Fri, 08 Oct 2021

Package wordpiece.data updated to version 1.0.2 with previous version 1.0.1 dated 2021-09-28

Title: Data for Wordpiece-Style Tokenization
Description: Provides data to be used by the wordpiece algorithm in order to tokenize text into somewhat meaningful chunks. Included vocabularies were retrieved from <https://huggingface.co/bert-base-cased/resolve/main/vocab.txt> and <https://huggingface.co/bert-base-uncased/resolve/main/vocab.txt> and parsed into an R-friendly format.
Author: Jonathan Bratt [aut] (<https://orcid.org/0000-0003-2859-0076>), Jon Harmon [aut, cre] (<https://orcid.org/0000-0003-4781-4346>), Bedford Freeman & Worth Pub Grp LLC DBA Macmillan Learning [cph], Google, Inc [cph] (original BERT vocabularies)
Maintainer: Jon Harmon <jonthegeek@gmail.com>

Diff between wordpiece.data versions 1.0.1 dated 2021-09-28 and 1.0.2 dated 2021-10-08

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Package PReMiuM updated to version 3.2.7 with previous version 3.2.6 dated 2021-04-26

Title: Dirichlet Process Bayesian Clustering, Profile Regression
Description: Bayesian clustering using a Dirichlet process mixture model. This model is an alternative to regression models, non-parametrically linking a response vector to covariate data through cluster membership. The package allows Bernoulli, Binomial, Poisson, Normal, survival and categorical response, as well as Normal and discrete covariates. It also allows for fixed effects in the response model, where a spatial CAR (conditional autoregressive) term can be also included. Additionally, predictions may be made for the response, and missing values for the covariates are handled. Several samplers and label switching moves are implemented along with diagnostic tools to assess convergence. A number of R functions for post-processing of the output are also provided. In addition to fitting mixtures, it may additionally be of interest to determine which covariates actively drive the mixture components. This is implemented in the package as variable selection. The main reference for the package is Liverani, Hastie, Azizi, Papathomas and Richardson (2015) <doi:10.18637/jss.v064.i07>.
Author: David I. Hastie, Silvia Liverani <liveranis@gmail.com> and Sylvia Richardson with contributions from Aurore J. Lavigne, Lucy Leigh, Lamiae Azizi, Xi Liu, Ruizhu Huang, Austin Gratton, Wei Jing
Maintainer: Silvia Liverani <liveranis@gmail.com>

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Package MortCast updated to version 2.6-0 with previous version 2.4-0 dated 2021-06-23

Title: Estimation and Projection of Age-Specific Mortality Rates
Description: Age-specific mortality rates are estimated and projected using the Kannisto, Lee-Carter and related methods as described in Sevcikova et al. (2016) <doi:10.1007/978-3-319-26603-9_15>.
Author: Hana Sevcikova, Nan Li and Patrick Gerland
Maintainer: Hana Sevcikova <hanas@uw.edu>

Diff between MortCast versions 2.4-0 dated 2021-06-23 and 2.6-0 dated 2021-10-08

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Package Rnumerai updated to version 2.1.4 with previous version 2.1.3 dated 2021-08-20

Title: Interface to the Numerai Machine Learning Tournament API
Description: Routines to interact with the Numerai Machine Learning Tournament API <https://numer.ai>. The functionality includes the ability to automatically download the current tournament data, submit predictions, and to get information for your user. General 'GraphQL' queries can also be executed.
Author: Omni Analytics Group [aut], Eric Hare [cre]
Maintainer: Eric Hare <eric@omnianalytics.io>

Diff between Rnumerai versions 2.1.3 dated 2021-08-20 and 2.1.4 dated 2021-10-08

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Package optparse updated to version 1.7.1 with previous version 1.6.6 dated 2020-04-16

Title: Command Line Option Parser
Description: A command line parser inspired by Python's 'optparse' library to be used with Rscript to write "#!" shebang scripts that accept short and long flag/options.
Author: Trevor L Davis [aut, cre], Allen Day [ctb] (Some documentation and examples ported from the getopt package.), Python Software Foundation [ctb] (Some documentation from the optparse Python module.), Steve Lianoglou [ctb], Jim Nikelski [ctb], Kirill Müller [ctb], Peter Humburg [ctb], Rich FitzJohn [ctb], Gyu Jin Choi [ctb]
Maintainer: Trevor L Davis <trevor.l.davis@gmail.com>

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Package memisc updated to version 0.99.30.7 with previous version 0.99.27.3 dated 2020-11-18

Title: Management of Survey Data and Presentation of Analysis Results
Description: An infrastructure for the management of survey data including value labels, definable missing values, recoding of variables, production of code books, and import of (subsets of) 'SPSS' and 'Stata' files is provided. Further, the package allows to produce tables and data frames of arbitrary descriptive statistics and (almost) publication-ready tables of regression model estimates, which can be exported to 'LaTeX' and HTML.
Author: Martin Elff (with contributions from Christopher N. Lawrence, Dave Atkins, Jason W. Morgan, Achim Zeileis)
Maintainer: Martin Elff <memisc@elff.eu>

Diff between memisc versions 0.99.27.3 dated 2020-11-18 and 0.99.30.7 dated 2021-10-08

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New package switchboard with initial version 0.1
Package: switchboard
Version: 0.1
Date: 2021-10-8
Title: An Agile Widget Engine for Real-Time, Dynamic Visualizations
Description: An unsorted collection of visualization widgets rendered in 'Tcl/Tk'<https://www.tcl.tk/> to generate agile dashboards for your iterative simulations. Widgets include progress bars, counters, eavesdroppers, injectors, switches, and sliders for dynamic manipulation and visualization of simulation parameters.
Depends: R (>= 3.3.2)
Imports: magrittr
SystemRequirements: Tcl/Tk toolkit (X11 Quarts for Mac)
VignetteBuilder: R.rsp
License: GPL (>= 2)
URL: http://lajeunesse.myweb.usf.edu/ https://github.com/mjlajeunesse/ https://www.youtube.com/c/LajeunesseLab/
Encoding: UTF-8
Suggests: R.rsp
NeedsCompilation: no
Packaged: 2021-10-08 12:35:49 UTC; lajeunesse
Author: Marc J. Lajeunesse [aut, cre] (<https://orcid.org/0000-0002-9678-2080>)
Maintainer: Marc J. Lajeunesse <lajeunesse@usf.edu>
Repository: CRAN
Date/Publication: 2021-10-08 18:00:02 UTC

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New package spm2 with initial version 1.1.0
Package: spm2
Title: Spatial Predictive Modeling
Version: 1.1.0
Date: 2021-10-01
Description: An updated and extended version of 'spm' package, by introducing some further novel functions for modern statistical methods (i.e., generalised linear models, glmnet, generalised least squares), support vector machine, kriging methods (i.e., simple kriging, universal kriging, block kriging, kriging with an external drift), and novel hybrid methods (228 hybrids plus numerous variants) of modern statistical methods or machine learning methods with mathematical and/or univariate geostatistical methods for spatial predictive modelling. For each method, two functions are provided, with one function for assessing the predictive errors and accuracy of the method based on cross-validation, and the other for generating spatial predictions. It also contains a couple of functions for data preparation and predictive accuracy assessment.
Depends: R (>= 2.10)
Imports: spm, gstat, sp, randomForest, psy, gbm, stats, ranger, MASS, nlme, glmnet, e1071
License: GPL (>= 2)
LazyData: true
Encoding: UTF-8
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2021-10-08 06:42:53 UTC; Jin
Author: Jin Li [aut, cre]
Maintainer: Jin Li <jinli68@gmail.com>
Repository: CRAN
Date/Publication: 2021-10-08 17:40:02 UTC

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New package retriever with initial version 0.1.0
Package: retriever
Title: Generate Disease-Specific Response Signatures from the LINCS-L1000 Data
Version: 0.1.0
Description: Generates disease-specific drug-response profiles that are independent of time, concentration, and cell-line. Based on the cell lines used as surrogates, the returned profiles represent the unique transcriptional changes induced by a compound in a given disease.
Depends: R (>= 3.5.0)
Imports: ccdata, pbapply, preprocessCore
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2021-10-08 13:10:52 UTC; danie
Author: Daniel Osorio [aut, cre] (<https://orcid.org/0000-0003-4424-8422>), Marieke Kuijjer [aut] (<https://orcid.org/0000-0001-6280-3130>)
Maintainer: Daniel Osorio <daniecos@uio.no>
Repository: CRAN
Date/Publication: 2021-10-08 18:00:07 UTC

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New package LIC with initial version 0.0.1
Package: LIC
Title: The LIC Criterion for Optimal Subset Selection
Version: 0.0.1
Description: The LIC criterion is to determine the most informative subsets so that the subset can retain most of the information contained in the complete data. The philosophy of the package is described in Guo G. (2020) <doi: 10.1007/s00180-020-00974-4>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: stats
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2021-10-08 08:04:16 UTC; H
Author: Guangbao Guo [aut, cre], Yue Sun [aut], Guoqi Qian [aut], Qian Wang [aut]
Maintainer: Guangbao Guo <ggb11111111@163.com>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2021-10-08 17:50:02 UTC

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New package expDB with initial version 0.1.0
Package: expDB
Title: Database for Experiment Dataset
Version: 0.1.0
Maintainer: Bangyou Zheng <bangyou.zheng@csiro.au>
Description: A SQLite database is designed to store all information of experiment-based data including metadata, experiment design, managements, phenotypic values and climate records. The dataset can be imported from an excel file.
License: MIT + file LICENSE
URL: https://expdb.bangyou.me/, https://github.com/byzheng/expdb
BugReports: https://github.com/byzheng/expdb/issues
Encoding: UTF-8
Imports: DBI, RSQLite, utils, readxl, png, grid, tibble, lubridate, dplyr, methods, weaana (>= 0.1.1), tidyr, tidyverse, magrittr, stats, reshape2, stringr, rlang
Suggests: testthat
NeedsCompilation: no
Packaged: 2021-10-08 05:00:13 UTC; zhe00a
Author: Bangyou Zheng [aut, cre]
Repository: CRAN
Date/Publication: 2021-10-08 17:40:06 UTC

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New package discretefit with initial version 0.0.0
Package: discretefit
Title: Simulated Goodness-of-Fit Tests for Discrete Distributions
Version: 0.0.0
Description: Implements fast, Monte Carlo simulations for goodness-of-fit (GOF) tests for discrete distributions. This includes tests based on the root-mean-square statistic, the Chi-squared statistic, the log-likelihood-ratio statistic (G^2), and the Kolmogorov-Smirnov statistic.
License: MIT + file LICENSE
Encoding: UTF-8
LinkingTo: Rcpp
Imports: Rcpp
Suggests: knitr, dgof, RVAideMemoire, bench, testthat (>= 3.0.0), rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-10-08 06:19:35 UTC; Josh
Author: Josh McCormick [aut, cre]
Maintainer: Josh McCormick <josh.mccormick@aya.yale.edu>
Repository: CRAN
Date/Publication: 2021-10-08 17:40:09 UTC

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Package rglobi (with last version 0.2.25) was removed from CRAN

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

2021-08-12 0.2.25
2021-05-19 0.2.24
2021-04-17 0.2.22
2019-12-06 0.2.21
2019-09-20 0.2.20
2019-04-26 0.2.19
2019-03-28 0.2.18
2018-12-14 0.2.17
2018-03-23 0.2.14
2018-02-28 0.2.13
2018-02-12 0.2.12
2017-10-14 0.2.11
2017-09-19 0.2.10
2016-03-08 0.2.9
2015-05-13 0.2.8
2015-03-17 0.2.6
2015-02-24 0.2.5
2015-01-28 0.2.4

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Package splitSelect updated to version 1.0.2 with previous version 1.0.1 dated 2020-09-01

Title: Best Split Selection Modeling for Low-Dimensional Data
Description: Functions to generate or sample from all possible splits of features or variables into a number of specified groups. Also computes the best split selection estimator (for low-dimensional data) as defined in Christidis, Van Aelst and Zamar (2019) <arXiv:1812.05678>.
Author: Anthony Christidis <anthony.christidis@stat.ubc.ca>, Stefan Van Aelst <stefan.vanaelst@kuleuven.be>, Ruben Zamar <ruben@stat.ubc.ca>
Maintainer: Anthony Christidis <anthony.christidis@stat.ubc.ca>

Diff between splitSelect versions 1.0.1 dated 2020-09-01 and 1.0.2 dated 2021-10-08

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Package movMF updated to version 0.2-6 with previous version 0.2-5 dated 2020-10-12

Title: Mixtures of von Mises-Fisher Distributions
Description: Fit and simulate mixtures of von Mises-Fisher distributions.
Author: Kurt Hornik [aut, cre] (<https://orcid.org/0000-0003-4198-9911>), Bettina Grün [aut] (<https://orcid.org/0000-0001-7265-4773>)
Maintainer: Kurt Hornik <Kurt.Hornik@R-project.org>

Diff between movMF versions 0.2-5 dated 2020-10-12 and 0.2-6 dated 2021-10-08

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Package stationery updated to version 1.0 with previous version 0.98.30 dated 2020-04-28

Title: Working Examples for Reproducible Research Documents
Description: Templates, guides, and scripts for writing documents in 'LaTeX' and 'R markdown' to produce guides, slides, and reports. Special care is taken to illustrate use of templates and customization opportunities. Challenges and opportunities of 'HTML' output from 'R markdown' receive special attention. Includes several vignettes to assist new users of literate programming.
Author: Paul Johnson [aut, cre], Brent Kaplan [ctb], Meghan Sullivan [ctb], Charles Redmon [ctb], Zack Roman [ctb], Chong Xing [ctb], Longcan 'Emma' Huang [ctb], Garrett Mills [ctb]
Maintainer: Paul Johnson <pauljohn@ku.edu>

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Package labelVector updated to version 0.1.2 with previous version 0.1.1 dated 2020-02-17

Title: Label Attributes for Atomic Vectors
Description: Labels are a common construct in statistical software providing a human readable description of a variable. While variable names are succinct, quick to type, and follow a language's naming conventions, labels may be more illustrative and may use plain text and spaces. R does not provide native support for labels. Some packages, however, have made this feature available. Most notably, the 'Hmisc' package provides labelling methods for a number of different object. Due to design decisions, these methods are not all exported, and so are unavailable for use in package development. The 'labelVector' package supports labels for atomic vectors in a light-weight design that is suitable for use in other packages.
Author: Benjamin Nutter [aut, cre]
Maintainer: Benjamin Nutter <benjamin.nutter@gmail.com>

Diff between labelVector versions 0.1.1 dated 2020-02-17 and 0.1.2 dated 2021-10-08

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Package interval updated to version 1.1-0.8 with previous version 1.1-0.7 dated 2020-09-24

Title: Weighted Logrank Tests and NPMLE for Interval Censored Data
Description: Functions to fit nonparametric survival curves, plot them, and perform logrank or Wilcoxon type tests [see Fay and Shaw <doi:10.18637/jss.v036.i02>].
Author: Michael P. Fay
Maintainer: Michael P. Fay <mfay@niaid.nih.gov>

Diff between interval versions 1.1-0.7 dated 2020-09-24 and 1.1-0.8 dated 2021-10-08

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Package rassta (with last version 1.0.0) was removed from CRAN

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

2021-09-22 1.0.0

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Package pexm updated to version 1.0.1 with previous version 1.0.0 dated 2020-07-06

Title: Loading a JAGS Module for the Piecewise Exponential Distribution
Description: Load the Just Another Gibbs Sampling (JAGS) module 'pexm'. The module provides the tools to work with the Piecewise Exponential (PE) distribution in a Bayesian model with the corresponding Markov Chain Monte Carlo algorithm (Gibbs Sampling) implemented via JAGS. Details about the module implementation can be found in Mayrink et al. (2020) <arXiv:2004.12359>.
Author: Vinicius Mayrink [aut, cre] (<https://orcid.org/0000-0002-5683-8326>), Joao Duarte [aut], Fabio Demarqui [ctb] (<https://orcid.org/0000-0001-9236-1986>)
Maintainer: Vinicius Mayrink <vdinizm@gmail.com>

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Package corels updated to version 0.0.3 with previous version 0.0.2 dated 2020-06-05

Title: R Binding for the 'Certifiably Optimal RulE ListS (Corels)' Learner
Description: The 'Certifiably Optimal RulE ListS (Corels)' learner by Angelino et al described in <arXiv:1704.01701> provides interpretable decision rules with an optimality guarantee, and is made available to R with this package. See the file 'AUTHORS' for a list of copyright holders and contributors.
Author: Dirk Eddelbuettel
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package staRdom updated to version 1.1.23 with previous version 1.1.21 dated 2021-04-20

Title: PARAFAC Analysis of EEMs from DOM
Description: This is a user-friendly way to run a parallel factor (PARAFAC) analysis (Harshman, 1971) <doi:10.1121/1.1977523> on excitation emission matrix (EEM) data from dissolved organic matter (DOM) samples (Murphy et al., 2013) <doi:10.1039/c3ay41160e>. The analysis includes profound methods for model validation. Some additional functions allow the calculation of absorbance slope parameters and create beautiful plots.
Author: Matthias Pucher [aut, cre], Daniel Graeber [aut, ctb], Stefan Preiner [ctb], Renata Pinto [ctb]
Maintainer: Matthias Pucher <matthias.pucher@wcl.ac.at>

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Package fairmodels updated to version 1.2.0 with previous version 1.1.0 dated 2021-05-31

Title: Flexible Tool for Bias Detection, Visualization, and Mitigation
Description: Measure fairness metrics in one place for many models. Check how big is model's bias towards different races, sex, nationalities etc. Use measures such as Statistical Parity, Equal odds to detect the discrimination against unprivileged groups. Visualize the bias using heatmap, radar plot, biplot, bar chart (and more!). There are various pre-processing and post-processing bias mitigation algorithms implemented. Package also supports calculating fairness metrics for regression models. Find more details in (Wiśniewski, Biecek (2021)) <arXiv:2104.00507>.
Author: Jakub Wiśniewski [aut, cre], Przemysław Biecek [aut] (<https://orcid.org/0000-0001-8423-1823>)
Maintainer: Jakub Wiśniewski <jakwisn@gmail.com>

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Package SplitSoftening updated to version 2.1-0 with previous version 2.0-1 dated 2020-03-10

Title: Softening Splits in Decision Trees
Description: Allows to produce and use classification trees with soft (probability) splits, as described in: Dvořák, J. (2019), <doi:10.1007/s00180-019-00867-1>.
Author: Jakub Dvorak
Maintainer: Jakub Dvorak <JakubDvorak@email.cz>

Diff between SplitSoftening versions 2.0-1 dated 2020-03-10 and 2.1-0 dated 2021-10-08

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New package CoMiRe with initial version 0.7.1
Package: CoMiRe
Title: Convex Mixture Regression
Version: 0.7.1
Date: 2021-10-08
Author: Antonio Canale [aut, cre], Daniele Durante [ctb], Arianna Falcioni [aut], Luisa Galtarossa [aut], Tommaso Rigon [ctb]
Maintainer: Antonio Canale <canale@stat.unipd.it>
Description: Posterior inference under the convex mixture regression (CoMiRe) models introduced by Canale, Durante, and Dunson (2018) <doi:10.1111/biom.12917>.
License: GPL-2
NeedsCompilation: yes
Imports: Rcpp (>= 1.0.5), KernSmooth, NonpModelCheck, ggplot2, gtools, mvtnorm, splines2 (>= 0.3.1), truncnorm, rlang
Depends: R (>= 4.0)
LinkingTo: RcppArmadillo, Rcpp (>= 1.0.5)
Encoding: UTF-8
Packaged: 2021-10-08 10:06:03 UTC; tony
Repository: CRAN
Date/Publication: 2021-10-08 10:50:02 UTC

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Package Ternary updated to version 1.2.3 with previous version 1.2.2 dated 2021-05-12

Title: Create Ternary Plots
Description: Plots ternary diagrams (simplex plots / Gibbs triangles) using the standard graphics functions. An alternative to 'ggtern', which uses the 'ggplot2' family of plotting functions. Includes a 'Shiny' user interface for point-and-click plotting.
Author: Martin R. Smith [aut, cre, cph] (<https://orcid.org/0000-0001-5660-1727>), Lilian Sanselme [ctb]
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>

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Package sdcLog updated to version 0.4.0 with previous version 0.3.0 dated 2021-07-22

Title: Tools for Statistical Disclosure Control in Research Data Centers
Description: Tools for researchers to explicitly show that their results comply to rules for statistical disclosure control imposed by research data centers. These tools help in checking descriptive statistics and models and in calculating extreme values that are not individual data. Also included is a simple function to create log files. The methods used here are described in the "Guidelines for the checking of output based on microdata research" by Bond, Brandt, and de Wolf (2015) <https://ec.europa.eu/eurostat/cros/system/files/dwb_standalone-document_output-checking-guidelines.pdf>.
Author: Matthias Gomolka [aut, cre], Tim Becker [aut], Pantelis Karapanagiotis [ctb]
Maintainer: Matthias Gomolka <matthias.gomolka@posteo.de>

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Package mvtnorm updated to version 1.1-3 with previous version 1.1-2 dated 2021-06-07

Title: Multivariate Normal and t Distributions
Description: Computes multivariate normal and t probabilities, quantiles, random deviates and densities.
Author: Alan Genz [aut], Frank Bretz [aut], Tetsuhisa Miwa [aut], Xuefei Mi [aut], Friedrich Leisch [ctb], Fabian Scheipl [ctb], Bjoern Bornkamp [ctb] (<https://orcid.org/0000-0002-6294-8185>), Martin Maechler [ctb] (<https://orcid.org/0000-0002-8685-9910>), Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between mvtnorm versions 1.1-2 dated 2021-06-07 and 1.1-3 dated 2021-10-08

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New package digitalDLSorteR with initial version 0.1.0
Package: digitalDLSorteR
Title: Deconvolution of Bulk RNA-Seq Data Based on Deep Learning
Version: 0.1.0
Maintainer: Diego Mañanes <dmananesc@cnic.es>
Description: Deconvolution of bulk RNA-Seq data using context-specific deconvolution models based on Deep Neural Networks using scRNA-Seq data as input. These models are able to make accurate estimates of the cell composition of bulk RNA-Seq samples from the same context using the advances provided by Deep Learning and the meaningful information provided by scRNA-Seq data. See Torroja and Sanchez-Cabo (2017) <doi:10.3389/fgene.2019.00978> for more details.
License: GPL-3
URL: https://diegommcc.github.io/digitalDLSorteR/, https://github.com/diegommcc/digitalDLSorteR
BugReports: https://github.com/diegommcc/digitalDLSorteR/issues
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: rlang, Matrix, Matrix.utils, methods, tidyr, SingleCellExperiment, SummarizedExperiment, splatter, zinbwave, stats, pbapply, S4Vectors, dplyr, tools, reshape2, gtools, edgeR, reticulate, keras, tensorflow, ggplot2, ggpubr, RColorBrewer
Suggests: knitr, rmarkdown, BiocParallel, rhdf5, DelayedArray, DelayedMatrixStats, HDF5Array, testthat
SystemRequirements: Python (>= 2.7.0), TensorFlow (https://www.tensorflow.org/)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-10-08 07:35:44 UTC; diegommcc
Author: Diego Mañanes [aut, cre] (<https://orcid.org/0000-0001-7247-6794>), Carlos Torroja [aut] (<https://orcid.org/0000-0001-8914-3400>), Fatima Sanchez-Cabo [aut] (<https://orcid.org/0000-0003-1881-1664>)
Repository: CRAN
Date/Publication: 2021-10-08 09:50:05 UTC

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Package RNAsmc (with last version 0.6.0) was removed from CRAN

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

2020-03-28 0.6.0
2020-03-24 0.5.0
2018-12-11 0.4.0
2018-03-19 0.3.0
2018-03-12 0.2.0
2017-08-23 0.1.0

Permanent link
New package SC.MEB with initial version 1.1
Package: SC.MEB
Title: Spatial Clustering with Hidden Markov Random Field using Empirical Bayes
Version: 1.1
Date: 2021-09-30
Description: Spatial clustering with hidden markov random field fitted via EM algorithm, details of which can be found in Yi Yang (2021) <doi:10.1101/2021.06.05.447181>. It is not only computationally efficient and scalable to the sample size increment, but also is capable of choosing the smoothness parameter and the number of clusters as well.
License: GPL-3
Depends: mclust,parallel,ggplot2, Matrix, R (>= 3.5)
Imports: Rcpp (>= 1.0.6), SingleCellExperiment, purrr,BiocSingular, SummarizedExperiment, scater, scran, S4Vectors
LinkingTo: Rcpp, RcppArmadillo
VignetteBuilder: knitr
Suggests: knitr, rmarkdown
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2021-10-06 14:54:38 UTC; yygao
Author: Yi Yang [aut, cre], Xingjie Shi [aut], Jin Liu [aut]
Maintainer: Yi Yang <yygaosansiban@sina.com>
Repository: CRAN
Date/Publication: 2021-10-08 08:40:21 UTC

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Package melt updated to version 1.0.1 with previous version 1.0.0 dated 2021-09-29

Title: Multiple Empirical Likelihood Tests
Description: Multiple hypothesis testing via empirical likelihood in general block designs. It provides asymptotic generalized family-wise error rate control.
Author: Eunseop Kim [aut, cre]
Maintainer: Eunseop Kim <kim.7302@osu.edu>

Diff between melt versions 1.0.0 dated 2021-09-29 and 1.0.1 dated 2021-10-08

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Package lasso2 updated to version 1.2-22 with previous version 1.2-21.1 dated 2020-09-22

Title: L1 Constrained Estimation aka `lasso'
Description: Routines and documentation for solving regression problems while imposing an L1 constraint on the estimates, based on the algorithm of Osborne et al. (1998).
Author: Justin Lokhorst, Bill Venables and Berwin Turlach; port to R, tests etc: Martin Maechler <maechler@stat.math.ethz.ch>
Maintainer: Berwin Turlach <Berwin.Turlach@gmail.com>

Diff between lasso2 versions 1.2-21.1 dated 2020-09-22 and 1.2-22 dated 2021-10-08

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New package kdtools with initial version 0.6.0
Package: kdtools
Title: Tools for Working with Multidimensional Data
Version: 0.6.0
Description: Provides various tools for working with multidimensional data in R and C++, including extremely fast nearest-neighbor- and range- queries without the overhead of linked tree nodes.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: Rcpp (>= 0.12.14)
LinkingTo: Rcpp
Suggests: testthat, knitr, markdown, rmarkdown, covr, ggplot2, tidytext, printr, scales, BH, sf
VignetteBuilder: knitr
SystemRequirements: A compiler that conforms to the C++17 standard
URL: https://github.com/thk686/kdtools
BugReports: https://github.com/thk686/kdtools/issues
Biarch: true
NeedsCompilation: yes
Packaged: 2021-10-07 05:04:19 UTC; tkeitt
Author: Timothy Keitt [aut, cre]
Maintainer: Timothy Keitt <tkeitt@gmail.com>
Repository: CRAN
Date/Publication: 2021-10-08 08:30:02 UTC

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Package IMIFA updated to version 2.1.7 with previous version 2.1.6 dated 2021-05-24

Title: Infinite Mixtures of Infinite Factor Analysers and Related Models
Description: Provides flexible Bayesian estimation of Infinite Mixtures of Infinite Factor Analysers and related models, for nonparametrically clustering high-dimensional data, introduced by Murphy et al. (2020) <doi:10.1214/19-BA1179>. The IMIFA model conducts Bayesian nonparametric model-based clustering with factor analytic covariance structures without recourse to model selection criteria to choose the number of clusters or cluster-specific latent factors, mostly via efficient Gibbs updates. Model-specific diagnostic tools are also provided, as well as many options for plotting results, conducting posterior inference on parameters of interest, posterior predictive checking, and quantifying uncertainty.
Author: Keefe Murphy [aut, cre] (<https://orcid.org/0000-0002-7709-3159>), Cinzia Viroli [ctb] (<https://orcid.org/0000-0002-3278-5266>), Isobel Claire Gormley [ctb] (<https://orcid.org/0000-0001-7713-681X>)
Maintainer: Keefe Murphy <keefe.murphy@mu.ie>

Diff between IMIFA versions 2.1.6 dated 2021-05-24 and 2.1.7 dated 2021-10-08

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Package ifultools updated to version 2.0-23 with previous version 2.0-22 dated 2020-12-07

Title: Insightful Research Tools
Description: Insightful Research Tools is a collection of signal processing, image processing, and time series modeling routines written in the C language for speed and efficency. The routines were originally developed at Insightful for use in S-PLUS.
Author: William Constantine [aut], Stephen Kaluzny [aut, cre]
Maintainer: Stephen Kaluzny <spkaluzny@gmail.com>

Diff between ifultools versions 2.0-22 dated 2020-12-07 and 2.0-23 dated 2021-10-08

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Package GNRS updated to version 0.3.3 with previous version 0.3.2 dated 2021-10-05

Title: Access the 'Geographic Name Resolution Service'
Description: Provides tools for interacting with the 'geographic name resolution service' ('GNRS') API <https://github.com/ojalaquellueva/gnrs> and associated functionality. The 'GNRS' is a batch application for resolving & standardizing political division names against standard name in the geonames database <http://www.geonames.org/>. The 'GNRS' resolves political division names at three levels: country, state/province and county/parish. Resolution is performed in a series of steps, beginning with direct matching to standard names, followed by direct matching to alternate names in different languages, followed by direct matching to standard codes (such as ISO and FIPS codes). If direct matching fails, the 'GNRS' attempts to match to standard and then alternate names using fuzzy matching, but does not perform fuzzing matching of political division codes. The 'GNRS' works down the political division hierarchy, stopping at the current level if all matches fail. In other words, if a country cannot be matched, the 'GNRS' does not attempt to match state or county.
Author: Brad Boyle [aut], Brian Maitner [aut, cre]
Maintainer: Brian Maitner <bmaitner@gmail.com>

Diff between GNRS versions 0.3.2 dated 2021-10-05 and 0.3.3 dated 2021-10-08

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New package fwildclusterboot with initial version 0.4
Package: fwildclusterboot
Title: Fast Wild Cluster Bootstrap Inference for Linear Regression Models
Version: 0.4
Date: 2021-10-03
Description: Implementation of the fast algorithm for wild cluster bootstrap inference developed in Roodman et al (2019, STATA Journal) for linear regression models <https://journals.sagepub.com/doi/full/10.1177/1536867X19830877>, which makes it feasible to quickly calculate bootstrap test statistics based on a large number of bootstrap draws even for large samples - as long as the number of bootstrapping clusters is not too large. Multiway clustering, regression weights, bootstrap weights, fixed effects and subcluster bootstrapping are supported. Further, both restricted (WCR) and unrestricted (WCU) bootstrap are supported. Methods are provided for a variety of fitted models, including 'lm()', 'feols()' (from package 'fixest') and 'felm()' (from package 'lfe').
URL: https://s3alfisc.github.io/fwildclusterboot/
BugReports: https://github.com/s3alfisc/fwildclusterboot/issues/
License: GPL-3
Imports: collapse, Formula, Rcpp, dreamerr, Matrix, Matrix.utils, generics, gtools
Suggests: fixest, lfe, plm, clusterSEs, data.table, fabricatr, tinytest, covr, knitr, rmarkdown, spelling, broom, modelsummary, RStata
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp, RcppEigen
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: yes
Packaged: 2021-10-06 17:57:11 UTC; alexa
Author: Alexander Fischer [aut, cre], David Roodman [aut], Achim Zeileis [ctb] (Author of included sandwich fragments), Nathaniel Graham [ctb] (Contributor to included sandwich fragments), Susanne Koell [ctb] (Contributor to included sandwich fragments), Laurent Berge [ctb] (Author of included fixest fragments), Sebastian Krantz [ctb]
Maintainer: Alexander Fischer <alexander-fischer1801@t-online.de>
Repository: CRAN
Date/Publication: 2021-10-08 08:30:05 UTC

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Package equateIRT updated to version 2.2.1 with previous version 2.2.0 dated 2021-05-31

Title: IRT Equating Methods
Description: Computation of direct, chain and average (bisector) equating coefficients with standard errors using Item Response Theory (IRT) methods for dichotomous items (Battauz (2013) <doi:10.1007/s11336-012-9316-y>, Battauz (2015) <doi:10.18637/jss.v068.i07>). Test scoring can be performed by true score equating and observed score equating methods. DIF detection can be performed using a Wald-type test (Battauz (2018) <doi:10.1007/s10260-018-00442-w>).
Author: Michela Battauz
Maintainer: Michela Battauz <michela.battauz@uniud.it>

Diff between equateIRT versions 2.2.0 dated 2021-05-31 and 2.2.1 dated 2021-10-08

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Package emayili updated to version 0.6.1 with previous version 0.5.0 dated 2021-09-17

Title: Send Email Messages
Description: A light, simple tool for sending emails with minimal dependencies.
Author: Andrew B. Collier [aut, cre, cph], Matt Dennis [ctb], Antoine Bichat [ctb] (<https://orcid.org/0000-0001-6599-7081>), Daniel Fahey [ctb], Johann R. Kleinbub [ctb], Panagiotis Moulos [ctb]
Maintainer: Andrew B. Collier <andrew@fathomdata.dev>

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Package dynutils updated to version 1.0.9 with previous version 1.0.8 dated 2021-09-20

Title: Common Functionality for the 'dynverse' Packages
Description: Provides common functionality for the 'dynverse' packages. 'dynverse' is created to support the development, execution, and benchmarking of trajectory inference methods. For more information, check out <https://dynverse.org>.
Author: Robrecht Cannoodt [aut, cre] (<https://orcid.org/0000-0003-3641-729X>, rcannood), Wouter Saelens [aut] (<https://orcid.org/0000-0002-7114-6248>, zouter)
Maintainer: Robrecht Cannoodt <rcannood@gmail.com>

Diff between dynutils versions 1.0.8 dated 2021-09-20 and 1.0.9 dated 2021-10-08

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New package covid19br with initial version 0.1.2
Package: covid19br
Title: Brazilian COVID-19 Pandemic Data
Version: 0.1.2
Description: Set of functions to import COVID-19 pandemic data into R. The Brazilian COVID-19 data, obtained from the official Brazilian repository at <https://covid.saude.gov.br/>, is available at country, region, state, and city-levels. The package also downloads the world-level COVID-19 data from the John Hopkins University's repository.
URL: https://fndemarqui.github.io/covid19br/
BugReports: https://github.com/fndemarqui/covid19br/issues
Encoding: UTF-8
License: AGPL (>= 3)
Depends: R (>= 3.5.0)
Imports: data.table, dplyr, httr, rio, rlang, sf, tidyr
Suggests: ggrepel, kableExtra, knitr, leaflet, pracma, plotly, rmarkdown, testthat, tidyverse
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-10-07 22:45:23 UTC; fndemarqui
Author: Fabio Demarqui [aut, cre], Cristiano Santos [aut], Matheus Costa [ctb]
Maintainer: Fabio Demarqui <fndemarqui@est.ufmg.br>
Repository: CRAN
Date/Publication: 2021-10-08 08:40:12 UTC

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New package cotram with initial version 0.3-1
Package: cotram
Title: Count Transformation Models
Version: 0.3-1
Date: 2021-09-21
Description: Count transformation models featuring parameters interpretable as discrete hazard ratios, odds ratios, reverse-time discrete hazard ratios, or transformed expectations. An appropriate data transformation for a count outcome and regression coefficients are simultaneously estimated by maximising the exact discrete log-likelihood using the computational framework provided in package 'mlt', technical details are given in Siegfried & Hothorn (2020) <DOI:10.1111/2041-210X.13383>. The package also contains an experimental implementation of multivariate count transformation models with an application to multi-species distribution models.
Depends: R (>= 3.5.0), tram (>= 0.2-6), mlt (>= 1.2-1)
Imports: variables (>= 1.0-2), basefun (>= 1.0-5), alabama, Matrix, methods
Suggests: TH.data, knitr, lattice, colorspace, multcomp, mvtnorm, numDeriv
VignetteBuilder: knitr
URL: http://ctm.R-forge.R-project.org
Encoding: UTF-8
License: GPL-2
NeedsCompilation: no
Packaged: 2021-09-24 07:38:30 UTC; hothorn
Author: Sandra Siegfried [aut] (<https://orcid.org/0000-0002-7312-1001>), Luisa Barbanti [aut] (<https://orcid.org/0000-0001-5352-5802>), Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>
Repository: CRAN
Date/Publication: 2021-10-08 08:20:02 UTC

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Package coin updated to version 1.4-2 with previous version 1.4-1 dated 2021-02-08

Title: Conditional Inference Procedures in a Permutation Test Framework
Description: Conditional inference procedures for the general independence problem including two-sample, K-sample (non-parametric ANOVA), correlation, censored, ordered and multivariate problems described in <doi:10.18637/jss.v028.i08>.
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>), Henric Winell [aut] (<https://orcid.org/0000-0001-7995-3047>), Kurt Hornik [aut] (<https://orcid.org/0000-0003-4198-9911>), Mark A. van de Wiel [aut] (<https://orcid.org/0000-0003-4780-8472>), Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package CholWishart updated to version 1.1.2 with previous version 1.1.0 dated 2019-11-14

Title: Cholesky Decomposition of the Wishart Distribution
Description: Sampling from the Cholesky factorization of a Wishart random variable, sampling from the inverse Wishart distribution, sampling from the Cholesky factorization of an inverse Wishart random variable, sampling from the pseudo Wishart distribution, sampling from the generalized inverse Wishart distribution, computing densities for the Wishart and inverse Wishart distributions, and computing the multivariate gamma and digamma functions. Provides a header file so the C functions can be called directly from other programs.
Author: Geoffrey Thompson [aut, cre] (<https://orcid.org/0000-0003-2436-8822>), R Core Team [ctb]
Maintainer: Geoffrey Thompson <gzthompson@gmail.com>

Diff between CholWishart versions 1.1.0 dated 2019-11-14 and 1.1.2 dated 2021-10-08

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Package vein updated to version 0.9.4 with previous version 0.9.3 dated 2021-06-30

Title: Vehicular Emissions Inventories
Description: Elaboration of vehicular emissions inventories, consisting in four stages, pre-processing activity data, preparing emissions factors, estimating the emissions and post-processing of emissions in maps and databases. More details in Ibarra-Espinosa et al (2018) <doi:10.5194/gmd-11-2209-2018>. Before using VEIN you need to know the vehicular composition of your study area, in other words, the combination of of type of vehicles, size and fuel of the fleet. Then, it is recommended to start with the project to download a template to create a structure of directories and scripts.
Author: Sergio Ibarra-Espinosa [aut, cre] (<https://orcid.org/0000-0002-3162-1905>), Joao Bazzo [ctb] (<https://orcid.org/0000-0003-4536-5006>)
Maintainer: Sergio Ibarra-Espinosa <zergioibarra@gmail.com>

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More information about vein at CRAN
Permanent link

New package quincunx with initial version 0.1.1
Package: quincunx
Title: REST API Client for the 'PGS' Catalog
Version: 0.1.1
Description: Programmatic access to the 'PGS' Catalog. This package provides easy access to 'PGS' Catalog data by accessing the REST API <https://www.pgscatalog.org/rest/>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Suggests: testthat, knitr, rmarkdown, ggplot2
Imports: stringr, magrittr, vroom, purrr, glue, dplyr, tidyjson, tibble, lubridate, rlang, tidyr, httr, utils, rvest, progress, methods, writexl, concatenate, memoise
Depends: R (>= 2.10)
URL: https://github.com/maialab/quincunx
BugReports: https://github.com/maialab/quincunx/issues
NeedsCompilation: no
Packaged: 2021-10-07 20:55:30 UTC; rmagno
Author: Ramiro Magno [aut, cre] (<https://orcid.org/0000-0001-5226-3441>), Isabel Duarte [aut] (<https://orcid.org/0000-0003-0060-2936>), Ana-Teresa Maia [aut] (<https://orcid.org/0000-0002-0454-9207>), CINTESIS [cph, fnd]
Maintainer: Ramiro Magno <ramiro.magno@gmail.com>
Repository: CRAN
Date/Publication: 2021-10-08 07:10:02 UTC

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Package nser updated to version 1.3.3 with previous version 1.3.2 dated 2021-09-16

Title: Bhavcopy and Live Market Data from National Stock Exchange (NSE) India for Equities and Equity Derivatives (F&O)
Description: Download Historical Bhavcopy and get Live Market data from NSE India of Equities and Derivatives(F&O) segment. Data source <https://www.nseindia.com/>.
Author: Nandan Patil [cre, aut]
Maintainer: Nandan Patil <tryanother609@gmail.com>

Diff between nser versions 1.3.2 dated 2021-09-16 and 1.3.3 dated 2021-10-08

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New package PAMmisc with initial version 1.7.0
Package: PAMmisc
Title: Miscellaneous Functions for Passive Acoustic Analysis
Version: 1.7.0
Description: A collection of miscellaneous functions for passive acoustics. Much of the content here is adapted to R from code written by other people. If you have any ideas of functions to add, please contact Taiki Sakai.
License: GNU General Public License
Encoding: UTF-8
LazyData: true
Imports: ggplot2, tuneR, seewave, dplyr, magrittr, RcppRoll, PamBinaries, RSQLite, lubridate, rerddap, ncdf4, httr, purrr, xml2, hoardr, methods, geosphere, tcltk, stringr, viridisLite, viridis
Suggests: testthat
NeedsCompilation: no
Packaged: 2021-10-07 18:30:55 UTC; tnsak
Author: Taiki Sakai [aut, cre], Jay Barlow [ctb], Julie Oswald [ctb], Val Schmidt [ctb]
Maintainer: Taiki Sakai <taiki.sakai@noaa.gov>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2021-10-08 07:10:06 UTC

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Package haldensify updated to version 0.2.1 with previous version 0.0.6 dated 2020-09-16

Title: Highly Adaptive Lasso Conditional Density Estimation
Description: An algorithm for flexible conditional density estimation based on application of pooled hazard regression to an artificial repeated measures dataset constructed by discretizing the support of the outcome variable. To facilitate non/semi-parametric estimation of the conditional density, the highly adaptive lasso, a nonparametric regression function shown to reliably estimate a large class of functions at a fast convergence rate, is utilized. The pooled hazards data augmentation formulation implemented was first described by Díaz and van der Laan (2011) <doi:10.2202/1557-4679.1356>. To complement the conditional density estimation utilities, tools for efficient nonparametric inverse probability weighted (IPW) estimation of the causal effects of stochastic shift interventions (modified treatment policies), directly utilizing the density estimation technique for construction of the generalized propensity score, are provided. These IPW estimators utilize undersmoothing (sieve estimation) of the conditional density estimators in order to achieve the non/semi-parametric efficiency bound.
Author: Nima Hejazi [aut, cre, cph] (<https://orcid.org/0000-0002-7127-2789>), David Benkeser [aut] (<https://orcid.org/0000-0002-1019-8343>), Mark van der Laan [aut, ths] (<https://orcid.org/0000-0003-1432-5511>), Rachael Phillips [ctb] (<https://orcid.org/0000-0002-8474-591X>)
Maintainer: Nima Hejazi <nh@nimahejazi.org>

Diff between haldensify versions 0.0.6 dated 2020-09-16 and 0.2.1 dated 2021-10-08

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Package duckdb updated to version 0.3.0 with previous version 0.2.9 dated 2021-09-06

Title: DBI Package for the DuckDB Database Management System
Description: The DuckDB project is an embedded analytical data management system with support for the Structured Query Language (SQL). This package includes all of DuckDB and a R Database Interface (DBI) connector.
Author: Hannes Mühleisen [aut, cre] (<https://orcid.org/0000-0001-8552-0029>), Mark Raasveldt [aut] (<https://orcid.org/0000-0001-5005-6844>), DuckDB Contributors [aut], Apache Software Foundation [cph], PostgreSQL Global Development Group [cph], The Regents of the University of California [cph], Cameron Desrochers [cph], Victor Zverovich [cph], RAD Game Tools [cph], Valve Software [cph], Rich Geldreich [cph], Tenacious Software LLC [cph], The RE2 Authors [cph], Google Inc. [cph], Facebook Inc. [cph], Steven G. Johnson [cph], Jiahao Chen [cph], Tony Kelman [cph], Jonas Fonseca [cph], Lukas Fittl [cph], Salvatore Sanfilippo [cph], Art.sy, Inc. [cph], Oran Agra [cph], Redis Labs, Inc. [cph], Melissa O'Neill [cph], PCG Project contributors [cph]
Maintainer: Hannes Mühleisen <hannes@cwi.nl>

Diff between duckdb versions 0.2.9 dated 2021-09-06 and 0.3.0 dated 2021-10-08

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 duckdb-0.3.0/duckdb/DESCRIPTION                                                                          |    6 
 duckdb-0.3.0/duckdb/MD5                                                                                  |  361 
 duckdb-0.3.0/duckdb/R/Connection.R                                                                       |   15 
 duckdb-0.3.0/duckdb/README.md                                                                            |    6 
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 duckdb-0.3.0/duckdb/src/duckdb/src/catalog/catalog.cpp                                                   |  176 
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 duckdb-0.3.0/duckdb/src/duckdb/src/common/file_system.cpp                                                |  968 
 duckdb-0.3.0/duckdb/src/duckdb/src/common/gzip_file_system.cpp                                           |   27 
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 duckdb-0.3.0/duckdb/src/duckdb/src/common/sort/merge_sorter.cpp                                          |   11 
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 duckdb-0.3.0/duckdb/src/duckdb/src/common/string_util.cpp                                                |   60 
 duckdb-0.3.0/duckdb/src/duckdb/src/common/types.cpp                                                      |    8 
 duckdb-0.3.0/duckdb/src/duckdb/src/common/types/chunk_collection.cpp                                     |   15 
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 duckdb-0.3.0/duckdb/src/duckdb/src/common/types/hugeint.cpp                                              |    1 
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 duckdb-0.3.0/duckdb/src/duckdb/src/execution/operator/persistent/physical_export.cpp                     |    9 
 duckdb-0.3.0/duckdb/src/duckdb/src/execution/physical_plan/plan_comparison_join.cpp                      |  125 
 duckdb-0.3.0/duckdb/src/duckdb/src/execution/physical_plan/plan_set.cpp                                  |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/execution/physical_plan/plan_set_operation.cpp                        |    3 
 duckdb-0.3.0/duckdb/src/duckdb/src/function/aggregate/distributive/minmax.cpp                            |    1 
 duckdb-0.3.0/duckdb/src/duckdb/src/function/pragma/pragma_functions.cpp                                  |   12 
 duckdb-0.3.0/duckdb/src/duckdb/src/function/pragma/pragma_queries.cpp                                    |    5 
 duckdb-0.3.0/duckdb/src/duckdb/src/function/scalar/date/age.cpp                                          |    4 
 duckdb-0.3.0/duckdb/src/duckdb/src/function/scalar/date/date_sub.cpp                                     |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/function/scalar/generic/current_setting.cpp                           |   20 
 duckdb-0.3.0/duckdb/src/duckdb/src/function/scalar/generic/least.cpp                                     |   12 
 duckdb-0.3.0/duckdb/src/duckdb/src/function/scalar/list/list_extract.cpp                                 |   89 
 duckdb-0.3.0/duckdb/src/duckdb/src/function/scalar/operators/arithmetic.cpp                              |  281 
 duckdb-0.3.0/duckdb/src/duckdb/src/function/scalar/operators/multiply.cpp                                |    1 
 duckdb-0.3.0/duckdb/src/duckdb/src/function/scalar/string/regexp.cpp                                     |   43 
 duckdb-0.3.0/duckdb/src/duckdb/src/function/table/arrow.cpp                                              |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/function/table/copy_csv.cpp                                           |    7 
 duckdb-0.3.0/duckdb/src/duckdb/src/function/table/read_csv.cpp                                           |    1 
 duckdb-0.3.0/duckdb/src/duckdb/src/function/table/version/pragma_version.cpp                             |    4 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/catalog/catalog.hpp                                    |   65 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/catalog/catalog_entry/schema_catalog_entry.hpp         |    4 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/catalog/catalog_entry/table_catalog_entry.hpp          |    6 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/catalog/catalog_search_path.hpp                        |only
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/catalog/catalog_set.hpp                                |   12 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/case_insensitive_map.hpp                        |only
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/enums/expression_type.hpp                       |    1 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/enums/set_scope.h                               |only
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/file_opener.hpp                                 |only
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/file_system.hpp                                 |  165 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/gzip_file_system.hpp                            |   11 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/local_file_system.hpp                           |only
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/operator/cast_operators.hpp                     |   24 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/pipe_file_system.hpp                            |   12 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/profiler.hpp                                    |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/row_operations/row_operations.hpp               |    4 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/serializer/buffered_file_reader.hpp             |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/serializer/buffered_file_writer.hpp             |    6 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/sort/sort.hpp                                   |   10 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/sort/sorted_block.hpp                           |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/string_util.hpp                                 |    3 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/types.hpp                                       |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/types/data_chunk.hpp                            |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/types/date.hpp                                  |   59 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/types/interval.hpp                              |    5 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/types/selection_vector.hpp                      |    1 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/types/time.hpp                                  |   18 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/types/timestamp.hpp                             |   44 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/types/uuid.hpp                                  |only
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/types/validity_mask.hpp                         |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/types/value.hpp                                 |    4 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/types/vector.hpp                                |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/types/vector_buffer.hpp                         |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/common/virtual_file_system.hpp                         |only
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/execution/expression_executor_state.hpp                |   13 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/execution/join_hashtable.hpp                           |   28 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/execution/operator/helper/physical_set.hpp             |   14 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/execution/operator/join/perfect_hash_join_executor.hpp |only
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/execution/operator/join/physical_hash_join.hpp         |   40 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/execution/operator/persistent/buffered_csv_reader.hpp  |    4 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/execution/physical_operator.hpp                        |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/function/scalar/operators.hpp                          |    6 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/function/scalar/regexp.hpp                             |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/function/scalar_function.hpp                           |    9 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/main/client_context.hpp                                |   15 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/main/client_context_file_opener.hpp                    |only
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/main/config.hpp                                        |    3 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/optimizer/statistics_propagator.hpp                    |   11 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/parser/expression/list.hpp                             |    1 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/parser/expression/star_expression.hpp                  |   13 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/parser/parsed_data/create_function_info.hpp            |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/parser/parsed_data/create_macro_info.hpp               |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/parser/parsed_data/create_sequence_info.hpp            |    5 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/parser/parsed_data/create_view_info.hpp                |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/parser/statement/set_statement.hpp                     |    4 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/parser/transformer.hpp                                 |    1 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/planner/bind_context.hpp                               |   40 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/planner/binder.hpp                                     |    8 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/planner/expression.hpp                                 |    4 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/planner/operator/logical_join.hpp                      |    3 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/planner/operator/logical_set.hpp                       |    7 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/planner/parsed_data/bound_create_table_info.hpp        |    3 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/planner/table_binding.hpp                              |    4 
 duckdb-0.3.0/duckdb/src/duckdb/src/include/duckdb/storage/buffer_manager.hpp                             |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/main/client_context.cpp                                               |   26 
 duckdb-0.3.0/duckdb/src/duckdb/src/main/client_context_file_opener.cpp                                   |only
 duckdb-0.3.0/duckdb/src/duckdb/src/main/connection.cpp                                                   |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/main/database.cpp                                                     |    4 
 duckdb-0.3.0/duckdb/src/duckdb/src/main/query_profiler.cpp                                               |   51 
 duckdb-0.3.0/duckdb/src/duckdb/src/optimizer/join_order_optimizer.cpp                                    |    5 
 duckdb-0.3.0/duckdb/src/duckdb/src/optimizer/statistics/expression/propagate_and_compress.cpp            |only
 duckdb-0.3.0/duckdb/src/duckdb/src/optimizer/statistics/operator/propagate_filter.cpp                    |    6 
 duckdb-0.3.0/duckdb/src/duckdb/src/optimizer/statistics/operator/propagate_get.cpp                       |    4 
 duckdb-0.3.0/duckdb/src/duckdb/src/optimizer/statistics/operator/propagate_join.cpp                      |   20 
 duckdb-0.3.0/duckdb/src/duckdb/src/optimizer/statistics/operator/propagate_order.cpp                     |   10 
 duckdb-0.3.0/duckdb/src/duckdb/src/optimizer/statistics/operator/propagate_window.cpp                    |   15 
 duckdb-0.3.0/duckdb/src/duckdb/src/optimizer/statistics_propagator.cpp                                   |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/parser/expression/star_expression.cpp                                 |   94 
 duckdb-0.3.0/duckdb/src/duckdb/src/parser/parsed_expression.cpp                                          |    7 
 duckdb-0.3.0/duckdb/src/duckdb/src/parser/parsed_expression_iterator.cpp                                 |    1 
 duckdb-0.3.0/duckdb/src/duckdb/src/parser/statement/set_statement.cpp                                    |    6 
 duckdb-0.3.0/duckdb/src/duckdb/src/parser/transform/expression/transform_columnref.cpp                   |   44 
 duckdb-0.3.0/duckdb/src/duckdb/src/parser/transform/expression/transform_function.cpp                    |   21 
 duckdb-0.3.0/duckdb/src/duckdb/src/parser/transform/statement/transform_set.cpp                          |   27 
 duckdb-0.3.0/duckdb/src/duckdb/src/planner/bind_context.cpp                                              |  135 
 duckdb-0.3.0/duckdb/src/duckdb/src/planner/binder.cpp                                                    |    8 
 duckdb-0.3.0/duckdb/src/duckdb/src/planner/binder/query_node/bind_select_node.cpp                        |    9 
 duckdb-0.3.0/duckdb/src/duckdb/src/planner/binder/query_node/plan_recursive_cte_node.cpp                 |    1 
 duckdb-0.3.0/duckdb/src/duckdb/src/planner/binder/statement/bind_create.cpp                              |    3 
 duckdb-0.3.0/duckdb/src/duckdb/src/planner/binder/statement/bind_set.cpp                                 |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/planner/binder/statement/bind_summarize.cpp                           |   33 
 duckdb-0.3.0/duckdb/src/duckdb/src/planner/binder/tableref/bind_joinref.cpp                              |  111 
 duckdb-0.3.0/duckdb/src/duckdb/src/planner/table_binding.cpp                                             |    7 
 duckdb-0.3.0/duckdb/src/duckdb/src/storage/buffer_manager.cpp                                            |   23 
 duckdb-0.3.0/duckdb/src/duckdb/src/storage/data_table.cpp                                                |    6 
 duckdb-0.3.0/duckdb/src/duckdb/src/storage/local_storage.cpp                                             |   28 
 duckdb-0.3.0/duckdb/src/duckdb/src/storage/single_file_block_manager.cpp                                 |    2 
 duckdb-0.3.0/duckdb/src/duckdb/src/storage/storage_info.cpp                                              |    2 
 duckdb-0.3.0/duckdb/src/duckdb/third_party/libpg_query/include/nodes/parsenodes.hpp                      |   16 
 duckdb-0.3.0/duckdb/src/duckdb/third_party/libpg_query/src_backend_parser_gram.cpp                       |13449 +++++-----
 duckdb-0.3.0/duckdb/src/include/typesr.hpp                                                               |    7 
 duckdb-0.3.0/duckdb/src/rapi.cpp                                                                         |    2 
 duckdb-0.3.0/duckdb/src/statement.cpp                                                                    |  434 
 duckdb-0.3.0/duckdb/tests/testthat/test_list.R                                                           |only
 duckdb-0.3.0/duckdb/tests/testthat/test_register_arrow.R                                                 |    8 
 191 files changed, 9739 insertions(+), 8955 deletions(-)

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New package FADPclust with initial version 0.1.0
Package: FADPclust
Title: Functional Data Clustering Using Adaptive Density Peak Detection
Version: 0.1.0
Author: Rui Ren <xmurr@stu.xmu.edu.cn>
Maintainer: Rui Ren <xmurr@stu.xmu.edu.cn>
Description: An implementation of a clustering algorithm for functional data based on adaptive density peak detection technique, in which the density is estimated by functional k-nearest neighbor density estimation based on a proposed semi-metric between functions. The proposed functional data clustering algorithm is computationally fast since it does not need iterative process. (Alex Rodriguez and Alessandro Laio (2014) <doi:10.1126/science.1242072>; Xiao-Feng Wang and Yifan Xu (2016) <doi:10.1177/0962280215609948>).
License: GPL (>= 2)
Depends: R (>= 3.5.0)
Imports: MFPCA, cluster, fda, fda.usc, funData, stats, graphics
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2021-10-07 19:39:16 UTC; renrui
Repository: CRAN
Date/Publication: 2021-10-08 07:10:09 UTC

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Package dbarts updated to version 0.9-20 with previous version 0.9-19 dated 2021-01-05

Title: Discrete Bayesian Additive Regression Trees Sampler
Description: Fits Bayesian additive regression trees (BART; Chipman, George, and McCulloch (2010) <doi:10.1214/09-AOAS285>) while allowing the updating of predictors or response so that BART can be incorporated as a conditional model in a Gibbs/Metropolis-Hastings sampler. Also serves as a drop-in replacement for package 'BayesTree'.
Author: Vincent Dorie [aut, cre] (<https://orcid.org/0000-0002-9576-3064>), Hugh Chipman [aut], Robert McCulloch [aut], Armon Dadgar [ctb] (adaptive radix tree), R Core Team [ctb] (basis of RNG), Guido U Draheim [ctb] (ax_check_compile_flag.m4), Maarten Bosmans [ctb] (ax_check_compile_flag.m4), Christophe Tournayre [ctb] (ax_compiler_ext.m4, ax_ext.m4), Michael Petch [ctb] (ax_compiler_ext.m4, ax_ext.m4, ax_gcc_x86_avx_xgetbv.m4, ax_gcc_x86_cpuid.m4), Rafael de Lucena Valle [ctb] (ax_compiler_ext.m4, ax_ext.m4), Steven G. Johnson [ctb] (ax_compiler_vendor.m4, ax_gcc_x86_cpuid.m4, ax_pthread.m4, <https://orcid.org/0000-0001-7327-4967>), Matteo Frigo [ctb] (ax_compiler_vendor.m4, ax_gcc_x86_cpuid.m4), John Zaitseff [ctb] (ax_compiler_vendor.m4), Todd Veldhuizen [ctb] (ax_cxx_namespace_std.m4), Luc Maisonobe [ctb] (ax_cxx_namespace_std.m4), Scott Pakin [ctb] (ax_func_posix_memalign.m4, <https://orcid.org/0000-0002-5220-1985>), Daniel Richard G. [ctb] (ax_pthread.m4)
Maintainer: Vincent Dorie <vdorie@gmail.com>

Diff between dbarts versions 0.9-19 dated 2021-01-05 and 0.9-20 dated 2021-10-08

 DESCRIPTION                              |    8 
 MD5                                      |  129 
 NAMESPACE                                |    2 
 R/A_class.R                              |   39 
 R/bart.R                                 |   45 
 R/data.R                                 |   18 
 R/dbarts.R                               |    5 
 R/generics.R                             |    3 
 R/model.R                                |   61 
 R/partialDependence.R                    |   20 
 R/rbart.R                                |  166 
 R/sliceSample.R                          |   12 
 R/utility.R                              |    2 
 R/xbart.R                                |    5 
 build/vignette.rds                       |binary
 configure                                | 5757 +++++++++++++++++--------------
 configure.ac                             |   49 
 inst/NEWS.Rd                             |   43 
 inst/doc/gibbs_sampler_mixture_model.pdf |binary
 inst/include/dbarts/R_C_interface.hpp    |   18 
 inst/include/dbarts/bartFit.hpp          |    7 
 inst/include/dbarts/model.hpp            |   68 
 man/bart.Rd                              |   40 
 man/dbarts.Rd                            |    3 
 man/rbart.Rd                             |    9 
 src/R_C_interface.cpp                    |   26 
 src/R_interface.cpp                      |    6 
 src/R_interface_common.cpp               |   68 
 src/R_interface_crossvalidate.cpp        |    9 
 src/R_interface_sampler.cpp              |    9 
 src/config.hpp.in                        |   37 
 src/config.hpp.win                       |    4 
 src/crossvalidate.cpp                    |   15 
 src/dbarts/bartFit.cpp                   |   99 
 src/dbarts/binaryIO.cpp                  |   42 
 src/dbarts/config.hpp.win                |    4 
 src/dbarts/likelihood.cpp                |    2 
 src/dbarts/node.cpp                      |    4 
 src/dbarts/node.hpp                      |    2 
 src/dbarts/parameterPrior.cpp            |   51 
 src/dbarts/tree.cpp                      |    4 
 src/external/config.h.win                |    4 
 src/external/linearAlgebra.c             |   40 
 src/external/randomBase.c                |    3 
 src/external/randomNorm.c                |    8 
 src/guessNumCores.cpp                    |    1 
 src/include/external/R.h                 |    9 
 src/include/external/Rinternals.h        |    7 
 src/include/external/stats.h             |    8 
 src/misc/config.h.win                    |    4 
 src/misc/hierarchicalThreadManager.c     |   20 
 tests/testthat/test-03-dbartsControl.R   |  128 
 tests/testthat/test-05-binaryResponse.R  |   10 
 tests/testthat/test-06-dbartsSampler.R   |    2 
 tests/testthat/test-08-xbart.R           |   14 
 tests/testthat/test-14-rbart.R           |   55 
 tests/testthat/test-17-rng.R             |only
 tools/build-aux/config.guess             | 1240 +++---
 tools/build-aux/config.sub               |   96 
 tools/m4/ax_check_compile_flag.m4        |   33 
 tools/m4/ax_compiler_ext.m4              |   13 
 tools/m4/ax_cxx_namespace_std.m4         |   17 
 tools/m4/ax_func_posix_memalign.m4       |   11 
 tools/m4/ax_log1p_in_namespace_std.m4    |    2 
 tools/m4/ax_pthread.m4                   |  248 -
 tools/m4/ax_snprintf_in_namespace_std.m4 |    2 
 66 files changed, 5040 insertions(+), 3826 deletions(-)

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New package presenter with initial version 0.1.0
Package: presenter
Title: Present Data with Style
Version: 0.1.0
Maintainer: Harrison Tietze <Harrison4192@gmail.com>
Description: Consists of custom wrapper functions using packages 'openxlsx', 'flextable', and 'officer' to create highly formatted MS office friendly output of your data frames. These viewer friendly outputs are intended to match expectations of professional looking presentations in business and consulting scenarios. The functions are opinionated in the sense that they expect the input data frame to have certain properties in order to take advantage of the automated formatting.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: flextable, magrittr, dplyr, rlang, stringr, purrr, officer, randomcoloR, tidyr, openxlsx, lubridate, janitor, tibble, stringi, berryFunctions, rvg, tidyselect, formattable, badger, framecleaner
Suggests: knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
URL: https://github.com/Harrison4192/presenter
BugReports: https://github.com/Harrison4192/presenter/issues
NeedsCompilation: no
Packaged: 2021-10-07 17:03:26 UTC; Harrison
Author: Harrison Tietze [aut, cre]
Repository: CRAN
Date/Publication: 2021-10-08 07:00:02 UTC

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Package mlfit updated to version 0.5.3 with previous version 0.5.2 dated 2021-07-02

Title: Iterative Proportional Fitting Algorithms for Nested Structures
Description: The Iterative Proportional Fitting (IPF) algorithm operates on count data. This package offers implementations for several algorithms that extend this to nested structures: 'parent' and 'child' items for both of which constraints can be provided. The fitting algorithms include Iterative Proportional Updating <https://trid.trb.org/view/881554>, Hierarchical IPF <doi:10.3929/ethz-a-006620748>, Entropy Optimization <https://trid.trb.org/view/881144>, and Generalized Raking <doi:10.2307/2290793>. Additionally, a number of replication methods is also provided such as 'Truncate, replicate, sample' <doi:10.1016/j.compenvurbsys.2013.03.004>.
Author: Kirill Müller [aut, cph] (Creator of the package), Kay W. Axhausen [ths] (Advisor of Kirill Müller), Amarin Siripanich [aut, cre] (Contributed `ml_replicate()`), Taha H. Rashidi [ths] (Advisor of Amarin Siripanich)
Maintainer: Amarin Siripanich <amarin.siri@gmail.com>

Diff between mlfit versions 0.5.2 dated 2021-07-02 and 0.5.3 dated 2021-10-08

 DESCRIPTION                          |   13 
 MD5                                  |   88 +-
 NAMESPACE                            |  110 +-
 R/S3.R                               |   44 -
 R/flatten_ml_fit_problem.R           | 1350 +++++++++++++++++------------------
 R/grake.R                            |  580 +++++++--------
 R/margins.R                          |  232 +++---
 R/ml_fit.R                           |  373 ++++-----
 R/ml_fit_dss.R                       |  110 +-
 R/ml_fit_entropy_o.R                 |  190 ++--
 R/ml_fit_hipf.R                      |  444 +++++------
 R/ml_fit_ipu.R                       |  176 ++--
 R/ml_problem.R                       |  580 +++++++--------
 R/ml_replicate.R                     |  270 +++----
 R/mlfit-package.R                    |   46 -
 R/toy.R                              |   50 -
 R/utils.R                            |   28 
 man/compute_margins.Rd               |  120 +--
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Package GPBayes updated to version 0.1.0-2.1 with previous version 0.1.0-2 dated 2021-09-13

Title: Tools for Gaussian Process Modeling in Uncertainty Quantification
Description: Gaussian processes (GPs) have been widely used to model spatial data, spatio-temporal data, and computer experiments in diverse areas of statistics including spatial statistics, spatio-temporal statistics, uncertainty quantification, and machine learning. This package creates basic tools for fitting and prediction based on GPs with spatial data, spatio-temporal data, and computer experiments. Key characteristics for this GP tool include: (1) the comprehensive implementation of various covariance functions including the Matérn family and the Confluent Hypergeometric family with isotropic form, tensor form, and automatic relevance determination form, where the isotropic form is widely used in spatial statistics, the tensor form is widely used in design and analysis of computer experiments and uncertainty quantification, and the automatic relevance determination form is widely used in machine learning; (2) implementations via Markov chain Monte Carlo (MCMC) algorithms and optimization algorithms for GP models with all the implemented covariance functions. The methods for fitting and prediction are mainly implemented in a Bayesian framework; (3) model evaluation via Fisher information and predictive metrics such as predictive scores; (4) built-in functionality for simulating GPs with all the implemented covariance functions; (5) unified implementation to allow easy specification of various GPs.
Author: Pulong Ma [aut, cre]
Maintainer: Pulong Ma <mpulong@gmail.com>

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Package sensemakr updated to version 0.1.4 with previous version 0.1.3 dated 2020-04-28

Title: Sensitivity Analysis Tools for Regression Models
Description: Implements a suite of sensitivity analysis tools that extends the traditional omitted variable bias framework and makes it easier to understand the impact of omitted variables in regression models, as discussed in Cinelli, C. and Hazlett, C. (2020), "Making Sense of Sensitivity: Extending Omitted Variable Bias." Journal of the Royal Statistical Society, Series B (Statistical Methodology) <doi:10.1111/rssb.12348>.
Author: Carlos Cinelli [aut, cre], Jeremy Ferwerda [aut], Chad Hazlett [aut], Aaron Rudkin [ctb]
Maintainer: Carlos Cinelli <carloscinelli@hotmail.com>

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Package rsmatrix updated to version 0.2.0 with previous version 0.1.2 dated 2021-01-23

Title: Matrices for Repeat-Sales Price Indexes
Description: A small package for calculating the matrices in Shiller (1991, <doi:10.1016/S1051-1377(05)80028-2>) that serve as the foundation for many repeat-sales price indexes.
Author: Steve Martin [aut, cre, cph]
Maintainer: Steve Martin <stevemartin041@gmail.com>

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Package MM updated to version 1.6-6 with previous version 1.6-5 dated 2018-05-16

Title: The Multiplicative Multinomial Distribution
Description: Various utilities for the Multiplicative Multinomial distribution.
Author: Robin K. S. Hankin and P. M. E. Altham
Maintainer: Robin K. S. Hankin <hankin.robin@gmail.com>

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Package dataMaid updated to version 1.4.1 with previous version 1.4.0 dated 2019-12-10

Title: A Suite of Checks for Identification of Potential Errors in a Data Frame as Part of the Data Screening Process
Description: Data screening is an important first step of any statistical analysis. dataMaid auto generates a customizable data report with a thorough summary of the checks and the results that a human can use to identify possible errors. It provides an extendable suite of test for common potential errors in a dataset.
Author: Anne Helby Petersen [aut], Claus Thorn Ekstrøm [aut, cre]
Maintainer: Claus Thorn Ekstrøm <ekstrom@sund.ku.dk>

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