Mon, 06 Apr 2020

Package NMOF updated to version 2.1-0 with previous version 2.0-1 dated 2019-10-20

Title: Numerical Methods and Optimization in Finance
Description: Functions, examples and data from the first and the second edition of "Numerical Methods and Optimization in Finance" by M. Gilli, D. Maringer and E. Schumann (2019, ISBN:978-0128150658). The package provides implementations of optimisation heuristics (Differential Evolution, Genetic Algorithms, Particle Swarm Optimisation, Simulated Annealing and Threshold Accepting), and other optimisation tools, such as grid search and greedy search. There are also functions for the valuation of financial instruments, such as bonds and options, and functions that help with stochastic simulations.
Author: Enrico Schumann [aut, cre] (<https://orcid.org/0000-0001-7601-6576>)
Maintainer: Enrico Schumann <es@enricoschumann.net>

Diff between NMOF versions 2.0-1 dated 2019-10-20 and 2.1-0 dated 2020-04-06

 DESCRIPTION                          |    8 -
 MD5                                  |   44 +++++-----
 NEWS                                 |   18 ++++
 R/market_data.R                      |  112 ++++++++++++++++++++++-----
 R/portfolio.R                        |  141 +++++++++++++++++++++++++++++++----
 build/vignette.rds                   |binary
 inst/doc/An_overview.pdf             |binary
 inst/doc/DEnss.pdf                   |binary
 inst/doc/LSqueens.pdf                |binary
 inst/doc/LSselect.pdf                |binary
 inst/doc/PSlms.pdf                   |binary
 inst/doc/TAportfolio.pdf             |binary
 inst/doc/qTableEx.pdf                |binary
 inst/doc/repair.pdf                  |binary
 inst/doc/vectorise.pdf               |binary
 inst/unitTests/test_results.txt      |   49 ++++++------
 inst/unitTests/unitTests_market.R    |    4 
 inst/unitTests/unitTests_portfolio.R |   57 +++++++++++---
 man/Shiller.Rd                       |    2 
 man/TAopt.Rd                         |    3 
 man/minvar.Rd                        |   28 ++++++
 man/mvFrontier.Rd                    |   45 +++++++++--
 man/randomReturns.Rd                 |   15 ++-
 23 files changed, 413 insertions(+), 113 deletions(-)

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New package tsmp with initial version 0.4.14
Type: Package
Package: tsmp
Title: Time Series with Matrix Profile
Version: 0.4.14
Authors@R: c(person(given = "Francisco", family = "Bischoff", role = c("aut", "cre"), email = "fbischoff@med.up.pt", comment = c(ORCID = "https://orcid.org/0000-0002-5301-8672")), person(given = "Michael", family = "Yeh", role = c("res", "ccp", "ctb"), email = "myeh003@ucr.edu", comment = c(ORCID = "https://orcid.org/0000-0002-9807-2963")), person(given = "Diego", family = "Silva", role = c("res", "ccp", "ctb"), email = "diegofs@ufscar.br", comment = c(ORCID = "https://orcid.org/0000-0002-5184-9413")), person(given = "Yan", family = "Zhu", role = c("res", "ccp", "ctb"), email = "yzhu015@ucr.edu", comment = c(ORCID = "https://orcid.org/0000-0002-5952-2108")), person(given = "Hoang", family = "Dau", role = c("res", "ccp", "ctb"), email = "hdau001@ucr.edu", comment = c(ORCID = "https://orcid.org/0000-0003-2439-5185")), person(given = "Michele", family = "Linardi", role = c("res", "ccp", "ctb"), email = "michele.linardi@orange.fr", comment = c(ORCID = "https://orcid.org/0000-0002-3249-2068")))
Maintainer: Francisco Bischoff <fbischoff@med.up.pt>
Description: A toolkit implementing the Matrix Profile concept that was created by CS-UCR <http://www.cs.ucr.edu/~eamonn/MatrixProfile.html>.
License: Apache License (>= 2.0)
URL: https://github.com/matrix-profile-foundation/tsmp
BugReports: https://github.com/matrix-profile-foundation/tsmp/issues
Depends: R (>= 3.5.0)
Imports: audio, checkmate, doSNOW, foreach, magrittr, parallel, progress, Rcpp, RcppParallel (>= 5.0.0), RJSONIO
Suggests: covr, gdtools, knitr, rmarkdown, raster, spelling, testthat (>= 2.1.0), vdiffr
LinkingTo: Rcpp (>= 1.0.3), RcppParallel (>= 5.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
NeedsCompilation: yes
RoxygenNote: 7.1.0
SystemRequirements: GNU make
Packaged: 2020-04-05 01:29:02 UTC; Franz
Author: Francisco Bischoff [aut, cre] (<https://orcid.org/0000-0002-5301-8672>), Michael Yeh [res, ccp, ctb] (<https://orcid.org/0000-0002-9807-2963>), Diego Silva [res, ccp, ctb] (<https://orcid.org/0000-0002-5184-9413>), Yan Zhu [res, ccp, ctb] (<https://orcid.org/0000-0002-5952-2108>), Hoang Dau [res, ccp, ctb] (<https://orcid.org/0000-0003-2439-5185>), Michele Linardi [res, ccp, ctb] (<https://orcid.org/0000-0002-3249-2068>)
Repository: CRAN
Date/Publication: 2020-04-06 17:10:02 UTC

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New package survCurve with initial version 1.0
Package: survCurve
Title: Plots Survival Curves Element by Element
Version: 1.0
Authors@R: person("Melchior", "Burri", email = "melchiorburri@msn.com", role = c("aut", "cre"))
Description: Plots survival models from the 'survival' package. Additionally, it plots curves of multistate models from the 'mstate' package. Typically, a plot is drawn by the sequence survplot(), confIntArea(), survCurve() and nrAtRisk(). The separation of the plot in this 4 functions allows for great flexibility to make a custom plot for publication.
Imports: survival (>= 3.1)
Depends: R (>= 3.6)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Suggests: knitr, mstate, rmarkdown
VignetteBuilder: knitr
Collate: 'confIntArea.R' 'nrAtRisk.R' 'oneGroupOneEvent.R' 'survCurve.R' 'survPlot.R'
NeedsCompilation: no
Packaged: 2020-04-05 16:41:53 UTC; melchior
Author: Melchior Burri [aut, cre]
Maintainer: Melchior Burri <melchiorburri@msn.com>
Repository: CRAN
Date/Publication: 2020-04-06 17:30:02 UTC

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New package ppgam with initial version 1.0.0
Package: ppgam
Type: Package
Title: Generalised Additive Point Process Models
Version: 1.0.0
Date: 2020-04-05
Author: Ben Youngman [aut, cre], Theo Economou [aut]
Maintainer: Ben Youngman <b.youngman@exeter.ac.uk>
Description: Methods for fitting point processes with parameters of generalised additive model (GAM) form are provided. For an introduction to point processes see Cox, D.R & Isham, V. (Point Processes, 1980, CRC Press), GAMs see Wood, S.N. (2017) <doi:10.1201/9781315370279>, and the fitting approach see Wood, S.N., Pya, N. & Safken, B. (2016) <doi:10.1080/01621459.2016.1180986>.
License: GPL-3
Depends: R (>= 3.5.0)
Imports: MASS, mgcv, evgam
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-04-05 16:26:11 UTC; ben
Repository: CRAN
Date/Publication: 2020-04-06 17:30:05 UTC

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New package brickr with initial version 0.3.2
Package: brickr
Title: Emulate LEGO Bricks in 2D and 3D
Version: 0.3.2
Authors@R: person(given = "Ryan", family = "Timpe", role = c("aut", "cre"), email = "ryan.timpe@gmail.com")
Description: Generate digital LEGO models using 'tidyverse' functions. Convert image files into 2D and 3D LEGO mosaics, complete with piece counts and instructions. Render 3D models using simple data frame instructions. Developed under the LEGO Group's Fair Play policy <https://www.lego.com/en-us/legal/notices-and-policies/fair-play/>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0.2)
Imports: ggplot2, magrittr, dplyr, tidyr, purrr, scales, farver, colorspace, rgl
Suggests: knitr, rmarkdown, gridExtra, png, jpeg, tibble, raster, stringr
RoxygenNote: 7.0.2
URL: https://github.com/ryantimpe/brickr
BugReports: https://github.com/ryantimpe/brickr/issues
Collate: 'brickr.R' 'bricks-from-mosaic.R' 'bricks-from-tables.R' 'build-bricks-rgl.R' 'build-instructions.R' 'build-mosaic.R' 'collect-bricks.R' 'colors-and-themes.R' 'data.R' 'geom-brick-rect.R' 'image-to-mosaic.R' 'image-to-prep-mosaic.R' 'piece-count.R' 'utils-pipe.R'
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-04-05 19:41:45 UTC; ryant
Author: Ryan Timpe [aut, cre]
Maintainer: Ryan Timpe <ryan.timpe@gmail.com>
Repository: CRAN
Date/Publication: 2020-04-06 17:42:06 UTC

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New package activegp with initial version 1.0.3
Package: activegp
Type: Package
Title: Gaussian Process Based Design and Analysis for the Active Subspace Method
Version: 1.0.3
Date: 2020-04-05
Author: Nathan Wycoff, Mickael Binois
Maintainer: Nathan Wycoff <nathw95@vt.edu>
Description: The active subspace method is a sensitivity analysis technique that finds important linear combinations of input variables for a simulator. This package provides functions allowing estimation of the active subspace without gradient information using Gaussian processes as well as sequential experimental design tools to minimize the amount of data required to do so. Implements Wycoff et al. (2019) <arXiv:1907.11572>.
License: BSD_3_clause + file LICENSE
Depends: R (>= 3.4.0)
Imports: Rcpp (>= 0.12.18), hetGP (>= 1.1.1), lhs, numDeriv, methods
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.1.0
Suggests: testthat
NeedsCompilation: yes
Packaged: 2020-04-05 21:21:40 UTC; nate
Repository: CRAN
Date/Publication: 2020-04-06 17:42:10 UTC

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Package spsh updated to version 1.1.0 with previous version 1.0.4 dated 2019-03-24

Title: Estimation and Prediction of Parameters of Various Soil Hydraulic Property Models
Description: Estimates model parameters of soil hydraulic property functions by inverting measured data. A wide range of hydraulic models, weighting schemes, global optimization algorithms, Markov chain Monte Carlo samplers, and extended statistical analyses of results are provided. Prediction of soil hydraulic property model parameters and common soil properties using pedotransfer functions is facilitated. Parameter estimation is based on identically and independentally distributed (weighted) model residuals, and simple model selection criteria (Hoege, M., Woehling, T., and Nowak, W. (2018) <doi:10.1002/2017WR021902>) can be calculated. The included models are the van Genuchten-Mualem in its unimodal, bimodal and trimodal form, the the Kosugi 2 parametric-Mualem model, and the Fredlund-Xing model. All models can be extended to account for non-capillary water storage and conductivity (Weber, T.K.D., Durner, W., Streck, T. and Diamantopoulos, E. (2019) <doi:10.1029/2018WR024584>. The isothermal vapour conductivity (Saito, H., Simunek, J. and Mohanty, B.P. (2006) <doi:10.2136/vzj2006.0007>) is calculated based on volumetric air space and a selection of different tortuosity models: (Grable, A.R., Siemer, E.G. (1968) <doi:10.2136/sssaj1968.03615995003200020011x>, Lai, S.H., Tiedje J.M., Erickson, E. (1976) <doi:10.2136/sssaj1976.03615995004000010006x>, Moldrup, P., Olesen, T., Rolston, D.E., and Yamaguchi, T. (1997) <doi:10.1097/00010694-199709000-00004>, Moldrup, P., Olesen, T., Yoshikawa, S., Komatsu, T., and Rolston, D.E. (2004) <doi:10.2136/sssaj2004.7500>, Moldrup, P., Olesen, T., Yoshikawa, S., Komatsu, T., and Rolston, D.E. (2005) <doi:10.1097/01.ss.0000196768.44165.1f>, Millington, R.J., Quirk, J.P. (1961) <doi:10.1039/TF9615701200>, Penman, H.L. (1940) <doi:10.1017/S0021859600048164>, and Xu, X, Nieber, J.L. Gupta, S.C. (1992) <doi:10.2136/sssaj1992.03615995005600060014x>).
Author: Tobias KD Weber [aut, cre], Efstathios Diamantopoulos [ctb], Melanie Weynants [ctb]
Maintainer: Tobias KD Weber <tobias.weber@uni-hohenheim.de>

Diff between spsh versions 1.0.4 dated 2019-03-24 and 1.1.0 dated 2020-04-06

 spsh-1.0.4/spsh/R/ptf.vG2FM.R         |only
 spsh-1.0.4/spsh/man/ptf.vG2FM.Rd      |only
 spsh-1.1.0/spsh/DESCRIPTION           |   35 -
 spsh-1.1.0/spsh/MD5                   |   97 ++-
 spsh-1.1.0/spsh/NAMESPACE             |   44 +
 spsh-1.1.0/spsh/R/Ibeta.R             |only
 spsh-1.1.0/spsh/R/KvapFun.R           |   82 ++-
 spsh-1.1.0/spsh/R/gofFun.r            |   63 ++
 spsh-1.1.0/spsh/R/inipopFun.R         |   42 +
 spsh-1.1.0/spsh/R/logLikFun.norm.R    |   27 -
 spsh-1.1.0/spsh/R/numMualem.R         |   44 +
 spsh-1.1.0/spsh/R/ptf.cW.R            |   20 
 spsh-1.1.0/spsh/R/ptf.vG2BW.R         |only
 spsh-1.1.0/spsh/R/resFun.R            |   67 ++
 spsh-1.1.0/spsh/R/shypEstFun.R        |  874 ++++++++++++++++++++++------------
 spsh-1.1.0/spsh/R/shypFun.01110.R     |   41 +
 spsh-1.1.0/spsh/R/shypFun.01210.R     |   44 +
 spsh-1.1.0/spsh/R/shypFun.01310.R     |   54 +-
 spsh-1.1.0/spsh/R/shypFun.02110.R     |   37 +
 spsh-1.1.0/spsh/R/shypFun.03110.R     |   39 +
 spsh-1.1.0/spsh/R/shypFun.04110.R     |only
 spsh-1.1.0/spsh/R/shypFun.R           |  446 +++++++++++------
 spsh-1.1.0/spsh/R/sncFun.01110.R      |only
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 spsh-1.1.0/spsh/R/spsh-package.R      |only
 spsh-1.1.0/spsh/R/transBoundFun.R     |   39 +
 spsh-1.1.0/spsh/R/transFun.R          |   25 
 spsh-1.1.0/spsh/R/weightFun.R         |   35 +
 spsh-1.1.0/spsh/build                 |only
 spsh-1.1.0/spsh/inst                  |only
 spsh-1.1.0/spsh/man/Ibeta.Rd          |only
 spsh-1.1.0/spsh/man/KvapFun.Rd        |  204 +++----
 spsh-1.1.0/spsh/man/gofFun.Rd         |  165 +++---
 spsh-1.1.0/spsh/man/inipopFun.Rd      |  112 ++--
 spsh-1.1.0/spsh/man/logLikFun.norm.Rd |   92 +--
 spsh-1.1.0/spsh/man/numMualem.Rd      |  105 +---
 spsh-1.1.0/spsh/man/ptf.cW.Rd         |   93 +--
 spsh-1.1.0/spsh/man/ptf.vG2BW.Rd      |only
 spsh-1.1.0/spsh/man/resFun.Rd         |  197 +++----
 spsh-1.1.0/spsh/man/shpdata1.Rd       |  132 ++---
 spsh-1.1.0/spsh/man/shypEstFun.Rd     |  702 ++++++++++++---------------
 spsh-1.1.0/spsh/man/shypFun.01110.Rd  |   96 +--
 spsh-1.1.0/spsh/man/shypFun.01210.Rd  |  105 ++--
 spsh-1.1.0/spsh/man/shypFun.01310.Rd  |  127 ++--
 spsh-1.1.0/spsh/man/shypFun.02110.Rd  |   89 +--
 spsh-1.1.0/spsh/man/shypFun.03110.Rd  |   94 +--
 spsh-1.1.0/spsh/man/shypFun.04110.Rd  |only
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 spsh-1.1.0/spsh/man/sncFun.01110.Rd   |only
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 spsh-1.1.0/spsh/man/sncFun.Rd         |   88 +--
 spsh-1.1.0/spsh/man/spsh-package.Rd   |  107 ----
 spsh-1.1.0/spsh/man/transBoundFun.Rd  |  117 ++--
 spsh-1.1.0/spsh/man/transFun.Rd       |   97 +--
 spsh-1.1.0/spsh/man/weightFun.Rd      |  109 +---
 58 files changed, 3080 insertions(+), 2249 deletions(-)

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New package shinyHeatmaply with initial version 0.2.0
Package: shinyHeatmaply
Type: Package
Title: Deploy 'heatmaply' using 'shiny'
Version: 0.2.0
Date: 2020-04-02
Authors@R: c( person(given = 'Jonathan',family = 'Sidi',email = 'yonicd@gmail.com',role = c('aut','cre')), person(given = 'Tal',family = 'Galili',email = 'tal.galili@metrumrg.com',role = c('aut')) )
Maintainer: Jonathan Sidi <yonicd@gmail.com>
Description: Access functionality of the 'heatmaply' package through 'Shiny UI'.
Depends: R (>= 2.3.0), heatmaply (>= 1.0.0)
Imports: shiny,htmltools,plotly,dplyr,stats,xtable,tools,rmarkdown,utils,readxl
License: GPL-2 | GPL-3
URL: https://github.com/yonicd/shinyHeatmaply
BugReports: https://github.com/yonicd/shinyHeatmaply/issues
LazyData: true
NeedsCompilation: no
Packaged: 2020-04-03 11:10:14 UTC; yonis
RoxygenNote: 7.0.2
Author: Jonathan Sidi [aut, cre], Tal Galili [aut]
Repository: CRAN
Date/Publication: 2020-04-06 16:40:02 UTC

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New package psychNET with initial version 0.0.4.1
Package: psychNET
Type: Package
Title: Psychometric Networks for Intensive Longitudinal Data
Version: 0.0.4.1
Date: 2020-04-03
Authors@R: c(person("Spyros", "Balafas", email = "s.balafas@rug.nl", role = c("aut", "cre")),person("Ernst", "Wit", role = "aut"),person("Marco", "Grzegorczyk", role = "aut"), person("Sanne", "Booij", role = "ctb"), person("Hanneke", "Wardenaar-Wigman", role = "ctb") )
Description: In the past decade, mental processes have been conceptualized as complex networks of interacting psychiatric symptoms. These networks that can be visualized by means of conditional independence graphs. For estimating the underlying directed graph from intensive longitudinal data, vector autoregression (VAR) is the most commonly used tool. This package wraps several methods in the VAR family that can be used to estimate conditional independence graphs (networks) from multivariate time-series data. The package can fit the simple VAR and VAR with exogenous variables (VARX) model Lutkepohl, H. (2005) <doi:10.1007/978-3-540-27752-1> that are currently available from the R package 'vars', and its sparse alternative by Basu S. and Michailidis, G.(2015) <doi:10.1214/15-AOS1315> and sparse vector error correction model (SVECM) implemented in the R package 'sparsevar'. The sparse graphical VAR with covariance estimation by Wild, B., Eichler, M., Friederich, H. C., Hartmann, M., Zipfel, S., & Herzog, W. (2010) <doi:10.1186/1471-2288-10-28> from the R package 'graphicalVAR' and the dynamic factor model (DFM) by Doz, Gianone & Reichlin (2011) <doi:10.1016/j.jeconom.2011.02.012> from the R package 'dynfactoR' are also available. Sparse estimation of high dimensional VAR, VARX, and vector autoregressive moving average (VARMA) and models using hierarchical lag structures Nicholson, W. B., Bien, J., Matteson, D. S. (2017) <arXiv:1412.5250v3> implemented from the R package 'bigtime' and mixed VAR for symptom time series with marginal distributions in the exponential family Haslbeck, J., Waldorp, L. J. (2015) <arXiv:1510.06871> from the package 'mgm' can also be used with this package. For the inference of symptom networks from multivariate time series of multiple individuals the 'psychNET' package adopts the multi-level VAR (MLVAR) by Epskamp, S., Waldorp, L. J., Mottus, R., & Borsboom, D. (2017) <arXiv:1609.04156v6> implemented in the R package 'mlVAR' and for the high-dimensional setting the sparse time series chain graphical model by Abegaz, F., Wit, E. (2013) <doi:10.1093/biostatistics/kxt005> available from the R package 'sparseTSCGM'.
Depends: R (>= 3.5)
Imports: vars, igraph, imputeTS, Hmisc, SparseTSCGM, mlVAR, qgraph, graphicalVAR, bigtime,mgm, crayon, longitudinal, networktools, gtools, car, stats, Matrix, methods, MASS, ordinalNet, glmnet, fastDummies, ncvreg, parallel, doParallel, reshape2, picasso, corpcor
Suggests: knitr
License: GPL (>= 2)
URL: http://www.math.rug.nl/stat/Main/HomePage
Maintainer: Spyros Balafas <s.balafas@rug.nl>
Repository: CRAN
NeedsCompilation: no
Packaged: 2020-04-05 21:01:11 UTC; balaf
Author: Spyros Balafas [aut, cre], Ernst Wit [aut], Marco Grzegorczyk [aut], Sanne Booij [ctb], Hanneke Wardenaar-Wigman [ctb]
Date/Publication: 2020-04-06 16:40:05 UTC

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Package latdiag updated to version 0.3 with previous version 0.2-4 dated 2018-05-23

Title: Draws Diagrams Useful for Checking Latent Scales
Description: A graph proposed by Rosenbaum is useful for checking some properties of various sorts of latent scale, this program generates commands to obtain the graph using 'dot' from 'graphviz'.
Author: Michael Dewey [aut, cre] (<https://orcid.org/0000-0002-7522-3677>)
Maintainer: Michael Dewey <lists@dewey.myzen.co.uk>

Diff between latdiag versions 0.2-4 dated 2018-05-23 and 0.3 dated 2020-04-06

 DESCRIPTION            |   19 ++++++++++------
 MD5                    |   34 ++++++++++++++++++++--------
 NAMESPACE              |    1 
 NEWS                   |    5 ++++
 R/draw.latent.R        |   32 ++++++++++-----------------
 R/draw.subgraph.R      |   10 +++++---
 R/plot.draw.latent.R   |    8 +++---
 R/print.draw.latent.R  |    9 +++++--
 build/partial.rdb      |binary
 build/vignette.rds     |only
 inst/REFERENCES.bib    |only
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 man/draw.latent.Rd     |   58 +++++++++++++++++++++++++------------------------
 man/latdiag-package.Rd |    5 ----
 vignettes              |only
 15 files changed, 102 insertions(+), 79 deletions(-)

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Package highlightHTML updated to version 0.2.4 with previous version 0.2.1 dated 2018-01-24

Title: Highlight HTML Text and Tables
Description: A tool to format R markdown with CSS ids for HTML output. The tool may be most helpful for those using markdown to create reproducible documents. The biggest limitations in formatting is the knowledge of CSS by the document authors.
Author: Brandon LeBeau [aut, cre] (<https://orcid.org/0000-0002-1265-8761>)
Maintainer: Brandon LeBeau <lebebr01+highlightHTML@gmail.com>

Diff between highlightHTML versions 0.2.1 dated 2018-01-24 and 0.2.4 dated 2020-04-06

 DESCRIPTION              |   10 -
 LICENSE                  |    2 
 MD5                      |   20 +-
 R/highlightHTMLmaster.r  |   42 ----
 README.md                |    9 -
 build/vignette.rds       |binary
 inst/doc/the_basics.R    |   11 -
 inst/doc/the_basics.Rmd  |    7 
 inst/doc/the_basics.html |  397 +++++++++++++++++++++++++++++++++++++----------
 man/highlight_html.Rd    |   52 ------
 vignettes/the_basics.Rmd |    7 
 11 files changed, 362 insertions(+), 195 deletions(-)

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Package econetwork updated to version 0.4 with previous version 0.3 dated 2020-03-10

Title: Analyzing Ecological Networks
Description: A collection of advanced tools, methods and models specifically designed for analyzing different types of ecological networks - especially antagonistic (food webs, host-parasite), mutualistic (plant-pollinator, plant-fungus, etc) and competitive networks, as well as their variability in time and space. Statistical models are developed to describe and understand the mechanisms that determine species interactions, and to decipher the organization of these (multi-layer) ecological networks.
Author: Stephane Dray [ctb], Catherine Matias [ctb], Vincent Miele [aut, cre], Marc Ohlmann [aut], Wilfried Thuiller [ctb]
Maintainer: Vincent Miele <vincent.miele@univ-lyon1.fr>

Diff between econetwork versions 0.3 dated 2020-03-10 and 0.4 dated 2020-04-06

 DESCRIPTION       |   13 +++++++------
 MD5               |    8 +++++---
 NAMESPACE         |   11 ++++++++---
 R/cpness.R        |only
 man/cpness.Rd     |only
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 6 files changed, 21 insertions(+), 14 deletions(-)

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Package CAST updated to version 0.4.0 with previous version 0.3.1 dated 2018-11-19

Title: 'caret' Applications for Spatial-Temporal Models
Description: Supporting functionality to run 'caret' with spatial or spatial-temporal data. 'caret' is a frequently used package for model training and prediction using machine learning. This package includes functions to improve spatial-temporal modelling tasks using 'caret'. It prepares data for Leave-Location-Out and Leave-Time-Out cross-validation which are target-oriented validation strategies for spatial-temporal models. To decrease overfitting and improve model performances, the package implements a forward feature selection that selects suitable predictor variables in view to their contribution to the target-oriented performance.
Author: Hanna Meyer [cre, aut], Chris Reudenbach [ctb], Marvin Ludwig [ctb], Thomas Nauss [ctb]
Maintainer: Hanna Meyer <hanna.meyer@uni-muenster.de>

Diff between CAST versions 0.3.1 dated 2018-11-19 and 0.4.0 dated 2020-04-06

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Package nationwider updated to version 1.1.1 with previous version 1.1.0 dated 2020-01-12

Title: Download House Price Data from Nationwide
Description: Web scraping the <https://www.nationwide.co.uk> for up-to-date data on house price indices. Download data in tidy format.
Author: Kostas Vasilopoulos [aut, cre] (<https://orcid.org/0000-0002-9769-6395>)
Maintainer: Kostas Vasilopoulos <k.vasilopoulo@gmail.com>

Diff between nationwider versions 1.1.0 dated 2020-01-12 and 1.1.1 dated 2020-04-06

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Package geomerge updated to version 0.3.2 with previous version 0.3.1 dated 2018-07-31

Title: Geospatial Data Integration
Description: Geospatial data integration framework that merges raster, spatial polygon, and (dynamic) spatial points data into a spatial (panel) data frame at any geographical resolution.
Author: Karsten Donnay and Andrew M. Linke
Maintainer: Karsten Donnay <kdonnay@gmx.net>

Diff between geomerge versions 0.3.1 dated 2018-07-31 and 0.3.2 dated 2020-04-06

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New package tbma with initial version 0.1.0
Package: tbma
Type: Package
Title: Tree-Based Moving Average Forecasting Model
Version: 0.1.0
Date: 2020-03-16
Authors@R: c(person("Burakhan", "Sel", email = "burakhan.sel@boun.edu.tr", role = c("aut", "cre")),person("Mustafa Gokce", "Baydogan", role = "aut"))
Author: Burakhan Sel [aut, cre], Mustafa Gokce Baydogan [aut]
Description: We provide a forecasting model for time series forecasting problems with predictors. The offered model, which is based on a submitted research and called tree-based moving average (TBMA), is based on the integration of the moving average approach to tree-based ensemble approach. The tree-based ensemble models can capture the complex correlations between the predictors and response variable but lack in modelling time series components. The integration of the moving average approach to the tree-based ensemble approach helps the TBMA model to handle both correlations and autocorrelations in time series data. This package provides a tbma() forecasting function that utilizes the ranger() function from the 'ranger' package. With the help of the ranger() function, various types of tree-based ensemble models, such as extremely randomized trees and random forests, can be used in the TBMA model.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Suggests: knitr, rmarkdown
Imports: data.table, ranger, zoo, RcppRoll
NeedsCompilation: no
Packaged: 2020-04-04 14:26:20 UTC; Burakhan
Maintainer: Burakhan Sel <burakhan.sel@boun.edu.tr>
Repository: CRAN
Date/Publication: 2020-04-06 14:20:03 UTC

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New package stpp with initial version 2.0-4
Package: stpp
Version: 2.0-4
Title: Space-Time Point Pattern Simulation, Visualisation and Analysis
Date: 2020-04-01
Authors@R: c(person("Edith", "Gabriel", role=c("aut","cre"), email="edith.gabriel@inrae.fr"), person("Peter J", "Diggle", role="aut", email="p.diggle@lancaster.ac.uk"), person("Barry", "Rowlingson",role="aut", email="b.rowlingson@lancaster.ac.uk"), person("Francisco J", "Rodriguez-Cortes", role="aut", email="frrodriguezc@unal.edu.co"))
Maintainer: Edith Gabriel <edith.gabriel@inrae.fr>
Depends: R (>= 3.3.0), grDevices, graphics, rpanel, splancs
Imports: KernSmooth, ggplot2, gridExtra, plot3D, rgl, spatstat, stats
Suggests: knitr(>= 1.11), rmarkdown(>= 0.8.1)
Description: Many of the models encountered in applications of point process methods to the study of spatio-temporal phenomena are covered in 'stpp'. This package provides statistical tools for analyzing the global and local second-order properties of spatio-temporal point processes, including estimators of the space-time inhomogeneous K-function and pair correlation function. It also includes tools to get static and dynamic display of spatio-temporal point patterns. See Gabriel et al (2013) <doi:10.18637/jss.v053.i02>.
License: GPL-3
LazyLoad: yes
NeedsCompilation: yes
RoxygenNote: 6.0.1
BuildVignettes: True
VignetteBuilder: knitr
BugReports: https://github.com/stpp-GitHub-community
Packaged: 2020-04-03 17:22:17 UTC; francisco
Author: Edith Gabriel [aut, cre], Peter J Diggle [aut], Barry Rowlingson [aut], Francisco J Rodriguez-Cortes [aut]
Repository: CRAN
Date/Publication: 2020-04-06 14:10:02 UTC

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Package sf updated to version 0.9-1 with previous version 0.9-0 dated 2020-03-24

Title: Simple Features for R
Description: Support for simple features, a standardized way to encode spatial vector data. Binds to 'GDAL' for reading and writing data, to 'GEOS' for geometrical operations, and to 'PROJ' for projection conversions and datum transformations.
Author: Edzer Pebesma [aut, cre] (<https://orcid.org/0000-0001-8049-7069>), Roger Bivand [ctb] (<https://orcid.org/0000-0003-2392-6140>), Etienne Racine [ctb], Michael Sumner [ctb], Ian Cook [ctb], Tim Keitt [ctb], Robin Lovelace [ctb], Hadley Wickham [ctb], Jeroen Ooms [ctb] (<https://orcid.org/0000-0002-4035-0289>), Kirill Müller [ctb], Thomas Lin Pedersen [ctb], Dan Baston [ctb]
Maintainer: Edzer Pebesma <edzer.pebesma@uni-muenster.de>

Diff between sf versions 0.9-0 dated 2020-03-24 and 0.9-1 dated 2020-04-06

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Package fsMTS updated to version 0.1.5 with previous version 0.1.4 dated 2020-03-25

Title: Feature Selection for Multivariate Time Series
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".
Author: Dmitry Pavlyuk [aut, cre] (<https://orcid.org/0000-0003-3710-9678>)
Maintainer: Dmitry Pavlyuk <Dmitry.Pavlyuk@tsi.lv>

Diff between fsMTS versions 0.1.4 dated 2020-03-25 and 0.1.5 dated 2020-04-06

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Package vip updated to version 0.2.2 with previous version 0.2.1 dated 2020-01-20

Title: Variable Importance Plots
Description: A general framework for constructing variable importance plots from various types of machine learning models in R. Aside from some standard model- specific variable importance measures, this package also provides model- agnostic approaches that can be applied to any supervised learning algorithm. These include 1) an efficient permutation-based variable importance measure, 2) variable importance based on Shapley values (Strumbelj and Kononenko, 2014) <doi:10.1007/s10115-013-0679-x>, and 3) the variance-based approach described in Greenwell et al. (2018) <arXiv:1805.04755>. A variance-based method for quantifying the relative strength of interaction effects is also included (see the previous reference for details).
Author: Brandon Greenwell [aut, cre] (<https://orcid.org/0000-0002-8120-0084>), Brad Boehmke [aut] (<https://orcid.org/0000-0002-3611-8516>), Bernie Gray [aut] (<https://orcid.org/0000-0001-9190-6032>)
Maintainer: Brandon Greenwell <greenwell.brandon@gmail.com>

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Package trialr updated to version 0.1.4 with previous version 0.1.3 dated 2020-01-08

Title: Clinical Trial Designs in 'rstan'
Description: A collection of clinical trial designs and methods, implemented in 'rstan' and R, including: the Continual Reassessment Method by O'Quigley et al. (1990) <doi:10.2307/2531628>; EffTox by Thall & Cook (2004) <doi:10.1111/j.0006-341X.2004.00218.x>; and the Augmented Binary method by Wason & Seaman (2013) <doi:10.1002/sim.5867>; and more. We provide functions to aid model-fitting and analysis. The 'rstan' implementations may also serve as a cookbook to anyone looking to extend or embellish these models. We hope that this package encourages the use of Bayesian methods in clinical trials. There is a preponderance of early phase trial designs because this is where Bayesian methods are used most. If there is a method you would like implemented, please get in touch.
Author: Kristian Brock [aut, cre] (<https://orcid.org/0000-0002-3921-0166>), Trustees of Columbia University [cph]
Maintainer: Kristian Brock <kristian.brock@gmail.com>

Diff between trialr versions 0.1.3 dated 2020-01-08 and 0.1.4 dated 2020-04-06

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 man/crm_dtps.Rd                                                             |   15 
 man/crm_fit-class.Rd                                                        |   16 
 man/crm_params-class.Rd                                                     |   14 
 man/crm_path_analysis.Rd                                                    |    3 
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 man/efftox_dtps.Rd                                                          |   11 
 man/efftox_fit-class.Rd                                                     |   23 
 man/efftox_params-class.Rd                                                  |   27 
 man/efftox_simulate.Rd                                                      |   11 
 man/peps2_get_data.Rd                                                       |   25 
 man/peps2_process.Rd                                                        |    9 
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 man/print.augbin_fit.Rd                                                     |    8 
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 man/prob_success.Rd                                                         |   13 
 man/stan_augbin.Rd                                                          |   10 
 man/stan_crm.Rd                                                             |   22 
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 man/stan_peps2.Rd                                                           |   22 
 man/trialr_simulate.Rd                                                      |   11 
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Package GridOnClusters updated to version 0.0.7 with previous version 0.0.6 dated 2020-03-27

Title: Joint Discretization of Data on a Grid that Preserves Clusters
Description: Discretize multivariate continuous data using a grid that captures the joint distribution via preserving clusters in the original data. Joint grid discretization is applicable as a data transformation step before using other methods to infer association, function, or causality without assuming a parametric model.
Author: Jiandong Wang [aut], Sajal Kumar [aut] (<https://orcid.org/0000-0003-0930-1582>), Joe Song [aut, cre] (<https://orcid.org/0000-0002-6883-6547>)
Maintainer: Joe Song <joemsong@cs.nmsu.edu>

Diff between GridOnClusters versions 0.0.6 dated 2020-03-27 and 0.0.7 dated 2020-04-06

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New package ChannelAttribution with initial version 1.17
Package: ChannelAttribution
Type: Package
Title: Markov Model for the Online Multi-Channel Attribution Problem
Version: 1.17
Date: 2020-04-03
Author: Davide Altomare, David Loris
Maintainer: Davide Altomare <davide.altomare@gmail.com>
Description: Advertisers use a variety of online marketing channels to reach consumers and they want to know the degree each channel contributes to their marketing success. This is called the online multi-channel attribution problem. This package contains a probabilistic algorithm for the attribution problem. The model uses a k-order Markov representation to identify structural correlations in the customer journey data. The package also contains three heuristic algorithms (first-touch, last-touch and linear-touch approach) for the same problem. The algorithms are implemented in C++.
License: GPL (>= 2)
URL: http://www.slideshare.net/adavide1982/markov-model-for-the-multichannel-attribution-problem http://www.lunametrics.com/blog/2016/06/30/marketing-channel-attribution-markov-models-r/ http://analyzecore.com/2016/08/03/attribution-model-r-part-1/
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp
NeedsCompilation: yes
Packaged: 2020-04-03 08:31:49 UTC; a458057
Repository: CRAN
Date/Publication: 2020-04-06 12:42:14 UTC

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New package BoutrosLab.plotting.general with initial version 6.0.0
Package: BoutrosLab.plotting.general
Version: 6.0.0
Type: Package
Title: Functions to Create Publication-Quality Plots
Date: 2020-04-01
Authors@R: c(person("Paul Boutros", role = c("aut", "cre"), email = "PBoutros@mednet.ucla.edu"), person("Christine P'ng", role = "ctb"), person("Jeff Green", role = "ctb"), person("Stephenie Prokopec", role = "ctb"), person("Ontario Institute for Cancer Research", role = "cph"), person("The R Core Team", role = "cph"), person("The R Foundation",role = "cph"), person("Robert Gentleman", role = "ctb"), person("Ross Ihaka", role = "ctb"), person("Caden Bugh", role = "ctb"))
Maintainer: Paul Boutros <PBoutros@mednet.ucla.edu>
Depends: R (>= 3.0.2), lattice (>= 0.20-27), latticeExtra (>= 0.6-26), cluster (>= 1.14.4), hexbin (>= 1.26.3), grid
Imports: gridExtra, tools, gtable, e1071, MASS(>= 7.3-29)
Suggests: Cairo (>= 1.5-1), knitr, testthat
Description: Contains several plotting functions such as barplots, scatterplots, heatmaps, as well as functions to combine plots and assist in the creation of these plots. These functions will give users great ease of use and customization options in broad use for biomedical applications, as well as general purpose plotting. Each of the functions also provides valid default settings to make plotting data more efficient and producing high quality plots with standard colour schemes simpler. All functions within this package are capable of producing plots that are of the quality to be presented in scientific publications and journals.
License: GPL-2
LazyLoad: yes
LazyData: yes
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-04-01 22:48:55 UTC; root
Author: Paul Boutros [aut, cre], Christine P'ng [ctb], Jeff Green [ctb], Stephenie Prokopec [ctb], Ontario Institute for Cancer Research [cph], The R Core Team [cph], The R Foundation [cph], Robert Gentleman [ctb], Ross Ihaka [ctb], Caden Bugh [ctb]
Repository: CRAN
Date/Publication: 2020-04-06 12:42:18 UTC

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New package anomaly with initial version 3.0.1
Package: anomaly
Type: Package
Title: Detecting Anomalies in Data
Version: 3.0.1
Date: 2020-04-02
Authors@R: c(person("Alex","Fisch",email="a.t.fisch@lancaster.ac.uk",role=c("aut")), person("Daniel","Grose",email="dan.grose@lancaster.ac.uk",role=c("aut","cre")), person("Lawrence","Bardwell",email="l.bardwell@lancaster.ac.uk",role=c("ctb")), person("Idris","Eckley",email="i.eckley@lancaster.ac.uk",role=c("ths")), person("Paul","Fearnhead",email="p.fearnhead@lancaster.ac.uk",role=c("ths")))
Description: Implements Collective And Point Anomaly (CAPA) <arXiv:1806.01947>, Multi-Variate Collective And Point Anomaly (MVCAPA) <arXiv:1909.01691>, Proportion Adaptive Segment Selection (PASS) <doi:10.1093/biomet/ass059>, and Bayesian Abnormal Region Detector (BARD) <doi:10.1214/16-BA998> methods for the detection of anomalies in time series data.
License: GPL
Imports: dplyr,rlang,methods,assertive,Rdpack,ggplot2,reshape2,Rcpp (>= 0.12.18),robustbase,cowplot
LinkingTo: Rcpp,BH
Suggests: magrittr
Depends: R (>= 3.5.0)
NeedsCompilation: yes
RoxygenNote: 7.1.0
RdMacros: Rdpack
Packaged: 2020-04-02 17:30:17 UTC; grosedj
Author: Alex Fisch [aut], Daniel Grose [aut, cre], Lawrence Bardwell [ctb], Idris Eckley [ths], Paul Fearnhead [ths]
Maintainer: Daniel Grose <dan.grose@lancaster.ac.uk>
Repository: CRAN
Date/Publication: 2020-04-06 12:42:07 UTC

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Package eudract updated to version 0.9.2 with previous version 0.9.1 dated 2020-02-13

Title: Creates Safety Results Summary in XML to Upload to EudraCT
Description: The remit of the European Clinical Trials Data Base (EudraCT <https://eudract.ema.europa.eu/> ) is to provide open access to summaries of all registered clinical trial results; thus aiming to prevent non-reporting of negative results and provide open-access to results to inform future research. The amount of information required and the format of the results, however, imposes a large extra workload at the end of studies on clinical trial units. In particular, the adverse-event-reporting component requires entering: each unique combination of treatment group and safety event; for every such event above, a further 4 pieces of information (body system, number of occurrences, number of subjects, number exposed) for non-serious events, plus an extra three pieces of data for serious adverse events (numbers of causally related events, deaths, causally related deaths). This package prepares the required statistics needed by EudraCT and formats them into the precise requirements to directly upload an XML file into the web portal, with no further data entry by hand.
Author: Simon Bond [cre], Beatrice Pantaleo [aut]
Maintainer: Simon Bond <simon.bond@addenbrookes.nhs.uk>

Diff between eudract versions 0.9.1 dated 2020-02-13 and 0.9.2 dated 2020-04-06

 DESCRIPTION                  |   10 ++--
 MD5                          |   30 +++++++-------
 NAMESPACE                    |    2 
 NEWS.md                      |    5 ++
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 man/simple_safety_xml.Rd     |   69 +++++++++++++++++---------------
 man/soc_code.Rd              |   42 +++++++++----------
 tests/testthat/test_bea.R    |    8 +--
 16 files changed, 271 insertions(+), 260 deletions(-)

More information about eudract at CRAN
Permanent link

Package stplanr updated to version 0.5.2 with previous version 0.5.1 dated 2020-03-01

Title: Sustainable Transport Planning
Description: Tools for transport planning with an emphasis on spatial transport data and non-motorized modes. Enables common transport planning tasks including: downloading and cleaning transport datasets; creating geographic "desire lines" from origin-destination (OD) data; route assignment, locally and via interfaces to routing services such as <http://cyclestreets.net/>; calculation of route segment attributes such as bearing and aggregate flow; and 'travel watershed' analysis. See Lovelace and Ellison (2018) <doi:10.32614/RJ-2018-053>.
Author: Robin Lovelace [aut, cre] (<https://orcid.org/0000-0001-5679-6536>), Richard Ellison [aut], Malcolm Morgan [aut] (<https://orcid.org/0000-0002-9488-9183>), Barry Rowlingson [ctb] (Author of overline), Nick Bearman [ctb] (Co-author of gclip), Nikolai Berkoff [ctb] (Co-author of line2route), Scott Chamberlain [rev] (Scott reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/10), Mark Padgham [ctb], Andrea Gilardi [ctb] (<https://orcid.org/0000-0002-9424-7439>)
Maintainer: Robin Lovelace <rob00x@gmail.com>

Diff between stplanr versions 0.5.1 dated 2020-03-01 and 0.5.2 dated 2020-04-06

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 46 files changed, 345 insertions(+), 346 deletions(-)

More information about stplanr at CRAN
Permanent link

Package spData updated to version 0.3.5 with previous version 0.3.3 dated 2020-02-11

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

Diff between spData versions 0.3.3 dated 2020-02-11 and 0.3.5 dated 2020-04-06

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 59 files changed, 283 insertions(+), 192 deletions(-)

More information about spData at CRAN
Permanent link

New package SpatialAcc with initial version 0.1-4
Package: SpatialAcc
Type: Package
Title: Spatial Accessibility Measures
Version: 0.1-4
Date: 2020-04-06
Authors@R: person("Stamatis", "Kalogirou", email = "stamatis@lctools.science", role = c("aut", "cre"))
Depends: R (>= 3.6)
Imports: sp
Description: Provides a set of spatial accessibility measures from a set of locations (demand) to another set of locations (supply). It aims, among others, to support research on spatial accessibility to health care facilities. Includes the locations and some characteristics of major public hospitals in Greece.
License: GPL (>= 2)
LazyData: TRUE
URL: http://lctools.science/
NeedsCompilation: no
Packaged: 2020-04-05 22:23:53 UTC; stama
Author: Stamatis Kalogirou [aut, cre]
Maintainer: Stamatis Kalogirou <stamatis@lctools.science>
Repository: CRAN
Date/Publication: 2020-04-06 10:22:06 UTC

More information about SpatialAcc at CRAN
Permanent link

Package pkgnet updated to version 0.4.1 with previous version 0.4.0 dated 2019-04-05

Title: Get Network Representation of an R Package
Description: Tools from the domain of graph theory can be used to quantify the complexity and vulnerability to failure of a software package. That is the guiding philosophy of this package. 'pkgnet' provides tools to analyze the dependencies between functions in an R package and between its imported packages. See the pkgnet website for vignettes and other supplementary information.
Author: Brian Burns [aut, cre], James Lamb [aut], Jay Qi [aut]
Maintainer: Brian Burns <brian.burns.opensource@gmail.com>

Diff between pkgnet versions 0.4.0 dated 2019-04-05 and 0.4.1 dated 2020-04-06

 pkgnet-0.4.0/pkgnet/build                                                                       |only
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 pkgnet-0.4.0/pkgnet/vignettes                                                                   |only
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 pkgnet-0.4.1/pkgnet/LICENSE                                                                     |    6 
 pkgnet-0.4.1/pkgnet/MD5                                                                         |  238 -
 pkgnet-0.4.1/pkgnet/NAMESPACE                                                                   |  142 -
 pkgnet-0.4.1/pkgnet/NEWS.md                                                                     |  170 -
 pkgnet-0.4.1/pkgnet/R/AbstractGraphReporter.R                                                   |  917 +++---
 pkgnet-0.4.1/pkgnet/R/AbstractPackageReporter.R                                                 |  376 +-
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 pkgnet-0.4.1/pkgnet/R/CreatePackageVignette.R                                                   |  307 +-
 pkgnet-0.4.1/pkgnet/R/DefaultReporters.R                                                        |   27 
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 pkgnet-0.4.1/pkgnet/R/GraphClasses.R                                                            | 1217 ++++-----
 pkgnet-0.4.1/pkgnet/R/InheritanceReporter.R                                                     |  437 +--
 pkgnet-0.4.1/pkgnet/R/SummaryReporter.R                                                         |  105 
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 pkgnet-0.4.1/pkgnet/inst/milne/DESCRIPTION                                                      |   36 
 pkgnet-0.4.1/pkgnet/inst/milne/LICENSE                                                          |    2 
 pkgnet-0.4.1/pkgnet/inst/milne/NAMESPACE                                                        |   26 
 pkgnet-0.4.1/pkgnet/inst/milne/R/Swing_Song.R                                                   |   38 
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Permanent link

Package MoTBFs updated to version 1.3 with previous version 1.2 dated 2020-01-14

Title: Learning Hybrid Bayesian Networks using Mixtures of Truncated Basis Functions
Description: Learning, manipulation and evaluation of mixtures of truncated basis functions (MoTBFs), which include mixtures of polynomials (MOPs) and mixtures of truncated exponentials (MTEs). MoTBFs are a flexible framework for modelling hybrid Bayesian networks (I. Pérez-Bernabé, A. Salmerón, H. Langseth (2015) <doi:10.1007/978-3-319-20807-7_36>; H. Langseth, T.D. Nielsen, I. Pérez-Bernabé, A. Salmerón (2014) <doi:10.1016/j.ijar.2013.09.012>; I. Pérez-Bernabé, A. Fernández, R. Rumí, A. Salmerón (2016) <doi:10.1007/s10618-015-0429-7>). The package provides functionality for learning univariate, multivariate and conditional densities, with the possibility of incorporating prior knowledge. Structural learning of hybrid Bayesian networks is also provided. A set of useful tools is provided, including plotting, printing and likelihood evaluation. This package makes use of S3 objects, with two new classes called 'motbf' and 'jointmotbf'.
Author: Inmaculada Pérez-Bernabé, Antonio Salmerón, Thomas D. Nielsen, Ana D. Maldonado
Maintainer: Ana D. Maldonado <ana.d.maldonado@ual.es>

Diff between MoTBFs versions 1.2 dated 2020-01-14 and 1.3 dated 2020-04-06

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More information about MoTBFs at CRAN
Permanent link

Package lubridate updated to version 1.7.8 with previous version 1.7.4 dated 2018-04-11

Title: Make Dealing with Dates a Little Easier
Description: Functions to work with date-times and time-spans: fast and user friendly parsing of date-time data, extraction and updating of components of a date-time (years, months, days, hours, minutes, and seconds), algebraic manipulation on date-time and time-span objects. The 'lubridate' package has a consistent and memorable syntax that makes working with dates easy and fun. Parts of the 'CCTZ' source code, released under the Apache 2.0 License, are included in this package. See <https://github.com/google/cctz> for more details.
Author: Vitalie Spinu [aut, cre], Garrett Grolemund [aut], Hadley Wickham [aut], Ian Lyttle [ctb], Imanuel Constigan [ctb], Jason Law [ctb], Doug Mitarotonda [ctb], Joseph Larmarange [ctb], Jonathan Boiser [ctb], Chel Hee Lee [ctb]
Maintainer: Vitalie Spinu <spinuvit@gmail.com>

Diff between lubridate versions 1.7.4 dated 2018-04-11 and 1.7.8 dated 2020-04-06

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Package FAOSTAT updated to version 2.1.2 with previous version 2.1.1 dated 2020-02-04

Title: Download Data from the FAOSTAT Database
Description: Download Data from the FAOSTAT Database of the Food and Agricultural Organization (FAO) of the United Nations. A list of functions to download statistics from FAOSTAT (database of the FAO <http://www.fao.org/faostat/en/#data>) and WDI (database of the World Bank <https://data.worldbank.org/>), and to perform some harmonization operations.
Author: Michael C. J. Kao <michael.kao@fao.org>, Markus Gesmann, Filippo Gheri
Maintainer: Paul Rougieux <paul.rougieux@gmail.com>

Diff between FAOSTAT versions 2.1.1 dated 2020-02-04 and 2.1.2 dated 2020-04-06

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Package blockrand updated to version 1.5 with previous version 1.3 dated 2013-01-18

Title: Randomization for Block Random Clinical Trials
Description: Create randomizations for block random clinical trials. Can also produce a pdf file of randomization cards.
Author: Greg Snow <538280@gmail.com>
Maintainer: Greg Snow <538280@gmail.com>

Diff between blockrand versions 1.3 dated 2013-01-18 and 1.5 dated 2020-04-06

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Permanent link

Package tlrmvnmvt updated to version 1.1.0 with previous version 1.0.1 dated 2020-01-11

Title: Low-Rank Methods for MVN and MVT Probabilities
Description: Implementation of the classic Genz algorithm and a novel tile-low-rank algorithm for computing relatively high-dimensional multivariate normal (MVN) and Student-t (MVT) probabilities. References used for this package: Foley, James, Andries van Dam, Steven Feiner, and John Hughes. "Computer Graphics: Principle and Practice". Addison-Wesley Publishing Company. Reading, Massachusetts (1987, ISBN:0-201-84840-6 1); Genz, A., "Numerical computation of multivariate normal probabilities," Journal of Computational and Graphical Statistics, 1, 141-149 (1992) <doi:10.1080/10618600.1992.10477010>; Cao, J., Genton, M. G., Keyes, D. E., & Turkiyyah, G. M. "Exploiting Low Rank Covariance Structures for Computing High-Dimensional Normal and Student- t Probabilities" (2019) <https://marcgenton.github.io/2019.CGKT.manuscript.pdf>.
Author: Jian Cao, Marc Genton, David Keyes, George Turkiyyah
Maintainer: Jian Cao <jian.cao@kaust.edu.sa>

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Package SimilaR updated to version 1.0.7 with previous version 1.0.6 dated 2019-07-01

Title: R Source Code Similarity Evaluation
Description: An implementation of a novel method to quantify the similarity the code-base of R functions by means of program dependence graphs. Possible use cases include detection of code clones for improving software quality and of plagiarism among students' homework assignments.
Author: Maciej Bartoszuk [aut, cre] (<https://orcid.org/0000-0001-6088-8273>), Marek Gagolewski [aut] (<https://orcid.org/0000-0003-0637-6028>)
Maintainer: Maciej Bartoszuk <bartoszuk@rexamine.com>

Diff between SimilaR versions 1.0.6 dated 2019-07-01 and 1.0.7 dated 2020-04-06

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Permanent link

Package rGEDI updated to version 0.1.6 with previous version 0.1.2 dated 2020-04-02

Title: NASA's Global Ecosystem Dynamics Investigation (GEDI) Data Visualization and Processing
Description: Set of tools for downloading, reading, visualizing and processing GEDI Level1B, Level2A and Level2B data.
Author: Carlos Alberto Silva [aut, cre, cph], Caio Hamamura [aut, cph], Ruben Valbuena [aut, ctb], Steven Hancock [aut, ctb], Adrian Cardil [aut, ctb], Eben North Broadbent [aut, ctb], Danilo Roberti Alves de Almeida [aut, ctb], Celso H. L. Silva Junior [aut, ctb], Carine Klauberg [aut, ctb], Burton Garbow [cph] (Is the author of the MINPACK-1 Least Squares Fitting Library), Kenneth Hillstrom [cph] (Is the author of the MINPACK-1 Least Squares Fitting Library), Jorge More [cph] (Is the author of the MINPACK-1 Least Squares Fitting Library), Craig Markwardt [cph] (Is the author of the enhanced MINPACK-1 Least Squares Fitting Library)
Maintainer: Carlos Alberto Silva <carlos_engflorestal@outlook.com>

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New package rdefra with initial version 0.3.8
Package: rdefra
Title: Interact with the UK AIR Pollution Database from DEFRA
Version: 0.3.8
Authors@R: c(person(given = "Claudia", family = "Vitolo", role = c("aut", "cre"), email = "cvitolodev@gmail.com", comment = c(ORCID = "0000-0002-4252-1176")), person("Andrew", "Russell", role = c("ctb"), comment = "This package is part of the KEHRA project and Andrew supervised the technical/software development."), person("Allan", "Tucker", role = c("ctb"), comment = "This package is part of the KEHRA project and Allan supervised the technical/software development."), person("Maëlle", "Salmon", role = c("ctb"), comment = "Maëlle Salmon reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/68"), person("Hao", "Zhu", role = c("ctb"), comment = "Hao Zhu reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/68"))
Maintainer: Claudia Vitolo <cvitolodev@gmail.com>
URL: https://docs.ropensci.org/rdefra, https://github.com/ropensci/rdefra
BugReports: https://github.com/ropensci/rdefra/issues
Description: Get data from DEFRA's UK-AIR website <https://uk-air.defra.gov.uk/>. It basically scrapes the HTML content.
Depends: R (>= 2.10)
Imports: lubridate, tibble, httr, xml2, dplyr, sp, rgdal
Suggests: testthat, rmarkdown, knitr, ggplot2, zoo
SystemRequirements: GDAL
VignetteBuilder: knitr
LazyData: true
Encoding: UTF-8
License: GPL-3
Repository: CRAN
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-04-05 15:18:06 UTC; claudia
Author: Claudia Vitolo [aut, cre] (<https://orcid.org/0000-0002-4252-1176>), Andrew Russell [ctb] (This package is part of the KEHRA project and Andrew supervised the technical/software development.), Allan Tucker [ctb] (This package is part of the KEHRA project and Allan supervised the technical/software development.), Maëlle Salmon [ctb] (Maëlle Salmon reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/68), Hao Zhu [ctb] (Hao Zhu reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/68)
Date/Publication: 2020-04-06 09:50:02 UTC

More information about rdefra at CRAN
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Package misty updated to version 0.3.0 with previous version 0.2.2 dated 2020-02-26

Title: Miscellaneous Functions 'T. Yanagida'
Description: Miscellaneous functions for descriptive statistics (e.g., frequency table, cross tabulation, multilevel descriptive statistics, coefficient alpha and omega, and various effect size measures), missing data (e.g., descriptive statistics for missing data, missing data pattern and auxiliary variable analysis), data management (e.g., reading and writing SPSS files, grand-mean and group-mean centering, recode variables and reverse code items, and scale and group scores), and statistical analysis (e.g., confidence intervals, Levene's test, and sample size determination).
Author: Takuya Yanagida [aut, cre]
Maintainer: Takuya Yanagida <takuya.yanagida@univie.ac.at>

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New package lctools with initial version 0.2-8
Package: lctools
Version: 0.2-8
Date: 2020-04-06
Type: Package
Title: Local Correlation, Spatial Inequalities, Geographically Weighted Regression and Other Tools
Author: Stamatis Kalogirou [aut, cre]
Maintainer: Stamatis Kalogirou <stamatis@lctools.science>
Depends: R (>= 3.6.0)
Imports: sp, reshape, weights, pscl, MASS
Description: Provides researchers and educators with easy-to-learn user friendly tools for calculating key spatial statistics and to apply simple as well as advanced methods of spatial analysis in real data. These include: Local Pearson and Geographically Weighted Pearson Correlation Coefficients, Spatial Inequality Measures (Gini, Spatial Gini, LQ, Focal LQ), Spatial Autocorrelation (Global and Local Moran's I), several Geographically Weighted Regression techniques and other Spatial Analysis tools (other geographically weighted statistics). This package also contains functions for measuring the significance of each statistic calculated, mainly based on Monte Carlo simulations.
License: GPL (>= 2)
VignetteBuilder: knitr
URL: http://lctools.science/
Suggests: knitr
NeedsCompilation: no
Packaged: 2020-04-05 22:06:59 UTC; stama
Repository: CRAN
Date/Publication: 2020-04-06 09:42:06 UTC

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Package eq5d updated to version 0.7.0 with previous version 0.6.0 dated 2020-02-04

Title: Methods for Calculating 'EQ-5D' Utility Index Scores
Description: EQ-5D is a popular health related quality of life instrument used in the clinical and economic evaluation of health care. Developed by the EuroQol group <https://www.euroqol.org>, the instrument consists of two components: health state description and evaluation. For the description component a subject self-rates their health in terms of five dimensions; mobility, self-care, usual activities, pain/discomfort, and anxiety/depression using either a three-level (EQ-5D-3L, <https://www.euroqol.org/eq-5d-instruments/eq-5d-3l-about>) or a five-level (EQ-5D-5L, <https://www.euroqol.org/eq-5d-instruments/eq-5d-5l-about>) scale. Frequently the scores on these five dimensions are converted to a single utility index using country specific value sets, which can be used in the clinical and economic evaluation of health care as well as in population health surveys. The eq5d package provides methods to calculate index scores from a subject's dimension scores. 25 TTO and 11 VAS EQ-5D-3L value sets including those for countries in Szende et al (2007) <doi:10.1007/1-4020-5511-0> and Szende et al (2014) <doi:10.1007/978-94-007-7596-1>, 20 EQ-5D-5L EQ-VT value sets from the EuroQol website, and the EQ-5D-5L crosswalk value sets developed by van Hout et al. (2012) <doi:10.1016/j.jval.2012.02.008> are included. Additionally, a shiny web tool is included to enable the calculation, visualisation and automated statistical analysis of EQ-5D index values via a web browser using EQ-5D dimension scores stored in CSV or Excel files.
Author: Fraser Morton [aut, cre], Jagtar Singh Nijjar [aut]
Maintainer: Fraser Morton <fraser.morton@glasgow.ac.uk>

Diff between eq5d versions 0.6.0 dated 2020-02-04 and 0.7.0 dated 2020-04-06

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Package DGLMExtPois updated to version 0.1.2 with previous version 0.1.1 dated 2020-02-03

Title: Double Generalized Linear Models Extending Poisson Regression
Description: Model estimation, dispersion testing and diagnosis of hyper-Poisson Saez-Castillo, A.J. and Conde-Sanchez, A. (2013) <doi:10.1016/j.csda.2012.12.009> and Conway-Maxwell-Poisson Huang, A. (2017) <doi:10.1177/1471082X17697749> regression models.
Author: Antonio Jose Saez-Castillo [aut], Antonio Conde-Sanchez [aut], Francisco Martinez [aut, cre]
Maintainer: Francisco Martinez <fmartin@ujaen.es>

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Package crmReg updated to version 1.0.1 with previous version 1.0.0 dated 2020-03-31

Title: Cellwise Robust M-Regression and SPADIMO
Description: Method for fitting a cellwise robust linear M-regression model (CRM, Filzmoser et al. (2020) <DOI:10.1016/j.csda.2020.106944>) that yields both a map of cellwise outliers consistent with the linear model, and a vector of regression coefficients that is robust against vertical outliers and leverage points. As a by-product, the method yields an imputed data set that contains estimates of what the values in cellwise outliers would need to amount to if they had fit the model. The package also provides diagnostic tools for analyzing casewise and cellwise outliers using sparse directions of maximal outlyingness (SPADIMO, Debruyne et al. (2019) <DOI:10.1007/s11222-018-9831-5>).
Author: Peter Filzmoser [aut], Sebastiaan Hoppner [aut, cre], Irene Ortner [aut], Sven Serneels [aut], Tim Verdonck [aut]
Maintainer: Sebastiaan Hoppner <sebastiaan.hoppner@kuleuven.be>

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Package sfsmisc updated to version 1.1-6 with previous version 1.1-5 dated 2020-02-09

Title: Utilities from 'Seminar fuer Statistik' ETH Zurich
Description: Useful utilities ['goodies'] from Seminar fuer Statistik ETH Zurich, some of which were ported from S-plus in the 1990's. For graphics, have pretty (Log-scale) axes, an enhanced Tukey-Anscombe plot, combining histogram and boxplot, 2d-residual plots, a 'tachoPlot()', pretty arrows, etc. For robustness, have a robust F test and robust range(). For system support, notably on Linux, provides 'Sys.*()' functions with more access to system and CPU information. Finally, miscellaneous utilities such as simple efficient prime numbers, integer codes, Duplicated(), toLatex.numeric() and is.whole().
Author: Martin Maechler [aut, cre] (<https://orcid.org/0000-0002-8685-9910>), Werner Stahel [ctb] (Functions: compresid2way(), f.robftest(), last(), p.scales(), p.dnorm()), Andreas Ruckstuhl [ctb] (Functions: p.arrows(), p.profileTraces(), p.res.2x()), Christian Keller [ctb] (Functions: histBxp(), p.tachoPlot()), Kjetil Halvorsen [ctb] (Functions: KSd(), ecdf.ksCI()), Alain Hauser [ctb] (Functions: cairoSwd(), is.whole(), toLatex.numeric()*), Christoph Buser [ctb] (to function Duplicated()), Lorenz Gygax [ctb] (to function p.res.2fact()), Bill Venables [ctb] (Functions: empty.dimnames(), primes()), Tony Plate [ctb] (to inv.seq()), Isabelle Fl<fc>ckiger [ctb], Marcel Wolbers [ctb], Markus Keller [ctb], Sandrine Dudoit [ctb], Jane Fridlyand [ctb], Greg Snow [ctb] (to loessDemo()), Henrik Aa. Nielsen [ctb] (to loessDemo()), Vincent Carey [ctb], Ben Bolker [ctb], Philippe Grosjean [ctb], Fr<e9>d<e9>ric Ibanez [ctb], Caterina Savi [ctb], Charles Geyer [ctb], Jens Oehlschl<e4>gel [ctb]
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>

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Package mlrCPO updated to version 0.3.6 with previous version 0.3.4-4 dated 2019-08-07

Title: Composable Preprocessing Operators and Pipelines for Machine Learning
Description: Toolset that enriches 'mlr' with a diverse set of preprocessing operators. Composable Preprocessing Operators ("CPO"s) are first-class R objects that can be applied to data.frames and 'mlr' "Task"s to modify data, can be attached to 'mlr' "Learner"s to add preprocessing to machine learning algorithms, and can be composed to form preprocessing pipelines.
Author: Martin Binder [aut, cre], Bernd Bischl [ctb], Michel Lang [ctb], Lars Kotthoff [ctb]
Maintainer: Martin Binder <developer.mb706@doublecaret.com>

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Package mlr3pipelines updated to version 0.1.3 with previous version 0.1.2 dated 2019-12-10

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

Diff between mlr3pipelines versions 0.1.2 dated 2019-12-10 and 0.1.3 dated 2020-04-06

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New package metarep with initial version 1.0.1
Package: metarep
Title: Replicability-Analysis Tools for Meta-Analysis
Version: 1.0.1
Depends: R (>= 3.5)
Imports: meta (>= 4.9.10),
Suggests: metafor (>= 1.9.9), lme4, numDeriv, BiasedUrn, knitr, rmarkdown
Authors@R: person("Iman","Jaljuli", role=c("cre","aut"), email="jaljuli.iman@gmail.com")
Date: 2020-03-08
URL: https://github.com/IJaljuli/metarep
Description: User-friendly package for reporting replicability-analysis methods, affixed to meta-analyses summary. The replicability-analysis output provides an assessment of the investigated intervention, where it offers quantification of effect replicability and assessment of the consistency of findings. - Replicability-analysis for fixed-effects and random-effect meta analysis: - r(u)-value; - lower bounds on the number of studies with replicated positive and\or negative effect; - Allows detecting inconsistency of signals; - forest plots with the summary of replicability analysis results; - Allows Replicability-analysis with or without the common-effect assumption.
License: GPL (>= 2)
Encoding: UTF-8
NeedsCompilation: yes
RoxygenNote: 7.0.2
VignetteBuilder: knitr
LazyData: true
Packaged: 2020-04-01 22:35:42 UTC; Iman
Author: Iman Jaljuli [cre, aut]
Maintainer: Iman Jaljuli <jaljuli.iman@gmail.com>
Repository: CRAN
Date/Publication: 2020-04-06 08:40:02 UTC

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New package covid19.analytics with initial version 1.0
Package: covid19.analytics
Type: Package
Title: Load and Analyze Live Data from the CoViD-19 Pandemic
Version: 1.0
Date: 2020-04-03
Author: Marcelo Ponce [aut, cre]
Maintainer: Marcelo Ponce <mponce@scinet.utoronto.ca>
Description: Load and analyze updated time series worldwide data of reported cases for the Novel CoronaVirus Disease (CoViD-19) from the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) data repository <https://github.com/CSSEGISandData/COVID-19>. The datasets are available in two main modalities, as a time series sequences and aggregated for the last day with greater spatial resolution. Several analysis, visualization and modelling functions are available in the package that will allow the user to compute and visualize total number of cases, total number of changes and growth rate globally or for an specific geographical location, while at the same time generating models using these trends; generate interactive visualizations and generate Susceptible-Infected-Recovered (SIR) model for the disease spread.
Imports: ape, plotly, htmlwidgets, deSolve, gplots, pheatmap
Suggests: knitr, devtools, roxygen2
License: GPL (>= 2)
URL: https://mponce0.github.io/covid19.analytics/
BugReports: https://github.com/mponce0/covid19.analytics/issues
RoxygenNote: 7.0.2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-04-03 16:03:11 UTC; marcelo
Repository: CRAN
Date/Publication: 2020-04-06 09:00:27 UTC

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Package explore updated to version 0.5.5 with previous version 0.5.4 dated 2020-02-09

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

Diff between explore versions 0.5.4 dated 2020-02-09 and 0.5.5 dated 2020-04-06

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Package exams updated to version 2.3-6 with previous version 2.3-5 dated 2020-04-04

Title: Automatic Generation of Exams in R
Description: Automatic generation of exams based on exercises in Markdown or LaTeX format, possibly including R code for dynamic generation of exercise elements. Exercise types include single-choice and multiple-choice questions, arithmetic problems, string questions, and combinations thereof (cloze). Output formats include standalone files (PDF, HTML, Docx, ODT, ...), Moodle XML, QTI 1.2, QTI 2.1, Blackboard, Canvas, OpenOLAT, ARSnova, and TCExam. In addition to fully customizable PDF exams, a standardized PDF format (NOPS) is provided that can be printed, scanned, and automatically evaluated.
Author: Achim Zeileis [aut, cre] (<https://orcid.org/0000-0003-0918-3766>), Bettina Gruen [aut] (<https://orcid.org/0000-0001-7265-4773>), Friedrich Leisch [aut] (<https://orcid.org/0000-0001-7278-1983>), Nikolaus Umlauf [aut], Mirko Birbaumer [ctb], Dominik Ernst [ctb], Patrik Keller [ctb], Niels Smits [ctb], Reto Stauffer [ctb], Kenji Sato [ctb]
Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org>

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Package Anthropometry updated to version 1.14 with previous version 1.13 dated 2019-12-06

Title: Statistical Methods for Anthropometric Data
Description: Statistical methodologies especially developed to analyze anthropometric data. These methods are aimed at providing effective solutions to some commons problems related to Ergonomics and Anthropometry. They are based on clustering, the statistical concept of data depth, statistical shape analysis and archetypal analysis. Please see Vinue (2017) <doi:10.18637/jss.v077.i06>.
Author: Guillermo Vinue, Irene Epifanio, Amelia Simo, M. Victoria Ibanez, Juan Domingo, Guillermo Ayala
Maintainer: Guillermo Vinue <Guillermo.Vinue@uv.es>

Diff between Anthropometry versions 1.13 dated 2019-12-06 and 1.14 dated 2020-04-06

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Package ijtiff updated to version 2.0.5 with previous version 2.0.4 dated 2019-10-25

Title: Comprehensive TIFF I/O with Full Support for 'ImageJ' TIFF Files
Description: General purpose TIFF file I/O for R users. Currently the only such package with read and write support for TIFF files with floating point (real-numbered) pixels, and the only package that can correctly import TIFF files that were saved from 'ImageJ' and write TIFF files than can be correctly read by 'ImageJ' <https://imagej.nih.gov/ij/>. Also supports text image I/O.
Author: Rory Nolan [aut, cre] (<https://orcid.org/0000-0002-5239-4043>), Kent Johnson [aut], Simon Urbanek [ctb], Sergi Padilla-Parra [ths] (<https://orcid.org/0000-0002-8010-9481>), Jeroen Ooms [rev, ctb] (<https://orcid.org/0000-0002-4035-0289>), Jon Clayden [rev] (<https://orcid.org/0000-0002-6608-0619>)
Maintainer: Rory Nolan <rorynoolan@gmail.com>

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