Description: A general-purpose computational engine for data analysis, drake rebuilds intermediate data objects when their dependencies change, and it skips work when the results are already up to date. Not every execution starts from scratch, there is native support for parallel and distributed computing, and completed projects have tangible evidence that they are reproducible. Extensive documentation, from beginner-friendly tutorials to practical examples and more, is available at the reference website <https://docs.ropensci.org/drake/> and the online manual <https://books.ropensci.org/drake/>.
Author: William Michael Landau [aut, cre] (<https://orcid.org/0000-0003-1878-3253>), Alex Axthelm [ctb], Jasper Clarkberg [ctb], Kirill Müller [ctb], Ben Bond-Lamberty [ctb] (<https://orcid.org/0000-0001-9525-4633>), Tristan Mahr [ctb] (<https://orcid.org/0000-0002-8890-5116>), Miles McBain [ctb] (<https://orcid.org/0000-0003-2865-2548>), Noam Ross [ctb] (<https://orcid.org/0000-0002-2136-0000>), Ellis Hughes [ctb], Matthew Mark Strasiotto [ctb], Ben Marwick [rev], Peter Slaughter [rev], Eli Lilly and Company [cph]
Maintainer: William Michael Landau <will.landau@gmail.com>

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Package dbnR updated to version 0.3.4 with previous version 0.3.3 dated 2020-03-20

Title: Dynamic Bayesian Network Learning and Inference
Description: Learning and inference over dynamic Bayesian networks of arbitrary Markovian order. Extends some of the functionality offered by the 'bnlearn' package to learn the networks from data and perform exact inference. It offers a modification of Trabelsi (2013) <doi:10.1007/978-3-642-41398-8_34> dynamic max-min hill climbing algorithm for structure learning and the possibility to perform forecasts of arbitrary length. A tool for visualizing the structure of the net is also provided via the 'visNetwork' package.
Author: David Quesada [aut, cre], Gabriel Valverde [ctb]
Maintainer: David Quesada <dkesada@gmail.com>

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Package BFS updated to version 0.2.5 with previous version 0.2.4 dated 2020-03-16

Title: Search and Download Data from the Swiss Federal Statistical Office (BFS)
Description: Search and download data from the Swiss Federal Statistical Office <https://www.bfs.admin.ch/>.
Author: Félix Luginbuhl [aut, cre]
Maintainer: Félix Luginbuhl <felix.luginbuhl@protonmail.ch>

Diff between BFS versions 0.2.4 dated 2020-03-16 and 0.2.5 dated 2020-03-25

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New package r2dii.data with initial version 0.0.3
Package: r2dii.data
Title: Datasets to Align Financial Markets with Climate Goals
Version: 0.0.3
Authors@R: c(person(given = "Mauro", family = "Lepore", role = c("aut", "cre", "ctr"), email = "maurolepore@gmail.com", comment = c(ORCID = "0000-0002-1986-7988")), person(given = "Jackson", family = "Hoffart", role = c("aut", "dtc"), email = "jackson@2degrees-investing.org", comment = c(ORCID = "0000-0002-8600-5042")), person(given = "Klaus", family = "Hagedorn", role = "aut", email = "klaus@2degrees-investing.org"), person(given = "2 Degrees Investing Initiative", role = c("cph", "fnd"), email = "contact@2degrees-investing.org"))
Description: These datasets support the implementation in R of the software 'PACTA' (Paris Agreement Capital Transition Assessment), which is a free tool that calculates the alignment between financial assets and climate scenarios (<https://2degrees-investing.org/>). Financial institutions use 'PACTA' to study how their capital allocation impacts the climate. Because both financial institutions and market data providers keep their data private, this package provides fake, public data to enable the development and use of 'PACTA' in R.
License: GPL-3
URL: https://github.com/2DegreesInvesting/r2dii.data
BugReports: https://github.com/2DegreesInvesting/r2dii.data/issues
Depends: R (>= 2.10)
Suggests: testthat (>= 2.1.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-03-22 22:24:45 UTC; mauro
Author: Mauro Lepore [aut, cre, ctr] (<https://orcid.org/0000-0002-1986-7988>), Jackson Hoffart [aut, dtc] (<https://orcid.org/0000-0002-8600-5042>), Klaus Hagedorn [aut], 2 Degrees Investing Initiative [cph, fnd]
Maintainer: Mauro Lepore <maurolepore@gmail.com>
Repository: CRAN
Date/Publication: 2020-03-25 13:00:02 UTC

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New package isoSurv with initial version 0.1.0
Package: isoSurv
Type: Package
Title: Isotonic Regression on Survival Analysis
Version: 0.1.0
Date: 2020-3-20
Author: Yunro Chung [aut, cre]
Maintainer: Yunro Chung <yunro.chung@asu.edu>
Description: Nonparametric estimation on survival analysis under order restrictions. It estimates monotone increasing or decreasing covariate effects in the proportional hazards model. Yunro Chung et al. (2018) <doi:10.1093/biomet/asx064>.
Depends: R (>= 3.6.0), Iso, survival
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2020-03-24 17:35:03 UTC; ychung36
Repository: CRAN
Date/Publication: 2020-03-25 12:40:02 UTC

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New package pollster with initial version 0.1.0
Package: pollster
Type: Package
Title: Calculate Crosstab and Topline Tables of Weighted Survey Data
Version: 0.1.0
Author: John D. Johnson [aut, cre]
Maintainer: John D. Johnson <john.d.johnson@marquette.edu>
Description: Calculate common types of tables for weighted survey data. Options include topline and (2-way and 3-way) crosstab tables of categorical or ordinal data as well as summary tables of weighted numeric variables. Optionally, include the margin of error at selected confidence intervals including the design effect. The design effect is calculated as described by Kish (1965) <doi:10.1002/bimj.19680100122> beginning on page 257. Output takes the form of tibbles (simple data frames). This package conveniently handles labelled data, such as that commonly used by 'Stata' and 'SPSS.' Complex survey design is not supported at this time.
Depends: R (>= 2.10)
Imports: dplyr (>= 0.8.0), stringr (>= 1.0.0), tidyr (>= 1.0.0), labelled (>= 2.0.0), lubridate, forcats, rlang (>= 0.4.5)
Suggests: ggplot2 (>= 3.3.0), knitr, rmarkdown
License: CC0
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-03-24 17:29:31 UTC; johnsonjoh
Repository: CRAN
Date/Publication: 2020-03-25 12:00:02 UTC

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Package JADE updated to version 2.0-3 with previous version 2.0-2 dated 2019-08-19

Title: Blind Source Separation Methods Based on Joint Diagonalization and Some BSS Performance Criteria
Description: Cardoso's JADE algorithm as well as his functions for joint diagonalization are ported to R. Also several other blind source separation (BSS) methods, like AMUSE and SOBI, and some criteria for performance evaluation of BSS algorithms, are given. The package is described in Miettinen, Nordhausen and Taskinen (2017) <doi:10.18637/jss.v076.i02>.
Author: Klaus Nordhausen [aut, cre] (<https://orcid.org/0000-0002-3758-8501>), Jean-Francois Cardoso [aut], Jari Miettinen [aut] (<https://orcid.org/0000-0002-3270-7014>), Hannu Oja [aut], Esa Ollila [aut], Sara Taskinen [aut] (<https://orcid.org/0000-0001-9470-7258>)
Maintainer: Klaus Nordhausen <klaus.nordhausen@tuwien.ac.at>

Diff between JADE versions 2.0-2 dated 2019-08-19 and 2.0-3 dated 2020-03-25

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New package animaltracker with initial version 0.1.0
Package: animaltracker
Title: Animal Tracker
Version: 0.1.0
Authors@R: c( person("Joe", "Champion", email = "joechampion@boisestate.edu", role = c("aut", "cre")), person("Thea", "Sukianto", email = "TheophiliaSukian@u.boisestate.edu", role=c("aut")), person("Chithkala", "Dhulipati", email = "chithkaladhulipa@u.boisestate.edu", role=c("aut")) )
Description: Utilities for spatial-temporal analysis and visualization of animal (e.g. cattle) tracking data. The core feature is a 'shiny' web application for customized processing of GPS logs, including features for data augmentation (e.g. elevation lookup), data selection, export, plotting, and statistical summaries. A data validation application allows for side-by-side comparison via time series plots and extreme value detection described by J.P. van Brakel <https://stackoverflow.com/questions/22583391/peak-signal-detection-in-realtime-timeseries-data/>.
Depends: R (>= 3.5.0)
Imports: zoo (>= 1.8.6), forcats (>= 0.4.0), lubridate (>= 1.7.0), tibble (>= 2.1.0), shinyBS (>= 0.61), V8 (>= 2.0), shinyjs (>= 1.0), shiny (>= 1.2.0), shinyWidgets (>= 0.4.4), shinycssloaders (>= 0.2.0), shinythemes (>= 1.1.2), leaflet (>= 2.0.2), leaflet.extras (>= 1.0.0), dplyr (>= 0.7.5), ggplot2 (>= 3.1.0), scales (>= 1.0.0), tidyr (>= 0.8.2), sp (>= 1.3.1), rgdal (>= 1.3.6), raster(>= 2.7.15), elevatr (>= 0.2.0), geosphere (>= 1.5.7)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-03-21 23:53:01 UTC; THEOPHILIASUKIAN
Author: Joe Champion [aut, cre], Thea Sukianto [aut], Chithkala Dhulipati [aut]
Maintainer: Joe Champion <joechampion@boisestate.edu>
Repository: CRAN
Date/Publication: 2020-03-25 11:50:02 UTC

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Package crp.CSFP (with last version 2.0.2) was removed from CRAN

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

2016-09-11 2.0.2
2015-07-11 2.0.1
2013-11-04 2.0
2013-05-08 1.2.1
2012-04-03 1.1
2012-02-20 1.0

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Package foreign updated to version 0.8-77 with previous version 0.8-76 dated 2020-03-03

Title: Read Data Stored by 'Minitab', 'S', 'SAS', 'SPSS', 'Stata', 'Systat', 'Weka', 'dBase', ...
Description: Reading and writing data stored by some versions of 'Epi Info', 'Minitab', 'S', 'SAS', 'SPSS', 'Stata', 'Systat', 'Weka', and for reading and writing some 'dBase' files.
Author: R Core Team [aut, cph, cre], Roger Bivand [ctb, cph], Vincent J. Carey [ctb, cph], Saikat DebRoy [ctb, cph], Stephen Eglen [ctb, cph], Rajarshi Guha [ctb, cph], Swetlana Herbrandt [ctb], Nicholas Lewin-Koh [ctb, cph], Mark Myatt [ctb, cph], Michael Nelson [ctb], Ben Pfaff [ctb], Brian Quistorff [ctb], Frank Warmerdam [ctb, cph], Stephen Weigand [ctb, cph], Free Software Foundation, Inc. [cph]
Maintainer: R Core Team <R-core@R-project.org>

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Package class updated to version 7.3-16 with previous version 7.3-15 dated 2019-01-01

Title: Functions for Classification
Description: Various functions for classification, including k-nearest neighbour, Learning Vector Quantization and Self-Organizing Maps.
Author: Brian Ripley [aut, cre, cph], William Venables [cph]
Maintainer: Brian Ripley <ripley@stats.ox.ac.uk>

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Package rsoi updated to version 0.5.2 with previous version 0.5.1 dated 2020-01-14

Title: Import Various Northern and Southern Hemisphere Climate Indices
Description: Downloads Southern Oscillation Index, Oceanic Nino Index, North Pacific Gyre Oscillation data, North Atlantic Oscillation and Arctic Oscillation. Data sources are described in the README file.
Author: Sam Albers [aut, cre] (<https://orcid.org/0000-0002-9270-7884>), Elio Campitelli [ctb] (<https://orcid.org/0000-0002-7742-9230>)
Maintainer: Sam Albers <sam.albers@gmail.com>

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Package radiant.multivariate updated to version 1.3.5 with previous version 0.9.9.1 dated 2019-05-16

Title: Multivariate Menu for Radiant: Business Analytics using R and Shiny
Description: The Radiant Multivariate menu includes interfaces for perceptual mapping, factor analysis, cluster analysis, and conjoint analysis. The application extends the functionality in radiant.data.
Author: Vincent Nijs [aut, cre]
Maintainer: Vincent Nijs <radiant@rady.ucsd.edu>

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Package datagovsgR updated to version 0.3.1 with previous version 0.3.0 dated 2020-02-25

Title: Calls Real Time APIs from Data Gov Singapore
Description: A wrapper for the Data Gov Singapore developer resources endpoints developer tools, which provide real time and historical information, ranging from carpark availability to weather forecasts. This tools makes the API calls for a given date and time, before returning the relevant information in a data frame. Relevant information can be found here <https://data.gov.sg/developer>.
Author: Clinton Wong <cwxy.clinton@gmail.com>
Maintainer: Clinton Wong <cwxy.clinton@gmail.com>

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Package Replication (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:

2019-08-01 0.1.1
2019-03-13 0.1.0

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Package tbrf updated to version 0.1.4 with previous version 0.1.3 dated 2019-11-15

Title: Time-Based Rolling Functions
Description: Provides rolling statistical functions based on date and time windows instead of n-lagged observations.
Author: Michael Schramm [aut, cre] (<https://orcid.org/0000-0003-1876-6592>), Frank Harrell [ctb]
Maintainer: Michael Schramm <michael.schramm@ag.tamu.edu>

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Package RobinHood updated to version 1.2.4 with previous version 1.2.1 dated 2019-10-06

Title: Interface for the RobinHood.com No Commission Investing Platform
Description: Execute API calls to the RobinHood <https://robinhood.com> investing platform. Functionality includes accessing account data and current holdings, retrieving investment statistics and quotes, placing and canceling orders, getting market trading hours, searching investments by popular tag, and interacting with watch lists.
Author: Joseph Blubaugh
Maintainer: Joseph Blubaugh <jestonblu@gmail.com>

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Package MCMCvis updated to version 0.14.0 with previous version 0.13.5 dated 2019-12-07

Title: Tools to Visualize, Manipulate, and Summarize MCMC Output
Description: Performs key functions for MCMC analysis using minimal code - visualizes, manipulates, and summarizes MCMC output. Functions support simple and straightforward subsetting of model parameters within the calls, and produce presentable and 'publication-ready' output. MCMC output may be derived from Bayesian model output fit with JAGS, Stan, or other MCMC samplers.
Author: Casey Youngflesh [aut, cre] (<https://orcid.org/0000-0001-6343-3311>), Christian Che-Castaldo [aut] (<https://orcid.org/0000-0002-7670-2178>), Tyler Hardy [ctb]
Maintainer: Casey Youngflesh <caseyyoungflesh@gmail.com>

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