Mon, 08 Nov 2021

Package vstsr updated to version 1.1.0 with previous version 1.0.0 dated 2018-03-14

Title: Access to 'Azure DevOps' API via R
Description: Implementation of 'Azure DevOps' <https://azure.microsoft.com/> API calls. It enables the extraction of information about repositories, build and release definitions and individual releases. It also helps create repositories and work items within a project without logging into 'Azure DevOps'. There is the ability to use any API service with a shell for any non-predefined call.
Author: Ashley Baldry [aut, cre]
Maintainer: Ashley Baldry <arbaldry91@gmail.com>

Diff between vstsr versions 1.0.0 dated 2018-03-14 and 1.1.0 dated 2021-11-08

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Package rcbsubset updated to version 1.1.5 with previous version 1.1.4 dated 2018-05-17

Title: Optimal Subset Matching with Refined Covariate Balance
Description: Tools for optimal subset matching of treated units and control units in observational studies, with support for refined covariate balance constraints, (including fine and near-fine balance as special cases). A close relative is the 'rcbalance' package. See Pimentel, et al.(2015) <doi:10.1080/01621459.2014.997879> and Pimentel and Kelz (2020) <doi:10.1080/01621459.2020.1720693>.
Author: Samuel D. Pimentel
Maintainer: Samuel D. Pimentel <spi@berkeley.edu>

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Package rasciidoc updated to version 4.0.0 with previous version 3.2.0 dated 2021-11-04

Title: Create Reports Using R and 'asciidoc'
Description: Inspired by Karl Broman`s reader on using 'knitr' with 'asciidoc' (<https://kbroman.org/knitr_knutshell/pages/asciidoc.html>), this is merely a wrapper to 'knitr' and 'asciidoc'.
Author: Andreas Dominik Cullmann [aut, cre]
Maintainer: Andreas Dominik Cullmann <fvafrcu@mailbox.org>

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Package lightr updated to version 1.6.2 with previous version 1.6.1 dated 2021-11-08

Title: Read Spectrometric Data and Metadata
Description: Parse various reflectance/transmittance/absorbance spectra file formats to extract spectral data and metadata, as described in Gruson, White & Maia (2019) <doi:10.21105/joss.01857>. Among other formats, it can import files from 'Avantes' <https://www.avantes.com/>, 'CRAIC' <https://www.microspectra.com/>, and 'OceanInsight' (formerly 'OceanOptics') <https://www.oceaninsight.com/> brands.
Author: Hugo Gruson [cre, aut, cph] (<https://orcid.org/0000-0002-4094-1476>), Rafael Maia [aut, cph] (<https://orcid.org/0000-0002-7563-9795>), Thomas White [aut, cph] (<https://orcid.org/0000-0002-3976-1734>), Kotya Karapetyan [ctb, cph] (Author of the MATLAB script to read AvaSoft7 binary files (CC-BY))
Maintainer: Hugo Gruson <hugo.gruson+R@normalesup.org>

Diff between lightr versions 1.6.1 dated 2021-11-08 and 1.6.2 dated 2021-11-08

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Package conos updated to version 1.4.4 with previous version 1.4.3 dated 2021-08-07

Title: Clustering on Network of Samples
Description: Wires together large collections of single-cell RNA-seq datasets, which allows for both the identification of recurrent cell clusters and the propagation of information between datasets in multi-sample or atlas-scale collections. 'Conos' focuses on the uniform mapping of homologous cell types across heterogeneous sample collections. For instance, users could investigate a collection of dozens of peripheral blood samples from cancer patients combined with dozens of controls, which perhaps includes samples of a related tissue such as lymph nodes. This package interacts with data available through the 'conosPanel' package, which is available in a 'drat' repository. To access this data package, see the instructions at <https://github.com/kharchenkolab/conos>. The size of the 'conosPanel' package is approximately 12 MB.
Author: Viktor Petukhov [aut], Nikolas Barkas [aut], Peter Kharchenko [aut], Weiliang Qiu [ctb], Evan Biederstedt [aut, cre]
Maintainer: Evan Biederstedt <evan.biederstedt@gmail.com>

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Package analogsea updated to version 1.0.3 with previous version 1.0.0 dated 2021-06-01

Title: Interface to 'Digital Ocean'
Description: Provides a set of functions for interacting with the 'Digital Ocean' API <https://www.digitalocean.com/>, including creating images, destroying them, rebooting, getting details on regions, and available images.
Author: Scott Chamberlain [aut] (<https://orcid.org/0000-0003-1444-9135>), Hadley Wickham [aut], Winston Chang [aut], Bob Rudis [ctb], Bryce Mecum [ctb] (<https://orcid.org/0000-0002-0381-3766>), Mauricio Vargas [aut, cre] (<https://orcid.org/0000-0003-1017-7574>), RStudio [cph]
Maintainer: Mauricio Vargas <mavargas11@uc.cl>

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Package jqr updated to version 1.2.2 with previous version 1.2.1 dated 2021-05-06

Title: Client for 'jq', a 'JSON' Processor
Description: Client for 'jq', a 'JSON' processor (<https://stedolan.github.io/jq/>), written in C. 'jq' allows the following with 'JSON' data: index into, parse, do calculations, cut up and filter, change key names and values, perform conditionals and comparisons, and more.
Author: Rich FitzJohn [aut], Jeroen Ooms [aut], Scott Chamberlain [aut, cre], Stefan Milton Bache [aut]
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

Diff between jqr versions 1.2.1 dated 2021-05-06 and 1.2.2 dated 2021-11-08

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Package IFAA updated to version 1.0.3 with previous version 1.0.2 dated 2021-07-20

Title: Robust Inference for Absolute Abundance in Microbiome Analysis
Description: A novel approach to make inference on the association of covariates with the absolute abundance (AA) of 'microbiome' in an ecosystem. It can be also directly applied to relative abundance (RA) data to make inference on AA (even if AA data is not available) because the ratio of two RA is equal ratio of their AA. This algorithm can estimate and test the associations of interest while adjusting for potential 'confounders'. The estimates of this method have easy interpretation like a typical regression analysis. High-dimensional covariates are handled with regularization and it is implemented by parallel computing. This algorithm finds optimal reference 'taxa/OTU (Operational Taxonomic Unit)/ASV (Amplicon Sequence Bariant)' and uses permutation to control FDR (False Discovery Rate).
Author: Quran Wu [aut], Zhigang Li [aut, cre]
Maintainer: Zhigang Li <zhigang.li@ufl.edu>

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Package rsample updated to version 0.1.1 with previous version 0.1.0 dated 2021-05-08

Title: General Resampling Infrastructure
Description: Classes and functions to create and summarize different types of resampling objects (e.g. bootstrap, cross-validation).
Author: Julia Silge [aut, cre] (<https://orcid.org/0000-0002-3671-836X>), Fanny Chow [aut], Max Kuhn [aut], Hadley Wickham [aut], RStudio [cph]
Maintainer: Julia Silge <julia.silge@rstudio.com>

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Package rbi updated to version 0.10.4 with previous version 0.10.3 dated 2020-04-17

Title: Interface to 'LibBi'
Description: Provides a complete interface to 'LibBi', a library for Bayesian inference (see <http://libbi.org> and <doi:10.18637/jss.v067.i10> for more information). This includes functions for manipulating 'LibBi' models, for reading and writing 'LibBi' input/output files, for converting 'LibBi' output to provide traces for use with the coda package, and for running 'LibBi' to conduct inference.
Author: Pierre E. Jacob [aut], Anthony Lee [ctb], Lawrence M. Murray [ctb], Sebastian Funk [aut, cre], Sam Abbott [ctb]
Maintainer: Sebastian Funk <sebastian.funk@lshtm.ac.uk>

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Package Compositional updated to version 5.2 with previous version 5.0 dated 2021-10-06

Title: Compositional Data Analysis
Description: Regression, classification, contour plots, hypothesis testing and fitting of distributions for compositional data are some of the functions included. The standard textbook for such data is John Aitchison's (1986) "The statistical analysis of compositional data". Relevant papers include: a) Tsagris M.T., Preston S. and Wood A.T.A. (2011). A data-based power transformation for compositional data. Fourth International International Workshop on Compositional Data Analysis. b) Tsagris M. (2014). The k-NN algorithm for compositional data: a revised approach with and without zero values present. Journal of Data Science, 12(3):519--534. c) Tsagris M. (2015). A novel, divergence based, regression for compositional data. Proceedings of the 28th Panhellenic Statistics Conference, 15-18 April 2015, Athens, Greece, 430--444. d) Tsagris M. (2015). Regression analysis with compositional data containing zero values. Chilean Journal of Statistics, 6(2):47--57. e) Tsagris M., Preston S. and Wood A.T.A. (2016). Improved supervised classification for compositional data using the alpha-transformation. Journal of Classification, 33(2):243--261. <doi:10.1007/s00357-016-9207-5>. f) Tsagris M., Preston S. and Wood A.T.A. (2017). Nonparametric hypothesis testing for equality of means on the simplex. Journal of Statistical Computation and Simulation, 87(2): 406--422. <doi:10.1080/00949655.2016.1216554>. g) Tsagris M. and Stewart C. (2018). A Dirichlet regression model for compositional data with zeros. Lobachevskii Journal of Mathematics,39(3): 398--412. <doi:10.1134/S1995080218030198>. h) Alenazi A. (2019). Regression for compositional data with compositional data as predictor variables with or without zero values. Journal of Data Science, 17(1): 219--238. <doi:10.6339/JDS.201901_17(1).0010>. i) Tsagris M. and Stewart C. (2020). A folded model for compositional data analysis. Australian and New Zealand Journal of Statistics, 62(2):249--277. <doi:10.1111/anzs.12289>. j) Tsagris M., Alenazi A. and Stewart C. (2021). Non-parametric regression models for compositional data. <arXiv:2002.05137>. We further include functions for percentages (or proportions).
Author: Michail Tsagris [aut, cre], Giorgos Athineou [aut], Abdulaziz Alenazi [ctb], Christos Adam [ctb]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

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 R/sym.test.R                 |    2 
 R/symkl.compreg.R            |    5 -
 R/ternary.R                  |   50 +++++++++-
 R/ternary.reg.R              |    1 
 R/tv.compreg.R               |   13 ++
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More information about Compositional at CRAN
Permanent link

Package mapboxapi updated to version 0.3 with previous version 0.2 dated 2020-10-05

Title: R Interface to 'Mapbox' Web Services
Description: Includes support for 'Mapbox' Navigation APIs, including directions, isochrones, and route optimization; the Search API for forward and reverse geocoding; the Maps API for interacting with 'Mapbox' vector tilesets and visualizing 'Mapbox' maps in R; and the 'tippecanoe' tile-generation utility. See <https://docs.mapbox.com/api/> for more information about the 'Mapbox' APIs.
Author: Kyle Walker [aut, cre]
Maintainer: Kyle Walker <kyle@walker-data.com>

Diff between mapboxapi versions 0.2 dated 2020-10-05 and 0.3 dated 2021-11-08

 DESCRIPTION             |   13 +-
 MD5                     |   15 +-
 NAMESPACE               |   13 ++
 R/mapboxapi-package.R   |    4 
 R/maps.R                |  262 +++++++++++++++++++++++++++++++++++++++++++++++-
 R/tippecanoe.R          |    6 -
 README.md               |   10 +
 man/get_static_tiles.Rd |only
 man/static_mapbox.Rd    |    3 
 9 files changed, 307 insertions(+), 19 deletions(-)

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Package logNormReg updated to version 0.5-0 with previous version 0.4-0 dated 2021-10-12

Title: log Normal Linear Regression
Description: Functions to fits simple linear regression models with log normal errors and identity link, i.e. taking the responses on the original scale. See Muggeo (2018) <doi:10.13140/RG.2.2.18118.16965>.
Author: Vito M. R. Muggeo [aut, cre] (<https://orcid.org/0000-0002-3386-4054>)
Maintainer: Vito M. R. Muggeo <vito.muggeo@unipa.it>

Diff between logNormReg versions 0.4-0 dated 2021-10-12 and 0.5-0 dated 2021-11-08

 DESCRIPTION               |    9 +-
 MD5                       |   24 ++++---
 NAMESPACE                 |   38 +++++------
 NEWS                      |   28 +++++---
 R/extractAIC.lognlm.R     |   14 ++--
 R/lognlm.R                |  145 +++++++++++++++++++++----------------------
 R/print.summary.lognlm.R  |   17 +++--
 R/summary.lognlm.R        |   19 +++++
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 14 files changed, 245 insertions(+), 207 deletions(-)

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Package gpx updated to version 1.1.0 with previous version 1.0.1 dated 2021-10-29

Title: Process GPX Files into R Data Structures
Description: Process open standard GPX files into data.frames for further use and analysis in R.
Author: Mark Ewing [aut, cre]
Maintainer: Mark Ewing <b.mark@ewingsonline.com>

Diff between gpx versions 1.0.1 dated 2021-10-29 and 1.1.0 dated 2021-11-08

 DESCRIPTION               |    6 +++---
 MD5                       |   12 ++++++------
 NEWS.md                   |    6 +++---
 R/helpers.R               |   30 ++++++++++++++++++++++++++++++
 R/read_gpx.R              |   17 ++++++++++++++---
 man/read_gpx.Rd           |   13 +++++++++++--
 tests/testthat/test-gpx.R |    8 ++++++--
 7 files changed, 73 insertions(+), 19 deletions(-)

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New package sawnuti with initial version 0.1.0
Package: sawnuti
Title: Comparing Sequences with Non-Uniform Time Intervals
Version: 0.1.0
Date: 2021-11-06
Description: The SAWNUTI algorithm performs sequence comparison for finite sequences of discrete events with non-uniform time intervals. Further description of the algorithm can be found in the paper: A. Murph, A. Flynt, B. R. King (2021). Comparing finite sequences of discrete events with non-uniform time intervals, Sequential Analysis, 40(3), 291-313. <doi:10.1080/07474946.2021.1940491>.
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2021-11-07 14:20:33 UTC; murph
Author: Alexander Murph [aut, cre]
Maintainer: Alexander Murph <acm026@bucknell.edu>
Repository: CRAN
Date/Publication: 2021-11-08 15:50:02 UTC

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New package robnptests with initial version 1.0.0
Package: robnptests
Version: 1.0.0
Title: Robust Nonparametric Two-Sample Tests for Location/Scale
Author: Sermad Abbas [aut, cre] (<https://orcid.org/0000-0001-9162-9792>), Barbara Brune [aut] (<https://orcid.org/0000-0002-3154-8445>), Roland Fried [aut]
Maintainer: Sermad Abbas <abbas@statistik.tu-dortmund.de>
BugReports: https://github.com/s-abbas/robnptests/issues
Description: Implementations of several robust nonparametric two-sample tests for location or scale differences. The test statistics are based on robust location and scale estimators, e.g. the sample median or the Hodges-Lehmann estimators as described in Fried & Dehling (2011) <doi:10.1007/s10260-011-0164-1>. The p-values can be computed via the permutation principle, the randomization principle, or by using the asymptotic distributions of the test statistics under the null hypothesis, which ensures (approximate) distribution independence of the test decision. To test for a difference in scale, we apply the tests for location difference to transformed observations; see Fried (2012) <doi:10.1016/j.csda.2011.02.012>. Random noise on a small range can be added to the original observations in order to hold the significance level on data from discrete distributions. The location tests assume homoscedasticity and the scale tests require the location parameters to be zero.
License: GPL (>= 2)
Depends: R (>= 4.0.0)
URL: https://github.com/s-abbas/robnptests
Encoding: UTF-8
Imports: Rdpack, gtools, robustbase, statmod, stats, utils, checkmate
RdMacros: Rdpack
Suggests: testthat, knitr, rmarkdown, usethis, covr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-11-07 14:02:23 UTC; abbas
Repository: CRAN
Date/Publication: 2021-11-08 15:40:02 UTC

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Package MixedPsy updated to version 1.1.0 with previous version 1.0.0 dated 2017-11-16

Title: Statistical Tools for the Analysis of Psychophysical Data
Description: Tools for the analysis of psychophysical data in R. This package allows to estimate the Point of Subjective Equivalence (PSE) and the Just Noticeable Difference (JND), either from a psychometric function or from a Generalized Linear Mixed Model (GLMM). Additionally, the package allows plotting the fitted models and the response data, simulating psychometric functions of different shapes, and simulating data sets. For a description of the use of GLMMs applied to psychophysical data, refer to Moscatelli et al. (2012).
Author: Alessandro Moscatelli [aut, cre] (<https://orcid.org/0000-0001-6269-4536>), Priscilla Balestrucci [aut] (<https://orcid.org/0000-0002-5764-9439>)
Maintainer: Alessandro Moscatelli <moskante@gmail.com>

Diff between MixedPsy versions 1.0.0 dated 2017-11-16 and 1.1.0 dated 2021-11-08

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 MixedPsy-1.1.0/MixedPsy/R/psych_utils.R       |  342 +++++++++++++++-----------
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 MixedPsy-1.1.0/MixedPsy/README.md             |    8 
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 MixedPsy-1.1.0/MixedPsy/man/MixDelta.Rd       |   68 ++---
 MixedPsy-1.1.0/MixedPsy/man/MixPlot.Rd        |   65 ++--
 MixedPsy-1.1.0/MixedPsy/man/PsySimulate.Rd    |   54 ++--
 MixedPsy-1.1.0/MixedPsy/man/PsychDelta.Rd     |   48 +--
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 MixedPsy-1.1.0/MixedPsy/man/pseMer.Rd         |   99 +++----
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 MixedPsy-1.1.0/MixedPsy/man/vibro_exp3.Rd     |   24 -
 MixedPsy-1.1.0/MixedPsy/man/xplode.Rd         |   37 --
 30 files changed, 717 insertions(+), 767 deletions(-)

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New package IxPopDyMod with initial version 0.1.0
Package: IxPopDyMod
Title: Framework for Tick Population and Infection Modeling
Version: 0.1.0
Maintainer: Myles Stokowski <mylesstokowski@gmail.com>
Description: Code to specify, run, and then visualize and analyze the results of Ixodidae (hard-bodied ticks) population and infection dynamics models. Such models exist in the literature, but the source code to run them is not always available. 'IxPopDyMod' provides an easy way for these models to be written and shared.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://github.com/dallenmidd/IxPopDyMod
Depends: R (>= 3.2.4)
Suggests: knitr, rmarkdown
Imports: magrittr, rlang, ggplot2, stringr, dplyr, tidyr, igraph, readr, yaml, tibble
Language: en-US
NeedsCompilation: no
Packaged: 2021-11-07 02:37:02 UTC; myles
Author: Myles Stokowski [aut, cre], David Allen [aut] (<https://orcid.org/0000-0002-0712-9603>)
Repository: CRAN
Date/Publication: 2021-11-08 15:30:11 UTC

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New package HierPorfolios with initial version 0.1.0
Package: HierPorfolios
Title: Hierarchical Clustering-Based Portfolio Allocation Strategies
Version: 0.1.0
Author: Carlos Trucios
Maintainer: Carlos Trucios <ctrucios@gmail.com>
Description: Machine learning portfolio allocation strategies based on hierarchical clustering methods. The implemented methods are: Hierarchical risk parity (De Prado, 2016) <DOI: 10.3905/jpm.2016.42.4.059> and Hierarchical clustering-based asset allocation (Raffinot, 2017) <DOI: 10.3905/jpm.2018.44.2.089>.
License: GPL-2
Depends: R (>= 3.6.0)
Imports: fastcluster, cluster, RiskPortfolios
Encoding: UTF-8
LazyData: true
URL: https://github.com/ctruciosm/HierPorfolios
BugReports: https://github.com/ctruciosm/HierPorfolios/issues
NeedsCompilation: no
Packaged: 2021-11-06 21:12:19 UTC; ctruciosm
Repository: CRAN
Date/Publication: 2021-11-08 15:30:14 UTC

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New package gstsm with initial version 0.0.1
Package: gstsm
Title: Generalized Spatial-Time Sequence Miner
Version: 0.0.1
Description: Implementations of the algorithms present in the future article Generalized Discovery of Tight Space-Time Sequences, original title (Castro Filho, A. J. ; Borges, H. ; Pacitti, Esther ; Porto, F. ; Coutinho, R. ; Ogasawara, E. . Generalização de Mineração de Sequências Restritas no Espaço e no Tempo. In: XXXVI SBBD - Simpósio Brasileiro de Banco de Dados, 2021).
License: MIT + file LICENSE
Encoding: UTF-8
Imports: digest
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2021-11-07 00:28:40 UTC; cassio
Author: Cássio Souza [aut, cre], Jorge Rodrigues [aut], Eduardo Ogasawara [ctb] (<https://orcid.org/0000-0002-0466-0626>), Antonio Filho [ctb], CEFET/RJ [cph]
Maintainer: Cássio Souza <cassiofb.souza@gmail.com>
Repository: CRAN
Date/Publication: 2021-11-08 15:30:02 UTC

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Package fflr updated to version 2.0.0 with previous version 1.9.2 dated 2021-10-05

Title: Retrieve ESPN Fantasy Football Data
Description: Format the raw data from the ESPN fantasy football API <https://fantasy.espn.com/apis/v3/games/ffl/> as data frames. Retrieve data on public leagues, rosters, athletes, and matches.
Author: Kiernan Nicholls [aut, cre, cph]
Maintainer: Kiernan Nicholls <kiernann@protonmail.com>

Diff between fflr versions 1.9.2 dated 2021-10-05 and 2.0.0 dated 2021-11-08

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 96 files changed, 1444 insertions(+), 888 deletions(-)

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New package ctpm with initial version 1.0.1
Encoding: UTF-8
Package: ctpm
Version: 1.0.1
Date: 2021-11-03
Title: Continuous-Time Phylogenetic Modeling
Maintainer: Michael J. Noonan <michael.noonan@ubc.ca>
URL: https://github.com/NoonanM/ctpm,
Depends: R (>= 3.5.0), ape, ctmm
Imports: slouch, ClusterR, methods, stats, utils
Suggests: phytools, viridis, knitr, rmarkdown, nlme, progress, graphics, grDevices,
Description: Functions for identifying, fitting, and applying continuous-time stochastic models to phylogenetic data. The package is based on methods introduced in Noonan et al. (2021) <doi:10.1101/2021.05.21.445056>.
License: GPL-3
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-11-05 05:31:50 UTC; michaelnoonan
Author: Michael J. Noonan [aut, cre], Christen H. Fleming [aut]
Repository: CRAN
Date/Publication: 2021-11-08 15:30:05 UTC

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New package bigQF with initial version 1.5
Package: bigQF
Title: Quadratic Forms in Large Matrices
Version: 1.5
Author: Thomas Lumley
Maintainer: Thomas Lumley <t.lumley@auckland.ac.nz>
Description: A computationally-efficient leading-eigenvalue approximation to tail probabilities and quantiles of large quadratic forms, in particular for the Sequence Kernel Association Test (SKAT) used in genomics <doi:10.1002/gepi.22136>. Also provides stochastic singular value decomposition for dense or sparse matrices.
URL: https://github.com/tslumley/bigQF
Imports: svd, CompQuadForm, Matrix, stats, coxme
Suggests: knitr, rmarkdown, SKAT
VignetteBuilder: knitr
Depends: R (>= 2.10), methods
License: GPL-2
NeedsCompilation: yes
Packaged: 2021-11-07 03:47:15 UTC; tlum005
Repository: CRAN
Date/Publication: 2021-11-08 15:30:08 UTC

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Package mongolite updated to version 2.4.0 with previous version 2.3.1 dated 2021-04-30

Title: Fast and Simple 'MongoDB' Client for R
Description: High-performance MongoDB client based on 'mongo-c-driver' and 'jsonlite'. Includes support for aggregation, indexing, map-reduce, streaming, encryption, enterprise authentication, and GridFS. The online user manual provides an overview of the available methods in the package: <https://jeroen.github.io/mongolite/>.
Author: Jeroen Ooms [aut, cre] (<https://orcid.org/0000-0002-4035-0289>), MongoDB, Inc [cph] (Bundled mongo-c-driver, see AUTHORS file)
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between mongolite versions 2.3.1 dated 2021-04-30 and 2.4.0 dated 2021-11-08

 mongolite-2.3.1/mongolite/src/mongoc/mongoc-collection-be47088b.o.tmp                |only
 mongolite-2.3.1/mongolite/tools                                                      |only
 mongolite-2.4.0/mongolite/DESCRIPTION                                                |    6 
 mongolite-2.4.0/mongolite/MD5                                                        |  304 +
 mongolite-2.4.0/mongolite/NEWS                                                       |    6 
 mongolite-2.4.0/mongolite/R/mongo.R                                                  |    4 
 mongolite-2.4.0/mongolite/cleanup                                                    |    2 
 mongolite-2.4.0/mongolite/configure                                                  |   63 
 mongolite-2.4.0/mongolite/inst/WORDLIST                                              |   29 
 mongolite-2.4.0/mongolite/man/mongo.Rd                                               |    4 
 mongolite-2.4.0/mongolite/src/Makevars.in                                            |    8 
 mongolite-2.4.0/mongolite/src/Makevars.win                                           |   31 
 mongolite-2.4.0/mongolite/src/bson/bcon.c                                            |    4 
 mongolite-2.4.0/mongolite/src/bson/bson-atomic.c                                     |   22 
 mongolite-2.4.0/mongolite/src/bson/bson-atomic.h                                     |   16 
 mongolite-2.4.0/mongolite/src/bson/bson-clock.c                                      |    2 
 mongolite-2.4.0/mongolite/src/bson/bson-config.h                                     |    1 
 mongolite-2.4.0/mongolite/src/bson/bson-context.c                                    |    6 
 mongolite-2.4.0/mongolite/src/bson/bson-decimal128.c                                 |    2 
 mongolite-2.4.0/mongolite/src/bson/bson-json-private.h                               |only
 mongolite-2.4.0/mongolite/src/bson/bson-json.c                                       |  188 -
 mongolite-2.4.0/mongolite/src/bson/bson-json.h                                       |   26 
 mongolite-2.4.0/mongolite/src/bson/bson-macros.h                                     |   12 
 mongolite-2.4.0/mongolite/src/bson/bson-md5.c                                        |    6 
 mongolite-2.4.0/mongolite/src/bson/bson-types.h                                      |   14 
 mongolite-2.4.0/mongolite/src/bson/bson-utf8.c                                       |    2 
 mongolite-2.4.0/mongolite/src/bson/bson-version.h                                    |    6 
 mongolite-2.4.0/mongolite/src/bson/bson.c                                            |  300 +
 mongolite-2.4.0/mongolite/src/bson/bson.h                                            |   27 
 mongolite-2.4.0/mongolite/src/client.c                                               |   12 
 mongolite-2.4.0/mongolite/src/common/common-b64-private.h                            |   37 
 mongolite-2.4.0/mongolite/src/common/common-b64.c                                    |   53 
 mongolite-2.4.0/mongolite/src/common/common-config.h                                 |only
 mongolite-2.4.0/mongolite/src/common/common-macros-private.h                         |only
 mongolite-2.4.0/mongolite/src/common/common-md5-private.h                            |   11 
 mongolite-2.4.0/mongolite/src/common/common-md5.c                                    |   16 
 mongolite-2.4.0/mongolite/src/common/common-prelude.h                                |    7 
 mongolite-2.4.0/mongolite/src/common/common-thread-private.h                         |   79 
 mongolite-2.4.0/mongolite/src/common/common-thread.c                                 |only
 mongolite-2.4.0/mongolite/src/mongo_log.c                                            |   11 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-apm-private.h                            |   26 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-apm.c                                    |  245 +
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-apm.h                                    |   18 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-async-cmd-private.h                      |    2 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-async-cmd.c                              |    7 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-async.c                                  |    2 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-buffer.c                                 |   54 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-bulk-operation.c                         |    9 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-change-stream-private.h                  |    7 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-change-stream.c                          |   99 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-client-pool.c                            |  105 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-client-pool.h                            |    5 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-client-private.h                         |   54 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-client-session-private.h                 |   20 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-client-session.c                         |  250 +
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-client-session.h                         |    9 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-client-side-encryption.c                 |   13 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-client.c                                 |  430 +-
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-client.h                                 |   15 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-cluster-aws-private.h                    |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-cluster-aws.c                            |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-cluster-cyrus.c                          |   54 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-cluster-private.h                        |   42 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-cluster-sasl.c                           |    5 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-cluster-sspi.c                           |   22 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-cluster.c                                | 1563 ++++++----
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-cmd-private.h                            |   17 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-cmd.c                                    |  147 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-collection-private.h                     |   12 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-collection.c                             |  613 ++-
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-config.h                                 |   55 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-crypt.c                                  |  144 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-crypto-cng.c                             |   42 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-cursor-legacy.c                          |   18 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-cursor-private.h                         |    6 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-cursor.c                                 |   54 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-cyrus-private.h                          |    4 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-cyrus.c                                  |   82 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-database-private.h                       |    2 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-database.c                               |   70 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-error-private.h                          |   54 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-error.c                                  |  249 +
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-error.h                                  |   13 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-find-and-modify.c                        |    5 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-flags-private.h                          |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-flags.h                                  |    4 
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 mongolite-2.4.0/mongolite/src/mongoc/mongoc-generation-map.c                         |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-gridfs-bucket-file.c                     |  123 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-gridfs-bucket.c                          |    4 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-gridfs-file.c                            |    3 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-gridfs.c                                 |   31 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-handshake-private.h                      |    8 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-handshake.c                              |   66 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-handshake.h                              |    2 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-host-list-private.h                      |   13 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-host-list.c                              |   75 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-http-private.h                           |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-http.c                                   |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-init.c                                   |   24 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-interrupt-private.h                      |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-interrupt.c                              |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-linux-distro-scanner.c                   |    3 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-log.c                                    |   10 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-ocsp-cache-private.h                     |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-ocsp-cache.c                             |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-openssl-private.h                        |   20 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-openssl.c                                |  520 +++
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-optional.c                               |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-optional.h                               |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-opts-private.h                           |   30 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-opts.c                                   |  192 +
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-rand-cng.c                               |    4 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-rand-openssl.c                           |   12 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-read-prefs-private.h                     |    1 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-read-prefs.c                             |   81 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-read-prefs.h                             |    4 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-rpc-private.h                            |    5 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-rpc.c                                    |   67 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-scram-private.h                          |    1 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-scram.c                                  |   31 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-secure-channel.c                         |   42 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-secure-transport-private.h               |    3 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-secure-transport.c                       |    9 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-server-api-private.h                     |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-server-api.c                             |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-server-api.h                             |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-server-description-private.h             |   71 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-server-description.c                     |  362 ++
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-server-description.h                     |    7 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-server-monitor-private.h                 |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-server-monitor.c                         |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-socket.c                                 |   15 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-ssl-private.h                            |   22 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-ssl.c                                    |   48 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-ssl.h                                    |    3 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-stream-tls-libressl.c                    |   11 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-stream-tls-openssl-private.h             |   13 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-stream-tls-openssl.c                     |   88 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-stream-tls-secure-channel.c              |   77 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-stream-tls-secure-transport.c            |  238 +
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-stream.c                                 |   34 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-thread-private.h                         |   23 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-timeout-private.h                        |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-timeout.c                                |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-topology-background-monitoring-private.h |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-topology-background-monitoring.c         |only
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-topology-description-apm.c               |   38 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-topology-description-private.h           |    9 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-topology-description.c                   |  194 +
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-topology-private.h                       |  136 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-topology-scanner-private.h               |   55 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-topology-scanner.c                       |  335 +-
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-topology.c                               | 1092 ++++--
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-trace-private.h                          |   22 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-uri-private.h                            |   31 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-uri.c                                    |  365 +-
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-uri.h                                    |    7 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-util-private.h                           |   27 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-util.c                                   |   82 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-version.h                                |    6 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-write-command-legacy.c                   |   79 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-write-command-private.h                  |    7 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-write-command.c                          |   72 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc-write-concern.c                          |    2 
 mongolite-2.4.0/mongolite/src/mongoc/mongoc.h                                        |   77 
 mongolite-2.4.0/mongolite/src/osx/Makevars                                           |    5 
 167 files changed, 8101 insertions(+), 2900 deletions(-)

More information about mongolite at CRAN
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Package lightr updated to version 1.6.1 with previous version 1.6.0 dated 2021-07-22

Title: Read Spectrometric Data and Metadata
Description: Parse various reflectance/transmittance/absorbance spectra file formats to extract spectral data and metadata, as described in Gruson, White & Maia (2019) <doi:10.21105/joss.01857>. Among other formats, it can import files from 'Avantes' <https://www.avantes.com/>, 'CRAIC' <https://www.microspectra.com/>, and 'OceanInsight' (formerly 'OceanOptics') <https://www.oceaninsight.com/> brands.
Author: Hugo Gruson [cre, aut, cph] (<https://orcid.org/0000-0002-4094-1476>), Rafael Maia [aut, cph] (<https://orcid.org/0000-0002-7563-9795>), Thomas White [aut, cph] (<https://orcid.org/0000-0002-3976-1734>), Kotya Karapetyan [ctb, cph] (Author of the MATLAB script to read AvaSoft7 binary files (CC-BY))
Maintainer: Hugo Gruson <hugo.gruson+R@normalesup.org>

Diff between lightr versions 1.6.0 dated 2021-07-22 and 1.6.1 dated 2021-11-08

 lightr-1.6.0/lightr/tests/testthat/compare_official.R               |only
 lightr-1.6.0/lightr/tests/testthat/compare_photobiologyInOut.R      |only
 lightr-1.6.1/lightr/DESCRIPTION                                     |    8 -
 lightr-1.6.1/lightr/MD5                                             |   54 +++++-----
 lightr-1.6.1/lightr/NEWS.md                                         |    6 +
 lightr-1.6.1/lightr/R/get_spec.R                                    |    3 
 lightr-1.6.1/lightr/R/parse_avantes_binary.R                        |   37 ++++--
 lightr-1.6.1/lightr/R/parse_avantes_converted.R                     |   15 ++
 lightr-1.6.1/lightr/R/parse_generic.R                               |   18 ++-
 lightr-1.6.1/lightr/R/parse_jdx.R                                   |    6 -
 lightr-1.6.1/lightr/R/parse_oceanoptics_converted.R                 |   36 ++++--
 lightr-1.6.1/lightr/R/parse_procspec.R                              |    8 -
 lightr-1.6.1/lightr/R/parse_spc.R                                   |    6 -
 lightr-1.6.1/lightr/build/partial.rdb                               |binary
 lightr-1.6.1/lightr/build/vignette.rds                              |binary
 lightr-1.6.1/lightr/inst/doc/batch_import.html                      |    4 
 lightr-1.6.1/lightr/inst/doc/renormalise.html                       |    4 
 lightr-1.6.1/lightr/inst/doc/true_example.html                      |    4 
 lightr-1.6.1/lightr/man/lr_get_spec.Rd                              |    3 
 lightr-1.6.1/lightr/man/lr_parse_generic.Rd                         |   18 ++-
 lightr-1.6.1/lightr/man/lr_parse_jaz.Rd                             |   29 +++--
 lightr-1.6.1/lightr/man/lr_parse_jdx.Rd                             |    6 -
 lightr-1.6.1/lightr/man/lr_parse_procspec.Rd                        |    8 -
 lightr-1.6.1/lightr/man/lr_parse_spc.Rd                             |    6 -
 lightr-1.6.1/lightr/man/lr_parse_trm.Rd                             |   37 ++++--
 lightr-1.6.1/lightr/man/lr_parse_ttt.Rd                             |   15 ++
 lightr-1.6.1/lightr/tests/testthat/test_compare_official.R          |only
 lightr-1.6.1/lightr/tests/testthat/test_compare_photobiologyInOut.R |only
 lightr-1.6.1/lightr/tests/testthat/test_dispatch.R                  |    1 
 lightr-1.6.1/lightr/tests/testthat/test_parsers.R                   |    2 
 30 files changed, 222 insertions(+), 112 deletions(-)

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New package tidylab with initial version 4.1.1
Package: tidylab
Title: Shared Infrastructure of 'Tidylab' Package Collection
Version: 4.1.1
Date: 2021-10-10
Maintainer: Harel Lustiger <tidylab@gmail.com>
Description: Selection of packages designed to be loaded in concert. The 'tidylab' package collection revolves around project development and deployment. The purpose of this is to make it easy to install and subsequently load those packages.
License: MIT + file LICENSE
URL: https://tidylab.github.io/tidylab/, https://github.com/tidylab/tidylab
BugReports: https://github.com/tidylab/tidylab/issues
Depends: R (>= 3.3)
Imports: cli (>= 2.4.0), crayon (>= 1.4.1), decorators, dplyr (>= 1.0.5), microservices, purrr (>= 0.3.4), rstudioapi (>= 0.13), tibble (>= 3.1.0), usethat
Suggests: testthat (>= 3.0.0), withr
Encoding: UTF-8
Language: en-GB
LazyData: true
NeedsCompilation: no
Packaged: 2021-11-05 23:20:17 UTC; Alpha
Author: Harel Lustiger [aut, cre] (<https://orcid.org/0000-0003-2953-9598>), Tidylab [cph, fnd]
Repository: CRAN
Date/Publication: 2021-11-08 12:10:02 UTC

More information about tidylab at CRAN
Permanent link

New package refer with initial version 0.1.0
Package: refer
Title: Create Object References
Version: 0.1.0
Author: Christopher Mann <cmann3@unl.edu>
Maintainer: Christopher Mann <cmann3@unl.edu>
Description: Allows users to easily create references to R objects then 'dereference' when needed or modify in place without using reference classes, environments, or active bindings as workarounds. Users can also create expression references that allow subsets of any object to be referenced or expressions containing references to multiple objects.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: utils, stats, eList, matchr
Suggests: knitr, rmarkdown
Language: en-US
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-11-06 15:54:28 UTC; chris
Repository: CRAN
Date/Publication: 2021-11-08 12:10:04 UTC

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New package MaximinInfer with initial version 1.0.0
Package: MaximinInfer
Title: Inference for Maximin Effect in High-Dimensional Settings
Version: 1.0.0
Author: Zhenyu Wang; Zijian Guo
Maintainer: Zhenyu Wang <wangzy0701@gmail.com>
Description: Implementation of the sampling and aggregation method for the covariate shift maximin effect, which was proposed in <arXiv:2011.07568>. It constructs the confidence interval for any linear combination of the high-dimensional maximin effect.
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown
Imports: MASS, stats, CVXR, glmnet, intervals, SIHR
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2021-11-05 21:34:52 UTC; Zhenyu Wang
Repository: CRAN
Date/Publication: 2021-11-08 12:10:15 UTC

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New package lddmm with initial version 0.1.0
Package: lddmm
Title: Longitudinal Drift-Diffusion Mixed Models (LDDMM)
Version: 0.1.0
Date: 2021-11-02
Description: Implementation of the drift-diffusion mixed model for category learning as described in Paulon et al. (2021).
Depends: R (>= 3.5.0)
Language: en-US
License: MIT + file LICENSE
Encoding: UTF-8
Imports: Rcpp (>= 1.0.6), RcppProgress, rgen, gtools, LaplacesDemon, dplyr, plyr, tidyr, ggplot2, latex2exp, reshape2, RColorBrewer
LazyData: true
LinkingTo: Rcpp, RcppArmadillo, RcppProgress, rgen
Suggests: rmarkdown, knitr
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-11-06 15:30:40 UTC; giorgio
Author: Giorgio Paulon [aut, cre], Abhra Sarkar [aut, ctb]
Maintainer: Giorgio Paulon <giorgio.paulon@utexas.edu>
Repository: CRAN
Date/Publication: 2021-11-08 12:10:08 UTC

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New package kairos with initial version 1.0.0
Package: kairos
Title: Analysis of Chronological Patterns from Archaeological Count Data
Version: 1.0.0
Description: A toolkit for absolute dating and analysis of chronological patterns. This package includes functions for chronological modeling and dating of archaeological assemblages from count data. It allows to compute time point estimates and density estimates of the occupation and duration of an archaeological site.
License: GPL (>= 3)
URL: https://packages.tesselle.org/kairos/, https://github.com/tesselle/kairos
BugReports: https://github.com/tesselle/kairos/issues
Depends: R (>= 3.4)
Imports: arkhe (>= 0.4.0), dimensio (>= 0.2.2), extraDistr, ggplot2, methods, rlang, stats, utils
Suggests: covr, folio, knitr, rmarkdown, testthat (>= 3.0.0), vdiffr (>= 1.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-11-06 11:38:24 UTC; nicolas
Author: Nicolas Frerebeau [aut, cre] (<https://orcid.org/0000-0001-5759-4944>, Université Bordeaux Montaigne), Brice Lebrun [ctb] (<https://orcid.org/0000-0001-7503-8685>, Université Bordeaux Montaigne), Ben Marwick [ctb] (<https://orcid.org/0000-0001-7879-4531>, University of Washington), Anne Philippe [ctb] (<https://orcid.org/0000-0002-5331-5087>, Université de Nantes)
Maintainer: Nicolas Frerebeau <nicolas.frerebeau@u-bordeaux-montaigne.fr>
Repository: CRAN
Date/Publication: 2021-11-08 12:10:11 UTC

More information about kairos at CRAN
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New package cvap with initial version 0.0.3
Package: cvap
Title: Citizen Voting Age Population
Version: 0.0.3
Description: Works with the Citizen Voting Age Population special tabulation from the US Census Bureau. Provides tools to download and process raw data. Also provides a downloading interface to processed data. Implements a very basic approach to estimate block level citizen voting age population from block group data.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: censable, cli, dplyr, fs, magrittr, readr, stringr, tidyr
URL: https://github.com/christopherkenny/cvap, https://www.christophertkenny.com/cvap/
BugReports: https://github.com/christopherkenny/cvap/issues
Depends: R (>= 2.10)
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2021-11-06 19:19:42 UTC; chris
Author: Christopher T. Kenny [aut, cre] (<https://orcid.org/0000-0002-9386-6860>)
Maintainer: Christopher T. Kenny <christopherkenny@fas.harvard.edu>
Repository: CRAN
Date/Publication: 2021-11-08 12:30:02 UTC

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Package pacotest updated to version 0.4.1 with previous version 0.4.0 dated 2020-12-15

Title: Testing for Partial Copulas and the Simplifying Assumption in Vine Copulas
Description: Routines for two different test types, the Constant Conditional Correlation (CCC) test and the Vectorial Independence (VI) test are provided (Kurz and Spanhel (2017) <arXiv:1706.02338>). The tests can be applied to check whether a conditional copula coincides with its partial copula. Functions to test whether a regular vine copula satisfies the so-called simplifying assumption or to test a single copula within a regular vine copula to be a (j-1)-th order partial copula are available. The CCC test comes with a decision tree approach to allow testing in high-dimensional settings.
Author: Malte S. Kurz [aut, cre]
Maintainer: Malte S. Kurz <malte.simon.kurz@uni-hamburg.de>

Diff between pacotest versions 0.4.0 dated 2020-12-15 and 0.4.1 dated 2021-11-08

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 pacotest-0.4.1/pacotest/DESCRIPTION                                                               |    7 
 pacotest-0.4.1/pacotest/LICENSE                                                                   |    2 
 pacotest-0.4.1/pacotest/MD5                                                                       |   59 +-
 pacotest-0.4.1/pacotest/NEWS.md                                                                   |    6 
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 pacotest-0.4.1/pacotest/src/pacotest_R_HelpingFunctions.cpp                                       |    7 
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 pacotest-0.4.1/pacotest/tests/testthat/test_chi2Statistic.R                                       |   24 
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Package mstate updated to version 0.3.2 with previous version 0.3.1 dated 2020-12-17

Title: Data Preparation, Estimation and Prediction in Multi-State Models
Description: Contains functions for data preparation, descriptives, hazard estimation and prediction with Aalen-Johansen or simulation in competing risks and multi-state models, see Putter, Fiocco, Geskus (2007) <doi:10.1002/sim.2712>.
Author: Hein Putter [aut, cre], Liesbeth C. de Wreede [aut], Marta Fiocco [aut], Ronald B. Geskus [ctb], Edouard F. Bonneville [aut], Damjan Manevski [ctb]
Maintainer: Hein Putter <H.Putter@lumc.nl>

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Package hierbase updated to version 0.1.2 with previous version 0.1.1 dated 2021-11-03

Title: Enabling Hierarchical Multiple Testing
Description: Implementation of hierarchical inference based on Meinshausen (2008). Hierarchical testing of variable importance. Biometrika, 95(2), 265-278 and Renaux, Buzdugan, Kalisch, and Bühlmann, (2020). Hierarchical inference for genome-wide association studies: a view on methodology with software. Computational Statistics, 35(1), 1-40. The R-package 'hierbase' offers tools to perform hierarchical inference for one or multiple data sets based on ready-to-use (group) test functions or alternatively a user specified (group) test function. The procedure is based on a hierarchical multiple testing correction and controls the family-wise error rate (FWER). The functions can easily be run in parallel. Hierarchical inference can be applied to (low- or) high-dimensional data sets to find significant groups or single variables (depending on the signal strength and correlation structure) in a data-driven and automated procedure. Possible applications can for example be found in statistical genetics and statistical genomics.
Author: Claude Renaux [aut, cre], Peter Bühlmann [ths]
Maintainer: Claude Renaux <renaux@stat.math.ethz.ch>

Diff between hierbase versions 0.1.1 dated 2021-11-03 and 0.1.2 dated 2021-11-08

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More information about hierbase at CRAN
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Package apollo updated to version 0.2.6 with previous version 0.2.5 dated 2021-07-31

Title: Tools for Choice Model Estimation and Application
Description: The Choice Modelling Centre (CMC) at the University of Leeds has developed flexible code for the estimation and application of choice models in R. Users are able to write their own model functions or use a mix of already available ones. Random heterogeneity, both continuous and discrete and at the level of individuals and choices, can be incorporated for all models. There is support for both standalone models and hybrid model structures. Both classical and Bayesian estimation is available, and multiple discrete continuous models are covered in addition to discrete choice. Multi-threading processing is supported for estimation and a large number of pre and post-estimation routines, including for computing posterior (individual-level) distributions are available. For examples, a manual, and a support forum, visit <http://www.ApolloChoiceModelling.com>. For more information on choice models see Train, K. (2009) <isbn:978-0-521-74738-7> and Hess, S. & Daly, A.J. (2014) <isbn:978-1-781-00314-5> for an overview of the field.
Author: Stephane Hess [aut], David Palma [aut, cre], Thomas Hancock [ctb]
Maintainer: David Palma <D.Palma@leeds.ac.uk>

Diff between apollo versions 0.2.5 dated 2021-07-31 and 0.2.6 dated 2021-11-08

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More information about apollo at CRAN
Permanent link

Package antaresEditObject updated to version 0.3.0 with previous version 0.2.2 dated 2021-06-21

Title: Edit an 'Antares' Simulation
Description: Edit an 'Antares' simulation before running it : create new areas, links, thermal clusters or binding constraints or edit existing ones. Update 'Antares' general & optimization settings. 'Antares' is an open source power system generator, more information available here : <https://antares-simulator.org/>.
Author: Veronique Bachelier [aut, cre], Frederic Breant [aut], Victor Perrier [aut], Baptiste Seguinot [ctb], Benoit Thieurmel [ctb], Titouan Robert [ctb], Jalal-Edine Zawam [ctb], Etienne Sanchez [ctb], Janus De Bondt [ctb], RTE [cph]
Maintainer: Veronique Bachelier <veronique.bachelier@rte-france.com>

Diff between antaresEditObject versions 0.2.2 dated 2021-06-21 and 0.3.0 dated 2021-11-08

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Package datasailr updated to version 0.8.10 with previous version 0.8.9 dated 2021-08-25

Title: Row by Row Data Processing Tool, Using 'DataSailr' Script
Description: A row by row data processing tool. You can write data processing code in 'DataSailr' script which is specially intended for data manipulation. The package uses 'libsailr' (C/C++ library) for its 'DataSailr' code parsing and its execution.
Author: Toshihiro Umehara [aut, cre], Troy Hanson [cph, ctb] (uthash), Howard Hinnant [cph, ctb] (date.h), Adrian Colomitchi [cph, ctb] (date.h), Florian Dang [cph, ctb] (date.h), Paul Thompson [cph, ctb] (date.h), Tomasz Kamiński [cph, ctb] (date.h), Nemanja Trifunovic [cph, ctb] (utfcpp), Kim Grasman [cph, ctb] (getopt_port), Jon Clayden [cph, ctb] (ore package), K.Kosako [cph, ctb] (onigmo author), K.Takata [cph, ctb] (onigmo author), Byte [cph, ctb] (onigmo contributor), KUBO Takehiro [cph, ctb] (onigmo contributor), Free Software Foundation, Inc [cph], X Consortium [cph]
Maintainer: Toshihiro Umehara <toshi@niceume.com>

Diff between datasailr versions 0.8.9 dated 2021-08-25 and 0.8.10 dated 2021-11-08

 DESCRIPTION  |    8 ++++----
 MD5          |    8 ++++----
 NEWS.md      |    5 +++++
 configure    |   18 +++++++++---------
 configure.ac |    6 +++---
 5 files changed, 25 insertions(+), 20 deletions(-)

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Package clustree updated to version 0.4.4 with previous version 0.4.3 dated 2020-06-14

Title: Visualise Clusterings at Different Resolutions
Description: Deciding what resolution to use can be a difficult question when approaching a clustering analysis. One way to approach this problem is to look at how samples move as the number of clusters increases. This package allows you to produce clustering trees, a visualisation for interrogating clusterings as resolution increases.
Author: Luke Zappia [aut, cre] (<https://orcid.org/0000-0001-7744-8565>), Alicia Oshlack [aut] (<https://orcid.org/0000-0001-9788-5690>), Andrea Rau [ctb], Paul Hoffman [ctb] (<https://orcid.org/0000-0002-7693-8957>)
Maintainer: Luke Zappia <luke@lazappi.id.au>

Diff between clustree versions 0.4.3 dated 2020-06-14 and 0.4.4 dated 2021-11-08

 DESCRIPTION                            |   10 
 MD5                                    |   18 
 NEWS.md                                |    8 
 R/datasets.R                           |    2 
 README.md                              |    8 
 build/vignette.rds                     |binary
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 10 files changed, 256 insertions(+), 395 deletions(-)

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Package tinyarray updated to version 2.2.7 with previous version 2.2.6 dated 2021-09-14

Title: Expression Data Analysis and Visualization
Description: Gene Expression Omnibus(GEO) and The Cancer Genome Atlas(TCGA) are common bioinformatics public databases. We integrate the regular analysis and charts for expression data, to analyze and display the data concisely and intuitively.
Author: Xiaojie Sun [aut, cre]
Maintainer: Xiaojie Sun <18763899370@163.com>

Diff between tinyarray versions 2.2.6 dated 2021-09-14 and 2.2.7 dated 2021-11-08

 DESCRIPTION                |   11 ++--
 MD5                        |   10 ++--
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 6 files changed, 100 insertions(+), 42 deletions(-)

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Package HDTSA updated to version 1.0.1 with previous version 1.0.0 dated 2021-06-04

Title: High Dimensional Time Series Analysis Tools
Description: Procedures for high-dimensional time series analysis including factor analysis proposed by Lam and Yao (2012) <doi:10.1214/12-AOS970> and Chang, Guo and Yao (2015) <doi:10.1016/j.jeconom.2015.03.024>, martingale difference test proposed by Chang, Jiang and Shao (2021) preprint, principal component analysis proposed by Chang, Guo and Yao (2018) <doi:10.1214/17-AOS1613>, unit root test proposed by Chang, Cheng and Yao (2021) <arXiv:2006.07551> and white noise test proposed by Chang, Yao and Zhou (2017) <doi:10.1093/biomet/asw066>.
Author: Chen Lin [aut, cre], Guanghui Cheng [aut], Jinyuan Chang [aut], Qiwei Yao [aut]
Maintainer: Chen Lin <linchen@smail.swufe.edu.cn>

Diff between HDTSA versions 1.0.0 dated 2021-06-04 and 1.0.1 dated 2021-11-08

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 MD5                       |   24 ++--
 NAMESPACE                 |    1 
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 R/Tools_martingale.R      |    2 
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New package BayesCACE with initial version 1.0
Package: BayesCACE
Title: Bayesian Model for CACE Analysis
Version: 1.0
Date: 2021-11-01
Depends: R (>= 3.5.0), rjags (>= 4-6)
Imports: coda, Rdpack, grDevices, MASS, mvtnorm, forestplot, metafor, lme4
SystemRequirements: JAGS 4.x.y (http://mcmc-jags.sourceforge.net)
Description: Performs Complier Average Causal Effect analysis on either a single study or meta-analysis of datasets with binary outcomes using the Bayesian methods proposed in Zhou et al. (2019) <doi:10.1111/biom.13028> and Zhou et al. (2021) <doi:10.1080/01621459.2021.1900859>.
License: GPL (>= 2)
NeedsCompilation: no
RdMacros: Rdpack
Encoding: UTF-8
LazyData: true
Packaged: 2021-11-05 20:31:04 UTC; james
Author: Jinhui Yang [aut, cre] (<https://orcid.org/0000-0001-8322-1121>), Jincheng Zhou [aut] (<https://orcid.org/0000-0003-2641-2495>), James Hodges [ctb], Haitao Chu [ctb] (<https://orcid.org/0000-0003-0932-598X>)
Maintainer: Jinhui Yang <james.yangjinhui@gmail.com>
Repository: CRAN
Date/Publication: 2021-11-08 09:10:02 UTC

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New package wnominate with initial version 1.3
Package: wnominate
Version: 1.3
Date: 2021-11-05
Title: Roll Call Analysis Software
Author: Keith Poole <ktpoole@uga.edu>, Jeffrey Lewis <jblewis@ucla.edu>, James Lo <lojames@usc.edu> and Royce Carroll <rcarroll@rice.edu>
Maintainer: Jeffrey B. Lewis <jblewis@ucla.edu>
Depends: R (>= 2.3.1), pscl (>= 0.59)
Description: Estimates Poole and Rosenthal's (1985 <doi:10.2307/2111172>, 1991 <doi:10.2307/2111445>) W-NOMINATE scores from roll call votes supplied though a 'rollcall' object from the 'pscl' package.
License: GPL-2
Repository: CRAN
Date/Publication: 2021-11-08 08:30:02 UTC
Packaged: 2021-11-08 01:47:42 UTC; jeffreylewis
NeedsCompilation: yes

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New package topicmodels.etm with initial version 0.1.0
Package: topicmodels.etm
Title: Topic Modelling in Embedding Spaces
Version: 0.1.0
Maintainer: Jan Wijffels <jwijffels@bnosac.be>
Description: Find topics in texts which are semantically embedded using techniques like word2vec or Glove. This topic modelling technique models each word with a categorical distribution whose natural parameter is the inner product between a word embedding and an embedding of its assigned topic. The techniques are explained in detail in the paper 'Topic Modeling in Embedding Spaces' by Adji B. Dieng, Francisco J. R. Ruiz, David M. Blei (2019), available at <arXiv:1907.04907>.
License: MIT + file LICENSE
Encoding: UTF-8
SystemRequirements: LibTorch (https://pytorch.org/)
Depends: R (>= 2.10)
Imports: graphics, stats, Matrix, torch (>= 0.5.0)
Suggests: udpipe (>= 0.8.4), word2vec, uwot, tinytest, textplot (>= 0.2.0), ggrepel, ggalt
NeedsCompilation: no
Packaged: 2021-11-05 11:01:22 UTC; Jan
Author: Jan Wijffels [aut, cre, cph] (R implementation), BNOSAC [cph] (R implementation), Adji B. Dieng [ctb, cph] (original Python implementation in inst/orig), Francisco J. R. Ruiz [ctb, cph] (original Python implementation in inst/orig), David M. Blei [ctb, cph] (original Python implementation in inst/orig)
Repository: CRAN
Date/Publication: 2021-11-08 08:40:02 UTC

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New package steprf with initial version 1.0.0
Package: steprf
Title: Stepwise Predictive Variable Selection for Random Forest
Version: 1.0.0
Date: 2021-10-28
Description: An introduction to several novel predictive variable selection methods for random forest. They are based on various variable importance methods (i.e., averaged variable importance (AVI), and knowledge informed AVI (i.e., KIAVI, and KIAVI2)) and predictive accuracy in stepwise algorithms. For details of the variable selection methods, please see: Li, J., Siwabessy, J., Huang, Z. and Nichol, S. (2019) <doi:10.3390/geosciences9040180>. Li, J., Alvarez, B., Siwabessy, J., Tran, M., Huang, Z., Przeslawski, R., Radke, L., Howard, F., Nichol, S. (2017). <DOI: 10.13140/RG.2.2.27686.22085>.
Depends: R (>= 4.0)
Imports: spm, randomForest, spm2, psy
License: GPL (>= 2)
Encoding: UTF-8
Suggests: knitr, rmarkdown, lattice, reshape2
NeedsCompilation: no
Packaged: 2021-11-05 00:52:25 UTC; Jin
Author: Jin Li [aut, cre]
Maintainer: Jin Li <jinli68@gmail.com>
Repository: CRAN
Date/Publication: 2021-11-08 08:40:05 UTC

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New package RGremlinsConjoint with initial version 0.9.0
Package: RGremlinsConjoint
Title: Estimate the "Gremlins in the Data" Model for Conjoint Studies
Version: 0.9.0
Description: The tools and utilities to estimate the model described in "Gremlin's in the Data: Identifying the Information Content of Research Subjects" (Howell et al. (2021) <doi:10.1177/0022243720965930>) using conjoint analysis data such as that collected in Sawtooth Software's 'Lighthouse' or 'Discover' products. Additional utilities are included for formatting the input data.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown, testthat
Depends: R (>= 2.10)
Imports: bayesm
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-11-05 19:57:46 UTC; jrhowell
Author: John Howell [aut, cre], Peter Ebbes [aut], John Leichty [aut]
Maintainer: John Howell <john_howell@byu.edu>
Repository: CRAN
Date/Publication: 2021-11-08 09:00:05 UTC

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Package powerly updated to version 1.7.1 with previous version 1.5.2 dated 2021-09-30

Title: Sample Size Analysis for Psychological Networks and More
Description: An implementation of the sample size computation method for network models proposed by Constantin et al. (2021) <doi:10.31234/osf.io/j5v7u>. The implementation takes the form of a three-step recursive algorithm designed to find an optimal sample size given a model specification and a performance measure of interest. It starts with a Monte Carlo simulation step for computing the performance measure and a statistic at various sample sizes selected from an initial sample size range. It continues with a monotone curve-fitting step for interpolating the statistic across the entire sample size range. The final step employs stratified bootstrapping to quantify the uncertainty around the fitted curve.
Author: Mihai Constantin [aut, cre] (<https://orcid.org/0000-0002-6460-0107>)
Maintainer: Mihai Constantin <mihai@mihaiconstantin.com>

Diff between powerly versions 1.5.2 dated 2021-09-30 and 1.7.1 dated 2021-11-08

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New package openeo with initial version 1.1.0
Package: openeo
Title: Client Interface for 'openEO' Servers
Version: 1.1.0
Description: Access data and processing functionalities of 'openEO' compliant back-ends in R.
Depends: R (>= 3.3)
Suggests: tibble, testthat, knitr, sf, geojsonsf, pkgdown, rmarkdown
Imports: jsonlite, httr, methods, R6, lubridate, base64enc
Encoding: UTF-8
LazyData: false
BugReports: https://github.com/Open-EO/openeo-r-client/issues
URL: https://github.com/Open-EO/openeo-r-client
VignetteBuilder: knitr
License: Apache License (>= 2)
NeedsCompilation: no
Packaged: 2021-11-05 17:11:19 UTC; fla
Author: Florian Lahn [aut, cre], Peter James Zellner [ctb]
Maintainer: Florian Lahn <florian.lahn@eftas.com>
Repository: CRAN
Date/Publication: 2021-11-08 08:50:02 UTC

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New package GenMarkov with initial version 0.1.0
Package: GenMarkov
Title: Multivariate Markov Chains
Version: 0.1.0
Maintainer: Carolina Vasconcelos <cvasconcelos@novaims.unl.pt>
Description: Provides routines to estimate the Mixture Transition Distribution Model based on Raftery (1985) <http://www.jstor.org/stable/2345788> and Nicolau (2014) <doi:10.1111/sjos.12087> specifications, for multivariate data. Additionally, provides a function for the estimation of a new model for multivariate non-homogeneous Markov chains. This new specification, Generalized Multivariate Markov Chains (GMMC) was proposed by Carolina Vasconcelos and Bruno Damasio and considers (continuous or discrete) covariates exogenous to the Markov chain.
License: GPL (>= 2)
Encoding: UTF-8
Imports: alabama (>= 2015.3-1), fastDummies (>= 1.6.3), Hmisc (>= 4.5-0), matrixcalc (>= 1.0-3), maxLik (>= 1.4-8), nnet (>= 7.3-16), stats (>= 4.1.0)
NeedsCompilation: no
Packaged: 2021-11-05 12:44:22 UTC; Carolina
Author: Carolina Vasconcelos [aut, cre], Bruno Damasio [aut]
Repository: CRAN
Date/Publication: 2021-11-08 08:50:08 UTC

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New package FracKrigingR with initial version 1.0.0
Package: FracKrigingR
Title: Spatial Multivariate Data Modeling
Version: 1.0.0
Copyright: Vilnius University Institute of Data Science and Digital Technologies
Author: Neringa Urbonaite [aut, cre], Leonidas Sakalauskas [aut]
Maintainer: Neringa Urbonaite <neringa.urbonaite@mif.vu.lt>
Description: Aim is to provide fractional Brownian vector field generation algorithm, Hurst parameter estimation method and fractional kriging model for multivariate data modeling.
License: GPL-2
Encoding: UTF-8
URL: https://github.com/NidaGreen/FracKriging
Imports: psych, clusterGeneration, graphics, stats
Suggests: knitr, gstat, sp, rmarkdown, raster
NeedsCompilation: no
Packaged: 2021-11-05 13:42:32 UTC; nerin
Repository: CRAN
Date/Publication: 2021-11-08 08:40:08 UTC

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Package xgboost updated to version 1.5.0.1 with previous version 1.4.1.1 dated 2021-04-22

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

Diff between xgboost versions 1.4.1.1 dated 2021-04-22 and 1.5.0.1 dated 2021-11-08

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Package wooldridge updated to version 1.4-2 with previous version 1.4-1 dated 2021-06-24

Title: 115 Data Sets from "Introductory Econometrics: A Modern Approach, 7e" by Jeffrey M. Wooldridge
Description: Students learning both econometrics and R may find the introduction to both challenging. The wooldridge data package aims to lighten the task by efficiently loading any data set found in the text with a single command. Data sets have been compressed to a fraction of their original size. Documentation files contain page numbers, the original source, time of publication, and notes from the author suggesting avenues for further analysis and research. If one needs an introduction to R model syntax, a vignette contains solutions to examples from chapters of the text. Data sets are from the 7th edition (Wooldridge 2020, ISBN-13: 978-1-337-55886-0), and are backwards compatible with all previous versions of the text.
Author: Justin M. Shea [aut, cre], Kennth H. Brown [ctb]
Maintainer: Justin M. Shea <jshea@roosevelt.edu>

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Package autostsm updated to version 2.0 with previous version 1.6 dated 2021-08-12

Title: Automatic Structural Time Series Models
Description: Automatic model selection for structural time series decomposition into trend, cycle, and seasonal components, plus optionality for structural interpolation, using the Kalman filter. Koopman, Siem Jan and Marius Ooms (2012) "Forecasting Economic Time Series Using Unobserved Components Time Series Models" <doi:10.1093/oxfordhb/9780195398649.013.0006>. Kim, Chang-Jin and Charles R. Nelson (1999) "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications" <doi:10.7551/mitpress/6444.001.0001><http://econ.korea.ac.kr/~cjkim/>.
Author: Alex Hubbard
Maintainer: Alex Hubbard <hubbard.alex@gmail.com>

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Package stoRy updated to version 0.2.0 with previous version 0.1.5 dated 2020-06-11

Title: Download, Explore, and Analyze Literary Theme Ontology Data
Description: Download, explore, and analyze Literary Theme Ontology themes and thematically annotated story data. To learn more about the project visit <https://github.com/theme-ontology/theming> and <https://themeontology.org>.
Author: Paul Sheridan [aut, cre] (<https://orcid.org/0000-0002-5484-1951>), Oshan Modi [aut], Mikael Onsjö [aut]
Maintainer: Paul Sheridan <paul.sheridan.stats@gmail.com>

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 87 files changed, 425 insertions(+), 189 deletions(-)

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