Tue, 21 Sep 2021

Package RTL updated to version 0.1.8 with previous version 0.1.7 dated 2021-06-12

Title: Risk Tool Library - Trading, Risk, Analytic for Commodities
Description: Collection of functions and metadata to complement core packages in Finance and Commodities, including futures expiry tables and <https://www.morningstar.com/products/commodities-and-energy> API functions. See <https://github.com/risktoollib/RTL>.
Author: Philippe Cote [aut, cre], Nima Safaian [aut], Mikel Buchinski [ctb], Joe Rikk [ctb], Gabriela Sanchez [ctb], Usman Farooq [ctb]
Maintainer: Philippe Cote <pcote@ualberta.ca>

Diff between RTL versions 0.1.7 dated 2021-06-12 and 0.1.8 dated 2021-09-21

 RTL-0.1.7/RTL/data/df_fut.rda              |only
 RTL-0.1.7/RTL/man/df_fut.Rd                |only
 RTL-0.1.8/RTL/DESCRIPTION                  |   10 +--
 RTL-0.1.8/RTL/MD5                          |   86 +++++++++++++++--------------
 RTL-0.1.8/RTL/NEWS.md                      |   15 +++--
 RTL-0.1.8/RTL/R/chart_PerfSummary.R        |    5 -
 RTL-0.1.8/RTL/R/data.R                     |   36 ++++++++++--
 RTL-0.1.8/RTL/R/distdescplot.R             |    5 -
 RTL-0.1.8/RTL/R/eia2tidy.R                 |    6 +-
 RTL-0.1.8/RTL/R/genscape.R                 |    7 +-
 RTL-0.1.8/RTL/R/getGIS.R                   |    2 
 RTL-0.1.8/RTL/R/globals.R                  |    4 -
 RTL-0.1.8/RTL/R/morningstar.R              |   46 +++++++++++----
 RTL-0.1.8/RTL/R/returns.R                  |    4 -
 RTL-0.1.8/RTL/R/rolladjust.R               |   23 +++----
 RTL-0.1.8/RTL/R/tradeStats.R               |    4 -
 RTL-0.1.8/RTL/data/cancrudeassays.rda      |binary
 RTL-0.1.8/RTL/data/cancrudeassayssum.rda   |binary
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 50 files changed, 176 insertions(+), 117 deletions(-)

More information about RTL at CRAN
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Package RcppML updated to version 0.3.7 with previous version 0.3.5 dated 2021-09-02

Title: Rcpp Machine Learning Library
Description: Fast machine learning algorithms including matrix factorization and divisive clustering for large sparse and dense matrices.
Author: Zachary DeBruine [aut, cre] (<https://orcid.org/0000-0003-2234-4827>)
Maintainer: Zachary DeBruine <zacharydebruine@gmail.com>

Diff between RcppML versions 0.3.5 dated 2021-09-02 and 0.3.7 dated 2021-09-21

 DESCRIPTION                          |   13 
 MD5                                  |   43 +-
 R/RcppExports.R                      |  457 ++-----------------------
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 man/RcppML.Rd                        |    2 
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 man/getRcppMLthreads.Rd              |   64 +--
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 man/project.Rd                       |  168 ++++-----
 man/setRcppMLthreads.Rd              |   70 +--
 src/RcppExports.cpp                  |  196 ++++++++---
 src/RcppFunctions.cpp                |  621 ++++++-----------------------------
 26 files changed, 983 insertions(+), 1669 deletions(-)

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Package maotai updated to version 0.2.1 with previous version 0.2.0 dated 2021-06-09

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

Diff between maotai versions 0.2.0 dated 2021-06-09 and 0.2.1 dated 2021-09-21

 DESCRIPTION              |    8 ++++----
 MD5                      |   13 +++++++------
 NEWS.md                  |    4 ++++
 R/RcppExports.R          |    4 ++++
 R/aux_hiddenR.R          |   20 +++++++++++++++++++-
 build/partial.rdb        |binary
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 8 files changed, 56 insertions(+), 11 deletions(-)

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Package bignum updated to version 0.2.2 with previous version 0.2.1 dated 2021-06-17

Title: Arbitrary-Precision Integer and Floating-Point Mathematics
Description: Classes for storing and manipulating arbitrary-precision integer vectors and high-precision floating-point vectors. These extend the range and precision of the 'integer' and 'double' data types found in R. This package utilizes the 'Boost.Multiprecision' C++ library. It is specifically designed to work well with the 'tidyverse' collection of R packages.
Author: David Hall [aut, cre, cph] (<https://orcid.org/0000-0002-2193-0480>)
Maintainer: David Hall <david.hall.physics@gmail.com>

Diff between bignum versions 0.2.1 dated 2021-06-17 and 0.2.2 dated 2021-09-21

 DESCRIPTION                      |    6 ++---
 MD5                              |   14 ++++++------
 NEWS.md                          |    4 +++
 build/vignette.rds               |binary
 inst/doc/operations.html         |    7 ++----
 inst/doc/precision.html          |   26 +++++++++--------------
 inst/doc/type-hierarchy.html     |   44 +++++++++++++++++++--------------------
 tests/testthat/test-biginteger.R |    6 ++---
 8 files changed, 53 insertions(+), 54 deletions(-)

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New package sqliteutils with initial version 0.1.0
Package: sqliteutils
Title: Utility Functions for 'SQLite'
Version: 0.1.0
Description: A tool for working with 'SQLite' databases. 'SQLite' has some idiosyncrasies and limitations that impose some hurdles to the R developer who is using this database as a repository. For instance, 'SQLite' doesn't have a date type and 'sqliteutils' has some functions to deal with that.
License: MIT + file LICENSE
Suggests: testthat (>= 3.0.0)
Encoding: UTF-8
Imports: RSQLite, DBI, dplyr, dbplyr, magrittr
NeedsCompilation: no
Packaged: 2021-09-20 21:28:30 UTC; crotm
Author: Bruno Crotman [aut, cre]
Maintainer: Bruno Crotman <crotman@gmail.com>
Repository: CRAN
Date/Publication: 2021-09-21 14:10:02 UTC

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New package CEC with initial version 0.10.3
Package: CEC
Title: Cross-Entropy Clustering
Version: 0.10.3
Date: 2021-09-20
Author: Konrad Kamieniecki [aut, cre], Przemyslaw Spurek [ctb]
Maintainer: Konrad Kamieniecki <konrad.kamieniecki@alumni.uj.edu.pl>
Description: Clustering that splits data into Gaussian type clusters. The implementation allows the simultaneous use of various type Gaussian mixture models, performs the reduction of unnecessary clusters and it's able to discover new groups. Based on Spurek, P. and Tabor, J. (2014) <doi:10.1016/j.patcog.2014.03.006>.
ByteCompile: true
URL: https://github.com/azureblue/cec
Encoding: UTF-8
NeedsCompilation: yes
SystemRequirements: C++11
License: GPL-3
Imports: graphics, methods, stats, utils
Packaged: 2021-09-20 21:50:01 UTC; konrad
Repository: CRAN
Date/Publication: 2021-09-21 14:10:05 UTC

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Package targets updated to version 0.8.0 with previous version 0.7.0 dated 2021-08-19

Title: Dynamic Function-Oriented 'Make'-Like Declarative Workflows
Description: As a pipeline toolkit for Statistics and data science in R, the 'targets' package brings together function-oriented programming and 'Make'-like declarative workflows. It analyzes the dependency relationships among the tasks of a workflow, skips steps that are already up to date, runs the necessary computation with optional parallel workers, abstracts files as R objects, and provides tangible evidence that the results match the underlying code and data. The methodology in this package borrows from GNU 'Make' (2015, ISBN:978-9881443519) and 'drake' (2018, <doi:10.21105/joss.00550>).
Author: William Michael Landau [aut, cre] (<https://orcid.org/0000-0003-1878-3253>), Matthew T. Warkentin [ctb], Samantha Oliver [rev] (<https://orcid.org/0000-0001-5668-1165>), Tristan Mahr [rev] (<https://orcid.org/0000-0002-8890-5116>), Eli Lilly and Company [cph]
Maintainer: William Michael Landau <will.landau@gmail.com>

Diff between targets versions 0.7.0 dated 2021-08-19 and 0.8.0 dated 2021-09-21

 targets-0.7.0/targets/R/utils_onload.R                                       |only
 targets-0.8.0/targets/DESCRIPTION                                            |   23 -
 targets-0.8.0/targets/MD5                                                    |  176 +++++-----
 targets-0.8.0/targets/NAMESPACE                                              |   29 +
 targets-0.8.0/targets/NEWS.md                                                |   22 +
 targets-0.8.0/targets/R/class_aws.R                                          |   33 -
 targets-0.8.0/targets/R/class_aws_feather.R                                  |    1 
 targets-0.8.0/targets/R/class_aws_file.R                                     |   15 
 targets-0.8.0/targets/R/class_aws_fst.R                                      |    9 
 targets-0.8.0/targets/R/class_aws_fst_dt.R                                   |    1 
 targets-0.8.0/targets/R/class_aws_fst_tbl.R                                  |    1 
 targets-0.8.0/targets/R/class_aws_keras.R                                    |    9 
 targets-0.8.0/targets/R/class_aws_parquet.R                                  |    9 
 targets-0.8.0/targets/R/class_aws_qs.R                                       |    9 
 targets-0.8.0/targets/R/class_aws_rds.R                                      |    9 
 targets-0.8.0/targets/R/class_aws_torch.R                                    |    9 
 targets-0.8.0/targets/R/class_builder.R                                      |   16 
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 targets-0.8.0/targets/R/class_feather.R                                      |   12 
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 targets-0.8.0/targets/R/class_imports.R                                      |    2 
 targets-0.8.0/targets/R/class_memory.R                                       |    2 
 targets-0.8.0/targets/R/class_options.R                                      |    4 
 targets-0.8.0/targets/R/class_parquet.R                                      |   12 
 targets-0.8.0/targets/R/class_store.R                                        |   49 ++
 targets-0.8.0/targets/R/class_store_file.R                                   |   24 +
 targets-0.8.0/targets/R/class_url.R                                          |    4 
 targets-0.8.0/targets/R/tar_config_get.R                                     |   90 ++++-
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 targets-0.8.0/targets/R/tar_path.R                                           |   42 +-
 targets-0.8.0/targets/R/tar_resources_future.R                               |    6 
 targets-0.8.0/targets/R/tar_target.R                                         |   59 +++
 targets-0.8.0/targets/R/tar_target_raw.R                                     |    6 
 targets-0.8.0/targets/R/tar_timestamp.R                                      |   16 
 targets-0.8.0/targets/R/tar_watch.R                                          |    8 
 targets-0.8.0/targets/R/tar_watch_server.R                                   |   57 ++-
 targets-0.8.0/targets/R/utils_imports.R                                      |    8 
 targets-0.8.0/targets/build/partial.rdb                                      |binary
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 targets-0.8.0/targets/tests/aws/test-class_aws_file.R                        |    2 
 targets-0.8.0/targets/tests/aws/test-class_aws_qs.R                          |   54 ++-
 targets-0.8.0/targets/tests/aws/test-prefix.R                                |    4 
 targets-0.8.0/targets/tests/hpc/test-future_sge.R                            |   32 +
 targets-0.8.0/targets/tests/testthat/test-class_build.R                      |    4 
 targets-0.8.0/targets/tests/testthat/test-class_builder.R                    |   80 ++++
 targets-0.8.0/targets/tests/testthat/test-class_feather.R                    |    1 
 targets-0.8.0/targets/tests/testthat/test-class_frames.R                     |    4 
 targets-0.8.0/targets/tests/testthat/test-class_fst.R                        |    1 
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 targets-0.8.0/targets/vignettes/overview.Rmd                                 |   16 
 93 files changed, 1535 insertions(+), 387 deletions(-)

More information about targets at CRAN
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Package tarchetypes updated to version 0.3.1 with previous version 0.3.0 dated 2021-08-04

Title: Archetypes for Targets
Description: Function-oriented Make-like declarative workflows for Statistics and data science are supported in the 'targets' R package. As an extension to 'targets', the 'tarchetypes' package provides convenient user-side functions to make 'targets' easier to use. By establishing reusable archetypes for common kinds of targets and pipelines, these functions help express complicated reproducible workflows concisely and compactly. The methods in this package were influenced by the 'drake' R package by Will Landau (2018) <doi:10.21105/joss.00550>.
Author: William Michael Landau [aut, cre] (<https://orcid.org/0000-0003-1878-3253>), Samantha Oliver [rev] (<https://orcid.org/0000-0001-5668-1165>), Tristan Mahr [rev] (<https://orcid.org/0000-0002-8890-5116>), Eli Lilly and Company [cph]
Maintainer: William Michael Landau <will.landau@gmail.com>

Diff between tarchetypes versions 0.3.0 dated 2021-08-04 and 0.3.1 dated 2021-09-21

 DESCRIPTION               |    6 ++--
 MD5                       |   68 +++++++++++++++++++++++-----------------------
 NEWS.md                   |    5 +++
 R/tar_age.R               |    8 ++---
 R/tar_cue_age.R           |    7 ++--
 R/tar_cue_age_raw.R       |    7 ++--
 R/tar_map.R               |   19 ------------
 R/utils_language.R        |    1 
 inst/WORDLIST             |    2 +
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Package specmine updated to version 3.1.6 with previous version 3.1.5 dated 2021-05-16

Title: Metabolomics and Spectral Data Analysis and Mining
Description: Provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, feature selection and pathway analysis. Case studies can be found on the website: <http://bio.di.uminho.pt/metabolomicspackage/index.html>. This package suggests 'rcytoscapejs', a package not in mainstream repositories. If you need to install it, use: devtools::install_github('cytoscape/r-cytoscape.js@v0.0.7').
Author: Christopher Costa <chrisbcl@hotmail.com> [aut], Marcelo Maraschin <mtocsy@gmail.com> [aut], Miguel Rocha <mrocha@di.uminho.pt> [aut, cre], Sara Cardoso <saracardoso501@gmail.com> [aut], Telma Afonso <telma.afonso94@gmail.com> [aut], Bruno Pereira <pereirinha_bp@hotmail.com> [aut], C. Beleites [cph], Jie Hao [cph],
Maintainer: Miguel Rocha <mrocha@di.uminho.pt>

Diff between specmine versions 3.1.5 dated 2021-05-16 and 3.1.6 dated 2021-09-21

 DESCRIPTION                                  |    8 
 MD5                                          |  492 ++++----
 NAMESPACE                                    |  424 +++---
 R/MAIT_metabolite_identification.R           |  300 ++--
 R/NMR_metabolite_identification.R            | 1042 ++++++++---------
 R/PATHWAY_ANALYSIS.R                         |  928 +++++++--------
 R/clustering.R                               |  256 ++--
 R/convert_chemospec.R                        |   30 
 R/data_integration.R                         |   64 -
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 R/missing_values.R                           |  180 +-
 R/ms_functions.R                             |  128 +-
 R/nmr_id_utils.R                             |  124 +-
 R/normalization.R                            |  378 +++---
 R/pca.R                                      |  930 +++++++--------
 R/peak_alignment.R                           |  630 +++++-----
 R/peaklists.R                                |  424 +++---
 R/preprocessing.R                            |  714 +++++------
 R/read.spc.modifed.R                         | 1610 +++++++++++++-------------
 R/read_NMR_spectra.R                         | 1640 +++++++++++++--------------
 R/read_dx.R                                  |  242 +--
 R/read_spc.R                                 |  100 -
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 R/regression.R                               |  174 +-
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 R/structure.R                                | 1266 ++++++++++----------
 R/univariate.R                               |  962 +++++++--------
 R/utils.R                                    |   56 
 README.md                                    |   88 -
 build/vignette.rds                           |binary
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More information about specmine at CRAN
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Package RKorAPClient updated to version 0.7.1 with previous version 0.6.1 dated 2021-03-12

Title: 'KorAP' Web Service Client Package
Description: A client package that makes the 'KorAP' web service API accessible from R. The corpus analysis platform 'KorAP' has been developed as a scientific tool to make potentially large, stratified and multiply annotated corpora, such as the 'German Reference Corpus DeReKo' or the 'Corpus of the Contemporary Romanian Language CoRoLa', accessible for linguists to let them verify hypotheses and to find interesting patterns in real language use. The 'RKorAPClient' package provides access to 'KorAP' and the corpora behind it for user-created R code, as a programmatic alternative to the 'KorAP' web user-interface. You can learn more about 'KorAP' and use it directly on 'DeReKo' at <https://korap.ids-mannheim.de/>.
Author: Marc Kupietz [aut, cre], Nils Diewald [ctb], Leibniz Institute for the German Language [cph, fnd]
Maintainer: Marc Kupietz <kupietz@ids-mannheim.de>

Diff between RKorAPClient versions 0.6.1 dated 2021-03-12 and 0.7.1 dated 2021-09-21

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New package RcppCensSpatial with initial version 0.1.0
Package: RcppCensSpatial
Title: Spatial Estimation and Prediction for Censored/Missing Responses
Version: 0.1.0
Description: It provides functions to estimate the parameters in spatial models with censored/missing responses via the Expectation-Maximization (EM) algorithm (see Dempster, Laird, and Rubin (1977)<https://www.jstor.org/stable/2984875>), the Stochastic Approximation EM (SAEM) algorithm (see Delyon, Lavielle, and Moulines (1999)<https://www.jstor.org/stable/120120>), and the Monte Carlo EM (MCEM) algorithm (see Wei and Tanner (1990)<doi:10.1080/01621459.1990.10474930>). These algorithms are widely used to compute the maximum likelihood (ML) estimates in incomplete data problems. The EM algorithm computes the ML estimates when a closed expression for the conditional expectation of the complete-data log-likelihood function is available. In the MCEM algorithm, the conditional expectation is substituted by a Monte Carlo approximation based on many independent simulations of the missing data, while the SAEM algorithm splits the E-step into a simulation step and an integration step. The SAEM algorithm was developed as an alternative to the computationally intensive MCEM algorithm. This package also approximates the standard error of the estimates using the method developed by Louis (1982)<https://www.jstor.org/stable/2345828>. It also has a function that performs spatial prediction in a set of new locations. Besides the functions to estimate parameters, this package allows computing the covariance matrix and the distance matrix.
License: GPL (>= 2)
Encoding: UTF-8
Imports: ggplot2, gridExtra, MomTrunc, mvtnorm, Rcpp, Rdpack, stats, tlrmvnmvt
RdMacros: Rdpack
LinkingTo: RcppArmadillo, Rcpp, RcppProgress, roptim
Suggests: CensSpatial, relliptical, StempCens
NeedsCompilation: yes
Packaged: 2021-09-20 18:32:13 UTC; 55199
Author: Katherine A. L. Valeriano [aut, cre] (<https://orcid.org/0000-0001-6388-4753>), Alejandro Ordonez Cuastumal [ctb] (<https://orcid.org/0000-0002-8157-9012>), Christian Galarza Morales [ctb] (<https://orcid.org/0000-0002-4818-6006>), Larissa Avila Matos [ctb] (<https://orcid.org/0000-0002-2635-0901>)
Maintainer: Katherine A. L. Valeriano <katandreina@gmail.com>
Repository: CRAN
Date/Publication: 2021-09-21 13:50:02 UTC

More information about RcppCensSpatial at CRAN
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Package portfolioBacktest updated to version 0.3.0 with previous version 0.2.3 dated 2021-01-12

Title: Automated Backtesting of Portfolios over Multiple Datasets
Description: Automated backtesting of multiple portfolios over multiple datasets of stock prices in a rolling-window fashion. Intended for researchers and practitioners to backtest a set of different portfolios, as well as by a course instructor to assess the students in their portfolio design in a fully automated and convenient manner, with results conveniently formatted in tables and plots. Each portfolio design is easily defined as a function that takes as input a window of the stock prices and outputs the portfolio weights. Multiple portfolios can be easily specified as a list of functions or as files in a folder. Multiple datasets can be conveniently extracted randomly from different markets, different time periods, and different subsets of the stock universe. The results can be later assessed and ranked with tables based on a number of performance criteria (e.g., expected return, volatility, Sharpe ratio, drawdown, turnover rate, return on investment, computational time, etc.), as well as plotted in a number of ways with nice barplots and boxplots.
Author: Daniel P. Palomar [cre, aut], Rui Zhou [aut]
Maintainer: Daniel P. Palomar <daniel.p.palomar@gmail.com>

Diff between portfolioBacktest versions 0.2.3 dated 2021-01-12 and 0.3.0 dated 2021-09-21

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New package PoDBAY with initial version 1.4.3
Package: PoDBAY
Title: Vaccine Efficacy Estimation Package
Version: 1.4.3
Depends: R (>= 3.6)
Date: 2021-09-20
Maintainer: Julie Dudasova (MSD) <julie.dudasova@merck.com>
Description: Set of functions that implement the PoDBAY method, described in the publication 'A method to estimate probability of disease and vaccine efficacy from clinical trial immunogenicity data' by Julie Dudasova, Regina Laube, Chandni Valiathan, Matthew C. Wiener, Ferdous Gheyas, Pavel Fiser, Justina Ivanauskaite, Frank Liu and Jeffrey R. Sachs (NPJ Vaccines, 2021), <doi:10.1038/s41541-021-00377-6>.
License: GPL-3
Copyright: 2021 Merck Sharp & Dohme Corp. a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp
Imports: Rcpp (>= 1.0.0), ggplot2 (>= 3.1.0), dplyr (>= 0.8.0.1), methods (>= 3.5.2), stats
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-09-20 07:38:33 UTC; vavrycuk
Author: Pavel Fiser (MSD) [aut], Tomas Bartonek (MSD) [aut], Julie Dudasova (MSD) [aut, cre], Regina Laube (MSD) [aut]
Repository: CRAN
Date/Publication: 2021-09-21 13:10:48 UTC

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Package pedquant updated to version 0.1.7 with previous version 0.1.6 dated 2020-08-27

Title: Public Economic Data and Quantitative Analysis
Description: Provides an interface to access public economic and financial data for economic research and quantitative analysis. The data sources including NBS, FRED, Yahoo Finance, 163 Finance and etc.
Author: Shichen Xie [aut, cre]
Maintainer: Shichen Xie <xie@shichen.name>

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Package pavo updated to version 2.7.1 with previous version 2.7.0 dated 2021-03-23

Title: Perceptual Analysis, Visualization and Organization of Spectral Colour Data
Description: A cohesive framework for the spectral and spatial analysis of colour described in Maia, Eliason, Bitton, Doucet & Shawkey (2013) <doi:10.1111/2041-210X.12069> and Maia, Grsuon, Endler & White (2019) <doi:10.1111/2041-210X.13174>.
Author: Thomas White [aut, cre] (<https://orcid.org/0000-0002-3976-1734>), Rafael Maia [aut] (<https://orcid.org/0000-0002-7563-9795>), Hugo Gruson [aut] (<https://orcid.org/0000-0002-4094-1476>), John Endler [aut], Chad Eliason [aut], Pierre-Paul Bitton [aut] (<https://orcid.org/0000-0001-5984-2331>)
Maintainer: Thomas White <thomas.white026@gmail.com>

Diff between pavo versions 2.7.0 dated 2021-03-23 and 2.7.1 dated 2021-09-21

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New package multiblock with initial version 0.8.0
Encoding: UTF-8
Package: multiblock
Title: Multiblock Data Fusion in Statistics and Machine Learning
Version: 0.8.0
Date: 2021-09-07
Description: Functions and datasets to support Smilde, Næs and Liland (2021, ISBN: 978-1-119-60096-1) "Multiblock Data Fusion in Statistics and Machine Learning - Applications in the Natural and Life Sciences". This implements and imports a large collection of methods for multiblock data analysis with common interfaces, result- and plotting functions, several real data sets and six vignettes covering a range different applications.
License: GPL (>= 2)
URL: https://khliland.github.io/multiblock/, https://github.com/khliland/multiblock/
BugReports: https://github.com/khliland/multiblock/issues/
Depends: R (>= 3.5.0)
Imports: ade4, car, FactoMineR, geigen, knitr, lme4, MASS, MFAg, mixlm, plotrix, pls, plsVarSel, pracma, progress, r.jive, Rcpp, RegularizedSCA, RGCCA, RSpectra, SSBtools
Suggests: rmarkdown
LinkingTo: Rcpp, RcppEigen
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-09-20 09:15:32 UTC; kristl
Author: Kristian Hovde Liland [aut, cre] (<https://orcid.org/0000-0001-6468-9423>), Solve Sæbø [ctb], Stefan Schrunner [rev]
Maintainer: Kristian Hovde Liland <kristian.liland@nmbu.no>
Repository: CRAN
Date/Publication: 2021-09-21 13:10:26 UTC

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Package mrbayes updated to version 0.5.0 with previous version 0.4.0 dated 2021-07-13

Title: Bayesian Summary Data Models for Mendelian Randomization Studies
Description: Bayesian estimation of inverse variance weighted (IVW), Burgess et al. (2013) <doi:10.1002/gepi.21758>, and MR-Egger, Bowden et al. (2015) <doi:10.1093/ije/dyv080>, summary data models for Mendelian randomization analyses.
Author: Okezie Uche-Ikonne [aut, cre] (<https://orcid.org/0000-0002-8461-8099>), Frank Dondelinger [aut] (<https://orcid.org/0000-0003-1816-6300>), Tom Palmer [aut] (<https://orcid.org/0000-0003-4655-4511>)
Maintainer: Okezie Uche-Ikonne <okezieikonne@gmail.com>

Diff between mrbayes versions 0.4.0 dated 2021-07-13 and 0.5.0 dated 2021-09-21

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Package MAINT.Data updated to version 2.6.2 with previous version 2.6.1 dated 2021-05-04

Title: Model and Analyse Interval Data
Description: Implements methodologies for modelling interval data by Normal and Skew-Normal distributions, considering appropriate parameterizations of the variance-covariance matrix that takes into account the intrinsic nature of interval data, and lead to four different possible configuration structures. The Skew-Normal parameters can be estimated by maximum likelihood, while Normal parameters may be estimated by maximum likelihood or robust trimmed maximum likelihood methods.
Author: Pedro Duarte Silva <psilva@porto.ucp.pt>, Paula Brito <mpbrito.fep.up.pt>
Maintainer: Pedro Duarte Silva <psilva@ucp.pt>

Diff between MAINT.Data versions 2.6.1 dated 2021-05-04 and 2.6.2 dated 2021-09-21

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Package drake updated to version 7.13.3 with previous version 7.13.2 dated 2021-04-22

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>

Diff between drake versions 7.13.2 dated 2021-04-22 and 7.13.3 dated 2021-09-21

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Package clock updated to version 0.4.1 with previous version 0.4.0 dated 2021-07-22

Title: Date-Time Types and Tools
Description: Provides a comprehensive library for date-time manipulations using a new family of orthogonal date-time classes (durations, time points, zoned-times, and calendars) that partition responsibilities so that the complexities of time zones are only considered when they are really needed. Capabilities include: date-time parsing, formatting, arithmetic, extraction and updating of components, and rounding.
Author: Davis Vaughan [aut, cre], RStudio [cph, fnd]
Maintainer: Davis Vaughan <davis@rstudio.com>

Diff between clock versions 0.4.0 dated 2021-07-22 and 0.4.1 dated 2021-09-21

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Package chicane updated to version 0.1.7 with previous version 0.1.6 dated 2021-07-25

Title: Capture Hi-C Analysis Engine
Description: Toolkit for processing and calling interactions in capture Hi-C data. Converts BAM files into counts of reads linking restriction fragments, and identifies pairs of fragments that interact more than expected by chance. Significant interactions are identified by comparing the observed read count to the expected background rate from a count regression model.
Author: Erle Holgersen [aut], Olivia Leavy [aut], Olivia Fletcher [aut], Frank Dudbridge [aut], Syed Haider [aut, cre]
Maintainer: Syed Haider <Syed.Haider@icr.ac.uk>

Diff between chicane versions 0.1.6 dated 2021-07-25 and 0.1.7 dated 2021-09-21

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Package bssm updated to version 1.1.7-1 with previous version 1.1.7 dated 2021-09-20

Title: Bayesian Inference of Non-Linear and Non-Gaussian State Space Models
Description: Efficient methods for Bayesian inference of state space models via particle Markov chain Monte Carlo (MCMC) and MCMC based on parallel importance sampling type weighted estimators (Vihola, Helske, and Franks, 2020, <doi:10.1111/sjos.12492>). Gaussian, Poisson, binomial, negative binomial, and Gamma observation densities and basic stochastic volatility models with linear-Gaussian state dynamics, as well as general non-linear Gaussian models and discretised diffusion models are supported.
Author: Jouni Helske [aut, cre] (<https://orcid.org/0000-0001-7130-793X>), Matti Vihola [aut] (<https://orcid.org/0000-0002-8041-7222>)
Maintainer: Jouni Helske <jouni.helske@iki.fi>

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New package BayesOrdDesign with initial version 0.1.0
Package: BayesOrdDesign
Title: Bayesian Group Sequential Design for Ordinal Data
Version: 0.1.0
Maintainer: Chengxue Zhong <chengxue.zhong@uth.tmc.edu>
Description: The proposed group-sequential trial design is based on Bayesian methods for ordinal endpoints, including three methods, the proportional-odds-model (PO)-based, non-proportional-odds-model (NPO)-based, and PO/NPO switch-model-based designs, which makes our proposed methods generic to be able to deal with various scenarios. Richard J. Barker, William A. Link (2013) <doi:10.1080/00031305.2013.791644>. Thomas A. Murray, Ying Yuan, Peter F. Thall, Joan H. Elizondo, Wayne L.Hofstetter (2018) <doi:10.1111/biom.12842>. Chengxue Zhong, Haitao Pan, Hongyu Miao (2021) <arXiv:2108.06568>.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: ordinal, schoolmath, tidyverse, fda, coda, gsDesign, superdiag, ggplot2, madness, rjmcmc, R2jags, rjags, methods
Depends: R (>= 2.10)
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2021-09-20 18:22:27 UTC; czhong
Author: Chengxue Zhong [aut, cre], Haitao Pan [aut], Hongyu Miao [aut]
Repository: CRAN
Date/Publication: 2021-09-21 13:40:02 UTC

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Package MXM updated to version 1.5.2 with previous version 1.5.1 dated 2021-02-23

Title: Feature Selection (Including Multiple Solutions) and Bayesian Networks
Description: Many feature selection methods for a wide range of response variables, including minimal, statistically-equivalent and equally-predictive feature subsets. Bayesian network algorithms and related functions are also included. The package name 'MXM' stands for "Mens eX Machina", meaning "Mind from the Machine" in Latin. References: a) Lagani, V. and Athineou, G. and Farcomeni, A. and Tsagris, M. and Tsamardinos, I. (2017). Feature Selection with the R Package MXM: Discovering Statistically Equivalent Feature Subsets. Journal of Statistical Software, 80(7). <doi:10.18637/jss.v080.i07>. b) Tsagris, M., Lagani, V. and Tsamardinos, I. (2018). Feature selection for high-dimensional temporal data. BMC Bioinformatics, 19:17. <doi:10.1186/s12859-018-2023-7>. c) Tsagris, M., Borboudakis, G., Lagani, V. and Tsamardinos, I. (2018). Constraint-based causal discovery with mixed data. International Journal of Data Science and Analytics, 6(1): 19-30. <doi:10.1007/s41060-018-0097-y>. d) Tsagris, M., Papadovasilakis, Z., Lakiotaki, K. and Tsamardinos, I. (2018). Efficient feature selection on gene expression data: Which algorithm to use? BioRxiv. <doi:10.1101/431734>. e) Tsagris, M. (2019). Bayesian Network Learning with the PC Algorithm: An Improved and Correct Variation. Applied Artificial Intelligence, 33(2):101-123. <doi:10.1080/08839514.2018.1526760>. f) Tsagris, M. and Tsamardinos, I. (2019). Feature selection with the R package MXM. F1000Research 7: 1505. <doi:10.12688/f1000research.16216.2>. g) Borboudakis, G. and Tsamardinos, I. (2019). Forward-Backward Selection with Early Dropping. Journal of Machine Learning Research 20: 1-39. h) The gamma-OMP algorithm for feature selection with application to gene expression data. IEEE/ACM Transactions on Computational Biology and Bioinformatics (Accepted for publication) <doi:10.1109/TCBB.2020.3029952>.
Author: Michail Tsagris [aut, cre], Ioannis Tsamardinos [aut, cph], Vincenzo Lagani [aut, cph], Giorgos Athineou [aut], Giorgos Borboudakis [ctb], Anna Roumpelaki [ctb]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

Diff between MXM versions 1.5.1 dated 2021-02-23 and 1.5.2 dated 2021-09-21

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Package survivoR updated to version 0.9.4 with previous version 0.9.3 dated 2021-05-11

Title: Data from all Seasons of Survivor (US) TV Series in Tidy Format
Description: Several datasets which detail the results and events of each season of Survivor. This includes details on the cast, voting history, immunity and reward challenges, jury votes and viewers. This data is useful for practicing data wrangling, graph analytics and analysing how each season of Survivor played out. Includes 'ggplot2' scales and colour palettes for visualisation.
Author: Daniel Oehm [aut, cre]
Maintainer: Daniel Oehm <danieloehm@gmail.com>

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Package plm updated to version 2.4-2 with previous version 2.4-1 dated 2021-03-02

Title: Linear Models for Panel Data
Description: A set of estimators and tests for panel data econometrics, as described in Baltagi (2021), Econometric Analysis of Panel Data, ISBN-13:978-3-030-53952-8, Hsiao (2014), Analysis of Panel Data <doi:10.1017/CBO9781139839327>, and Croissant and Millo (2018), Panel Data Econometrics with R, ISBN-13:978-1-118-94918-4.
Author: Yves Croissant [aut, cre], Giovanni Millo [aut], Kevin Tappe [aut], Ott Toomet [ctb], Christian Kleiber [ctb], Achim Zeileis [ctb], Arne Henningsen [ctb], Liviu Andronic [ctb], Nina Schoenfelder [ctb]
Maintainer: Yves Croissant <yves.croissant@univ-reunion.fr>

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Package litteR updated to version 0.9.1 with previous version 0.9.0 dated 2021-09-08

Title: Litter Analysis
Description: Data sets on various litter types like beach litter, riverain litter, floating litter, and seafloor litter are rapidly growing. This package offers a simple user interface to analyse these litter data in a consistent and reproducible way. It also provides functions to facilitate several kinds of litter analysis, e.g., trend analysis, power analysis, and baseline analysis. Under the hood, these functions are also used by the user interface. See Schulz et al. (2019) <doi:10.1016/j.envpol.2019.02.030> for details. MS-Windows users are advised to run 'litteR' in 'RStudio'. See our vignette: Installation manual for 'RStudio' and 'litteR'.
Author: Dennis Walvoort [aut, cre, cph], Willem van Loon [aut, cph], Rijkswaterstaat - The Netherlands [cph, fnd, dtc]
Maintainer: Dennis Walvoort <dennis.Walvoort@wur.nl>

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Package fundiversity updated to version 0.2.1 with previous version 0.2.0 dated 2021-05-14

Title: Easy Computation of Alpha Functional Diversity Indices
Description: Computes 5 alpha-functional diversity indices: Functional Divergence (FDiv), Function Evenness (FEve), Functional Richness (FRic), Functional Dispersion (FDis) and Rao's entropy (Q) (reviewed in Villéger et al. 2008 <doi:10.1890/07-1206.1>). Provides efficient and modular functions to compute functional diversity indices.
Author: Matthias Grenié [aut, cre] (<https://orcid.org/0000-0002-4659-7522>), Hugo Gruson [aut] (<https://orcid.org/0000-0002-4094-1476>)
Maintainer: Matthias Grenié <matthias.grenie@gmail.com>

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Package Microsoft365R updated to version 2.3.1 with previous version 2.3.0 dated 2021-08-12

Title: Interface to the 'Microsoft 365' Suite of Cloud Services
Description: An interface to the 'Microsoft 365' (formerly known as 'Office 365') suite of cloud services, building on the framework supplied by the 'AzureGraph' package. Enables access from R to data stored in 'Teams', 'SharePoint Online' and 'OneDrive', including the ability to list drive folder contents, upload and download files, send messages, and retrieve data lists. Also provides a full-featured 'Outlook' email client, with the ability to send emails and manage emails and mail folders.
Author: Hong Ooi [aut, cre], Roman Zenka [ctb], Robert Ashton [ctb], Microsoft [cph]
Maintainer: Hong Ooi <hongooi73@gmail.com>

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Package Unicode updated to version 14.0.0-1 with previous version 13.0.0-2 dated 2020-12-03

Title: Unicode Data and Utilities
Description: Data from Unicode 14.0.0 and related utilities.
Author: Kurt Hornik [aut, cre] (<https://orcid.org/0000-0003-4198-9911>)
Maintainer: Kurt Hornik <Kurt.Hornik@R-project.org>

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Package rstudio.prefs updated to version 0.1.7 with previous version 0.1.6 dated 2021-09-20

Title: Set 'RStudio' Preferences
Description: As of 'RStudio' v1.3, the preferences in the Global Options dialog (and a number of other preferences that aren’t) are now saved in simple, plain-text JSON files. This package provides an interface for working with these 'RStudio' JSON preference files to easily make modifications without using the point-and-click option menus. This is particularly helpful when working on teams to ensure a unified experience across machines and utilizing settings for best practices.
Author: Daniel D. Sjoberg [aut, cre, cph] (<https://orcid.org/0000-0003-0862-2018>)
Maintainer: Daniel D. Sjoberg <danield.sjoberg@gmail.com>

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Package AlphaPart updated to version 0.8.2 with previous version 0.8.1 dated 2020-03-25

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 [aut, cre] (<https://orcid.org/0000-0001-8008-2787>), Jana Obsteter [aut] (<https://orcid.org/0000-0003-1511-3916>), Thiago de Paula Oliveira [aut] (<https://orcid.org/0000-0002-4555-2584>)
Maintainer: Gregor Gorjanc <gregor.gorjanc@roslin.ed.ac.uk>

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Package csodata (with last version 1.2.0) was removed from CRAN

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

2021-06-07 1.2.0
2020-12-17 1.1.1

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Package klassR (with last version 0.1.5) was removed from CRAN

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

2021-03-30 0.1.5

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Package DesignCTPB updated to version 1.1.3 with previous version 1.1.1 dated 2021-04-05

Title: Design Clinical Trials with Potential Biomarker Effect
Description: Applying 'CUDA' 'GPUs' via 'Numba' for optimal clinical design. It allows the user to utilize a 'reticulate' 'Python' environment and run intensive Monte Carlo simulation to get the optimal cutoff for the clinical design with potential biomarker effect, which can guide the realistic clinical trials.
Author: Yitao Lu [aut, cre] (<https://orcid.org/0000-0002-0523-7416>), Belaid Moa [aut], Julie Zhou [aut], Li Xing [aut] (<https://orcid.org/0000-0002-4186-7909>), Xuekui Zhang [aut] (<https://orcid.org/0000-0003-4728-2343>)
Maintainer: Yitao Lu <yitaolu@uvic.ca>

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Package bamlss updated to version 1.1-5 with previous version 1.1-4 dated 2021-05-15

Title: Bayesian Additive Models for Location, Scale, and Shape (and Beyond)
Description: Infrastructure for estimating probabilistic distributional regression models in a Bayesian framework. The distribution parameters may capture location, scale, shape, etc. and every parameter may depend on complex additive terms (fixed, random, smooth, spatial, etc.) similar to a generalized additive model. The conceptual and computational framework is introduced in Umlauf, Klein, Zeileis (2019) <doi:10.1080/10618600.2017.1407325> and the R package in Umlauf, Klein, Simon, Zeileis (2019) <arXiv:1909.11784>.
Author: Nikolaus Umlauf [aut, cre] (<https://orcid.org/0000-0003-2160-9803>), Nadja Klein [aut] (<https://orcid.org/0000-0002-5072-5347>), Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>), Meike Koehler [ctb], Thorsten Simon [aut] (<https://orcid.org/0000-0002-3778-7738>), Stanislaus Stadlmann [ctb]
Maintainer: Nikolaus Umlauf <Nikolaus.Umlauf@uibk.ac.at>

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Package rasterKernelEstimates updated to version 1.0.2 with previous version 1.0.1 dated 2016-08-04

Title: Kernel Based Estimates on in-Memory Raster Images
Description: Performs kernel based estimates on in-memory raster images from the raster package. These kernel estimates include local means variances, modes, and quantiles. All results are in the form of raster images, preserving original resolution and projection attributes.
Author: Jonathan Lisic [aut, cre]
Maintainer: Jonathan Lisic <jlisic@gmail.com>

Diff between rasterKernelEstimates versions 1.0.1 dated 2016-08-04 and 1.0.2 dated 2021-09-21

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Package qrNLMM updated to version 3.0 with previous version 2.2 dated 2021-06-17

Title: Quantile Regression for Nonlinear Mixed-Effects Models
Description: Quantile regression (QR) for Nonlinear Mixed-Effects Models via the asymmetric Laplace distribution (ALD). It uses the Stochastic Approximation of the EM (SAEM) algorithm for deriving exact maximum likelihood estimates and full inference results for the fixed-effects and variance components. It also provides prediction and graphical summaries for assessing the algorithm convergence and fitting results.
Author: Christian E. Galarza <chedgala@espol.edu.ec> and Victor H. Lachos <hlachos@uconn.edu>
Maintainer: Christian E. Galarza <cgalarza88@gmail.com>

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Package praznik updated to version 9.0.0 with previous version 8.0.0 dated 2020-02-29

Title: Tools for Information-Based Feature Selection
Description: A toolbox of fast, native and parallel implementations of various information-based importance criteria estimators and feature selection filters based on them, inspired by the overview by Brown, Pocock, Zhao and Lujan (2012) <https://www.jmlr.org/papers/v13/brown12a.html>. Contains, among other, minimum redundancy maximal relevancy ('mRMR') method by Peng, Long and Ding (2005) <doi:10.1109/TPAMI.2005.159>; joint mutual information ('JMI') method by Yang and Moody (1999) <https://papers.nips.cc/paper/1779-data-visualization-and-feature-selection-new-algorithms-for-nongaussian-data>; double input symmetrical relevance ('DISR') method by Meyer and Bontempi (2006) <doi:10.1007/11732242_9> as well as joint mutual information maximisation ('JMIM') method by Bennasar, Hicks and Setchi (2015) <doi:10.1016/j.eswa.2015.07.007>.
Author: Miron B. Kursa [aut, cre] (<https://orcid.org/0000-0001-7672-648X>)
Maintainer: Miron B. Kursa <m@mbq.me>

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Package Numero updated to version 1.8.4 with previous version 1.8.2 dated 2021-07-20

Title: Statistical Framework to Define Subgroups in Complex Datasets
Description: High-dimensional datasets that do not exhibit a clear intrinsic clustered structure pose a challenge to conventional clustering algorithms. For this reason, we developed an unsupervised framework that helps scientists to better subgroup their datasets based on visual cues, please see Gao S, Mutter S, Casey A, Makinen V-P (2019) Numero: a statistical framework to define multivariable subgroups in complex population-based datasets, Int J Epidemiology, 48:369-37, <doi:10.1093/ije/dyy113>. The framework includes the necessary functions to construct a self-organizing map of the data, to evaluate the statistical significance of the observed data patterns, and to visualize the results.
Author: Song Gao [aut], Stefan Mutter [aut], Aaron E. Casey [aut], Ville-Petteri Makinen [aut, cre]
Maintainer: Ville-Petteri Makinen <vpmakine@gmail.com>

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 Numero-1.8.4/Numero/src/nro_kohonen.cpp                     |    2 
 Numero-1.8.4/Numero/src/nro_label.cpp                       |    2 
 Numero-1.8.4/Numero/src/nro_match.cpp                       |    2 
 Numero-1.8.4/Numero/src/nro_permute.cpp                     |    2 
 Numero-1.8.4/Numero/src/nro_train.cpp                       |    8 
 Numero-1.8.4/Numero/src/nro_webpage.cpp                     |    2 
 Numero-1.8.4/Numero/src/punos.h                             |    2 
 Numero-1.8.4/Numero/src/punos.local.h                       |    2 
 Numero-1.8.4/Numero/src/punos.smoothen.cpp                  |    2 
 Numero-1.8.4/Numero/src/punos.topology.cpp                  |    2 
 Numero-1.8.4/Numero/src/punos.topology.depth.cpp            |    2 
 Numero-1.8.4/Numero/src/punos.topology.diffuse.cpp          |    2 
 Numero-1.8.4/Numero/src/punos.topology.distance.cpp         |    2 
 Numero-1.8.4/Numero/src/punos.topology.highlight.cpp        |    2 
 Numero-1.8.4/Numero/src/punos.topology.import.cpp           |    2 
 Numero-1.8.4/Numero/src/punos.topology.interpolate.cpp      |    2 
 Numero-1.8.4/Numero/src/punos.topology.levels.cpp           |    2 
 Numero-1.8.4/Numero/src/punos.topology.neighbors.cpp        |    2 
 Numero-1.8.4/Numero/src/punos.topology.operator[].cpp       |    2 
 Numero-1.8.4/Numero/src/punos.topology.paint.cpp            |    2 
 Numero-1.8.4/Numero/src/punos.topology.radius.cpp           |    2 
 Numero-1.8.4/Numero/src/punos.topology.rewire.cpp           |    2 
 Numero-1.8.4/Numero/src/punos.topology.save.cpp             |    2 
 Numero-1.8.4/Numero/src/punos.topology.sigma.cpp            |    2 
 Numero-1.8.4/Numero/src/punos.topology.size.cpp             |    2 
 Numero-1.8.4/Numero/src/punos.topology.stratify.cpp         |    2 
 Numero-1.8.4/Numero/src/punos.topology.weight.cpp           |    2 
 Numero-1.8.4/Numero/src/punos.topology.write.cpp            |    2 
 Numero-1.8.4/Numero/src/punos.version.cpp                   |    2 
 Numero-1.8.4/Numero/src/scriptum.artist.background.cpp      |    2 
 Numero-1.8.4/Numero/src/scriptum.artist.close.cpp           |    2 
 Numero-1.8.4/Numero/src/scriptum.artist.cpp                 |    2 
 Numero-1.8.4/Numero/src/scriptum.artist.group.cpp           |    2 
 Numero-1.8.4/Numero/src/scriptum.artist.horizontal.cpp      |    2 
 Numero-1.8.4/Numero/src/scriptum.artist.paint.cpp           |    2 
 Numero-1.8.4/Numero/src/scriptum.artist.vertical.cpp        |    2 
 Numero-1.8.4/Numero/src/scriptum.artistbuffer.prolog.cpp    |    2 
 Numero-1.8.4/Numero/src/scriptum.color.cpp                  |    2 
 Numero-1.8.4/Numero/src/scriptum.colorize.cpp               |    2 
 Numero-1.8.4/Numero/src/scriptum.colormap.cpp               |    2 
 Numero-1.8.4/Numero/src/scriptum.frame.box.cpp              |    2 
 Numero-1.8.4/Numero/src/scriptum.frame.cpp                  |    2 
 Numero-1.8.4/Numero/src/scriptum.frame.curve.cpp            |    2 
 Numero-1.8.4/Numero/src/scriptum.frame.flush.cpp            |    2 
 Numero-1.8.4/Numero/src/scriptum.frame.group.cpp            |    2 
 Numero-1.8.4/Numero/src/scriptum.frame.horizontal.cpp       |    2 
 Numero-1.8.4/Numero/src/scriptum.frame.shape.cpp            |    2 
 Numero-1.8.4/Numero/src/scriptum.frame.shapes.cpp           |    2 
 Numero-1.8.4/Numero/src/scriptum.frame.slice.cpp            |    2 
 Numero-1.8.4/Numero/src/scriptum.frame.style.cpp            |    2 
 Numero-1.8.4/Numero/src/scriptum.frame.stylize.cpp          |    2 
 Numero-1.8.4/Numero/src/scriptum.frame.text.cpp             |    2 
 Numero-1.8.4/Numero/src/scriptum.frame.vertical.cpp         |    2 
 Numero-1.8.4/Numero/src/scriptum.framebuffer.cpp            |    2 
 Numero-1.8.4/Numero/src/scriptum.h                          |    2 
 Numero-1.8.4/Numero/src/scriptum.limes.cpp                  |    2 
 Numero-1.8.4/Numero/src/scriptum.local.h                    |    2 
 Numero-1.8.4/Numero/src/scriptum.style.cpp                  |    2 
 Numero-1.8.4/Numero/src/scriptum.style2code.cpp             |    2 
 Numero-1.8.4/Numero/src/scriptum.version.cpp                |    2 
 210 files changed, 644 insertions(+), 635 deletions(-)

More information about Numero at CRAN
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Package meanShiftR updated to version 0.56 with previous version 0.53 dated 2018-12-03

Title: A Computationally Efficient Mean Shift Implementation
Description: Performs mean shift classification using linear and k-d tree based nearest neighbor implementations for the Gaussian, Epanechnikov, and biweight product kernels.
Author: Jonathan Lisic [aut, cre]
Maintainer: Jonathan Lisic <jlisic@gmail.com>

Diff between meanShiftR versions 0.53 dated 2018-12-03 and 0.56 dated 2021-09-21

 DESCRIPTION     |    8 ++++----
 MD5             |    8 ++++----
 src/init.c      |    7 ++++---
 src/meanShift.c |    9 +++++----
 src/meanShift.h |    7 ++++---
 5 files changed, 21 insertions(+), 18 deletions(-)

More information about meanShiftR at CRAN
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