Thu, 06 Aug 2020

Package survHE updated to version 1.1 with previous version 1.0.65 dated 2018-11-09

Title: Survival Analysis in Health Economic Evaluation
Description: Contains a suite of functions for survival analysis in health economics. These can be used to run survival models under a frequentist (based on maximum likelihood) or a Bayesian approach (both based on Integrated Nested Laplace Approximation or Hamiltonian Monte Carlo). The user can specify a set of parametric models using a common notation and select the preferred mode of inference. The results can also be post-processed to produce probabilistic sensitivity analysis and can be used to export the output to an Excel file (e.g. for a Markov model, as often done by modellers and practitioners).
Author: Gianluca Baio [aut, cre]
Maintainer: Gianluca Baio <gianluca@stats.ucl.ac.uk>

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Package nntrf updated to version 0.1.3 with previous version 0.1.2 dated 2020-07-27

Title: Supervised Data Transformation by Means of Neural Network Hidden Layer
Description: A supervised transformation of datasets is performed. The aim is similar to that of Principal Component Analysis (PCA), that is, to carry out data transformation and dimensionality reduction, but in a supervised way. This is achieved by first training a 3-layer Multi-Layer Perceptron and then using the activations of the hidden layer as a transformation of the input features. In fact, it takes advantage of the change of representation provided by the hidden layer of a neural network. This can be useful as data pre-processing for Machine Learning methods in general, specially for those that do not work well with many irrelevant or redundant features. It uses the nnet package under the hood. Rumelhart, D.E., Hinton, G.E. and Williams, R.J. (1986) "Learning representations by back-propagating errors" <doi:10.1038/323533a0>.
Author: Ricardo Aler [aut, cre], Jose Valls [aut], Ines Galvan [aut], David Camacho [aut]
Maintainer: Ricardo Aler <ricardo.aler@uc3m.es>

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Package nanotime updated to version 0.3.0 with previous version 0.2.4 dated 2019-05-25

Title: Nanosecond-Resolution Time for R
Description: Full 64-bit resolution date and time support with resolution up to nanosecond granularity is provided, with easy transition to and from the standard 'POSIXct' type.
Author: Dirk Eddelbuettel and Leonardo Silvestri
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package journalabbr updated to version 0.2.2 with previous version 0.2.1 dated 2020-07-27

Title: Journal Abbreviations for BibTeX Documents
Description: Since the reference management software (such as 'Zotero', 'Mendeley') exports Bib file journal abbreviation is not detailed enough, the 'journalabbr' package only abbreviates the journal field of Bib file, and then outputs a new Bib file for generating reference format with journal abbreviation on other software (such as 'texstudio'). The abbreviation table is from 'JabRef'. At the same time, 'Shiny' application is provided to generate 'thebibliography', a reference format that can be directly used for latex paper writing based on 'Rmd' files.
Author: ShuCai Zou [aut, cre], Yu Chen [aut]
Maintainer: ShuCai Zou <zscmoyujian@163.com>

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Package PINSPlus updated to version 2.0.5 with previous version 2.0.4 dated 2020-05-30

Title: Clustering Algorithm for Data Integration and Disease Subtyping
Description: Provides a robust approach for omics data integration and disease subtyping. PINSPlus is fast and supports the analysis of large datasets with hundreds of thousands of samples and features. The software automatically determines the optimal number of clusters and then partitions the samples in a way such that the results are robust against noise and data perturbation (Nguyen et.al. (2019) <DOI: 10.1093/bioinformatics/bty1049>, Nguyen et.al. (2017)<DOI: 10.1101/gr.215129.116>).
Author: Hung Nguyen, Bang Tran, Duc Tran and Tin Nguyen
Maintainer: Hung Nguyen <hungnp@nevada.unr.edu>

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Package rjdqa updated to version 0.1.1 with previous version 0.1.0 dated 2019-06-17

Title: Quality Assessment for Seasonal Adjustment
Description: Add-in to the 'RJDemetra' package on seasonal adjustments. It allows to produce quality assessments outputs (dashboards, quality report matrix, etc.).
Author: Alain Quartier-la-Tente [aut, cre] (<https://orcid.org/0000-0001-7890-3857>)
Maintainer: Alain Quartier-la-Tente <alain.quartier@yahoo.fr>

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Package PlaneGeometry updated to version 1.2.0 with previous version 1.1.0 dated 2020-02-24

Title: Plane Geometry
Description: An extensive set of plane geometry routines. Provides R6 classes representing triangles, circles, circular arcs, ellipses, elliptical arcs and lines, and their plot methods. Also provides R6 classes representing transformations: rotations, reflections, homotheties, scalings, general affine transformations, inversions, Möbius transformations.
Author: Stéphane Laurent
Maintainer: Stéphane Laurent <laurent_step@outlook.fr>

Diff between PlaneGeometry versions 1.1.0 dated 2020-02-24 and 1.2.0 dated 2020-08-06

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Package FCSlib updated to version 1.1.1 with previous version 1.1.0 dated 2020-02-12

Title: A Collection of Fluorescence Fluctuation Spectroscopy Methods
Description: A set of tools for fluorescence fluctuation spectroscopy data analysis performance is provided in this package. It includes techniques such as single-point fluorescence correlation spectroscopy, autocorrelation and pair correlation functions, number & brightness (raster line scan) and a novel, recently developed method by Hinde and co-workers, pair correlation of molecular brightness (doi:10.1038/ncomms11047). A set of simulations and real experimental data is used for the examples of each function provided in this package. For an in-depth description of the basics behind each function here included and a detailed step-by-step guide on how to use them on your own data, please refer to the Supplementary Material file provided at (<https://github.com/RPintoC/FCSlib>).
Author: Raul Pinto Camara, Adan Guerrero.
Maintainer: Raul Pinto Camara <vasto.lorde.rp@gmail.com>

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Package calpassapi updated to version 0.0.3 with previous version 0.0.2 dated 2018-08-27

Title: R Interface to Access CalPASS API
Description: Implements methods for querying data from CalPASS using its API. CalPASS Plus. MMAP API V1. <https://mmap.calpassplus.org/docs/index.html>.
Author: Vinh Nguyen [aut, cre]
Maintainer: Vinh Nguyen <nguyenvq714@gmail.com>

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New package torch with initial version 0.0.1
Package: torch
Type: Package
Title: Tensors and Neural Networks with 'GPU' Acceleration
Version: 0.0.1
Authors@R: c( person("Daniel", "Falbel", email = "daniel@rstudio.com", role = c("aut", "cre", "cph")), person("Javier", "Luraschi", email = "javier@rstudio.com", role = c("aut", "cph")), person("Dmitriy", "Selivanov", role = c("ctb")), person("Athos", "Damiani", role = c("ctb")), person(family = "RStudio", role = c("cph")) )
Description: Provides functionality to define and train neural networks similar to 'PyTorch' by Paszke et al (2019) <arXiv:1912.01703> but written entirely in R using the 'libtorch' library. Also supports low-level tensor operations and 'GPU' acceleration.
License: MIT + file LICENSE
URL: http://mlverse.github.io/torch, https://github.com/mlverse/torch
BugReports: https://github.com/mlverse/torch/issues
Encoding: UTF-8
LazyData: true
SystemRequirements: C++11, LibTorch (https://pytorch.org/)
LinkingTo: Rcpp
Imports: Rcpp, R6, withr, rlang, methods, utils, stats
RoxygenNote: 7.1.1
Suggests: testthat (>= 2.1.0), covr, knitr, rmarkdown, bit64, magrittr, glue
VignetteBuilder: knitr
Collate: 'R7.R' 'RcppExports.R' 'tensor.R' 'autograd.R' 'backends.R' 'codegen-utils.R' 'conditions.R' 'creation-ops.R' 'cuda.R' 'device.R' 'dimname_list.R' 'dtype.R' 'gen-method.R' 'gen-namespace-docs.R' 'gen-namespace-examples.R' 'gen-namespace.R' 'generator.R' 'help.R' 'indexing.R' 'install.R' 'lantern_load.R' 'lantern_sync.R' 'layout.R' 'memory_format.R' 'utils-data.R' 'nn.R' 'nn-activation.R' 'nn-batchnorm.R' 'nn-conv.R' 'nn-dropout.R' 'nn-init.R' 'nn-linear.R' 'nn-loss.R' 'nn-pooling.R' 'nn-rnn.R' 'nn-sparse.R' 'nn-utils-rnn.R' 'nn-utils.R' 'nn_adaptive.R' 'nnf-activation.R' 'nnf-batchnorm.R' 'nnf-conv.R' 'nnf-distance.R' 'nnf-dropout.R' 'nnf-embedding.R' 'nnf-fold.R' 'nnf-instancenorm.R' 'nnf-linear.R' 'nnf-loss.R' 'nnf-normalization.R' 'nnf-padding.R' 'nnf-pixelshuffle.R' 'nnf-pooling.R' 'nnf-upsampling.R' 'nnf-vision.R' 'operators.R' 'optim.R' 'optim-adam.R' 'optim-sgd.R' 'package.R' 'qscheme.R' 'quantization.R' 'reduction.R' 'save.R' 'scalar.R' 'storage.R' 'tensor_list.R' 'tensor_options.R' 'utils-data-collate.R' 'utils-data-dataloader.R' 'utils-data-enum.R' 'utils-data-fetcher.R' 'utils-data-sampler.R' 'utils.R' 'variable_list.R' 'with-indices.R' 'wrapers.R'
NeedsCompilation: yes
Packaged: 2020-07-30 19:28:10 UTC; dfalbel
Author: Daniel Falbel [aut, cre, cph], Javier Luraschi [aut, cph], Dmitriy Selivanov [ctb], Athos Damiani [ctb], RStudio [cph]
Maintainer: Daniel Falbel <daniel@rstudio.com>
Repository: CRAN
Date/Publication: 2020-08-06 14:40:02 UTC

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New package RoBMA with initial version 1.0.3
Package: RoBMA
Title: Robust Bayesian Meta-Analyses
Version: 1.0.3
Maintainer: František Bartoš <f.bartos96@gmail.com>
Authors@R: c( person("František", "Bartoš", role = c("aut", "cre"), email = "f.bartos96@gmail.com", comment = c(ORCID = "0000-0002-0018-5573")), person("Maximilian", "Maier", role = "aut", email = "maximilianmaier0401@gmail.com", comment = c(ORCID = "0000-0002-9873-6096")), person("Eric-Jan", "Wagenmakers", role = "ths", comment = c(ORCID = "0000-0003-1596-1034")), person("Joris", "Goosen", role = "ctb") )
Description: A framework for estimating ensembles of meta-analytic models (assuming either presence or absence of the effect, heterogeneity, and publication bias) and using Bayesian model averaging to combine them. The ensembles use Bayes Factors to test for the presence or absence of the individual components (e.g., effect vs. no effect) and model-averages parameter estimates based on posterior model probabilities (Maier, Bartoš & Wagenmakers, 2020, <doi:10.31234/osf.io/u4cns>). The user can define a wide range of non-informative or informative priors for the effect size, heterogeneity, and weight functions. The package provides convenient functions for summary, visualizations, and fit diagnostics.
URL: https://fbartos.github.io/RoBMA/
BugReports: https://github.com/FBartos/RoBMA/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Imports: runjags, bridgesampling, rjags, coda, psych, stats, graphics, extraDistr, scales, DPQ, callr, Rdpack
Suggests: ggplot2, rstan, metaBMA, testthat, vdiffr, knitr, rmarkdown
RdMacros: Rdpack
LinkingTo: BH
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-07-31 14:41:52 UTC; Frantisek
Author: František Bartoš [aut, cre] (<https://orcid.org/0000-0002-0018-5573>), Maximilian Maier [aut] (<https://orcid.org/0000-0002-9873-6096>), Eric-Jan Wagenmakers [ths] (<https://orcid.org/0000-0003-1596-1034>), Joris Goosen [ctb]
Repository: CRAN
Date/Publication: 2020-08-06 14:40:15 UTC

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New package Phenotype with initial version 0.1.0
Package: Phenotype
Type: Package
Title: A Tool for Phenotypic Data Processing
Version: 0.1.0
Authors@R: person(given = "Peng", family = "Zhao", email = "pengzhao@nwafu.edu.cn", role = c("aut", "cre"))
Maintainer: Peng Zhao <pengzhao@nwafu.edu.cn>
Description: Large-scale phenotypic data processing is essential in research. Researchers need to eliminate outliers from the data in order to obtain true and reliable results. Best linear unbiased prediction (BLUP) is a standard method for estimating random effects of a mixed model. This method can be used to process phenotypic data under different conditions and is widely used in animal and plant breeding. The 'Phenotype' can remove outliers from phenotypic data and performs the best linear unbiased prediction (BLUP), help researchers quickly complete phenotypic data analysis. H.P.Piepho. (2008) <doi:10.1007/s10681-007-9449-8>.
License: Artistic-2.0
Encoding: UTF-8
LazyData: true
URL: https://github.com/biozhp/Phenotype
BugReports: https://github.com/biozhp/Phenotype/issues
Depends: R (>= 3.5.0)
Imports: lme4, tidyr
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-07-31 08:03:53 UTC; Misosugar
Author: Peng Zhao [aut, cre]
Repository: CRAN
Date/Publication: 2020-08-06 14:40:19 UTC

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Package nsarfima updated to version 0.2.0.0 with previous version 0.1.0.0 dated 2019-09-20

Title: Methods for Fitting and Simulating Non-Stationary ARFIMA Models
Description: Routines for fitting and simulating data under autoregressive fractionally integrated moving average (ARFIMA) models, without the constraint of covariance stationarity. Two fitting methods are implemented, a pseudo-maximum likelihood method and a minimum distance estimator. Mayoral, L. (2007) <doi:10.1111/j.1368-423X.2007.00202.x>. Beran, J. (1995) <doi:10.1111/j.2517-6161.1995.tb02054.x>.
Author: Benjamin Groebe [aut, cre]
Maintainer: Benjamin Groebe <ben.groebe@gmail.com>

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New package fairml with initial version 0.2
Package: fairml
Type: Package
Title: Fair Models in Machine Learning
Version: 0.2
Date: 2020-07-30
Depends: R (>= 3.5.0)
Imports: methods, optiSolve
Suggests: lattice
Author: Marco Scutari [aut, cre]
Maintainer: Marco Scutari <marco.scutari@gmail.com>
Description: Fair machine learning regression models which take sensitive attributes into account in model estimation. Currently implementing Komiyama et al. (2018) <http://proceedings.mlr.press/v80/komiyama18a/komiyama18a.pdf>.
License: MIT + file LICENSE
LazyData: yes
NeedsCompilation: no
Packaged: 2020-07-30 09:55:37 UTC; fizban
Repository: CRAN
Date/Publication: 2020-08-06 14:10:03 UTC

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Package CONCUR updated to version 1.3 with previous version 1.2 dated 2020-03-25

Title: Copy Number Profile Curve-Based Association Test
Description: Implements a kernel-based association test for copy number variation (CNV) aggregate analysis in a certain genomic region (e.g., gene set, chromosome, or genome) that is robust to the within-locus and across-locus etiological heterogeneity, and bypass the need to define a "locus" unit for CNVs. Brucker, A., et al. (2020) <doi:10.1101/666875>.
Author: Amanda Brucker, Shannon T. Holloway, Jung-Ying Tzeng
Maintainer: Shannon T. Holloway <sthollow@ncsu.edu>

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Package mboost updated to version 2.9-3 with previous version 2.9-2.1 dated 2020-08-02

Title: Model-Based Boosting
Description: Functional gradient descent algorithm (boosting) for optimizing general risk functions utilizing component-wise (penalised) least squares estimates or regression trees as base-learners for fitting generalized linear, additive and interaction models to potentially high-dimensional data.
Author: Torsten Hothorn [aut] (<https://orcid.org/0000-0001-8301-0471>), Peter Buehlmann [aut], Thomas Kneib [aut], Matthias Schmid [aut], Benjamin Hofner [aut, cre] (<https://orcid.org/0000-0003-2810-3186>), Fabian Sobotka [ctb], Fabian Scheipl [ctb], Andreas Mayr [ctb]
Maintainer: Benjamin Hofner <benjamin.hofner@pei.de>

Diff between mboost versions 2.9-2.1 dated 2020-08-02 and 2.9-3 dated 2020-08-06

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Package RAthena updated to version 1.10.0 with previous version 1.9.1 dated 2020-07-02

Title: Connect to 'AWS Athena' using 'Boto3' ('DBI' Interface)
Description: Designed to be compatible with the R package 'DBI' (Database Interface) when connecting to Amazon Web Service ('AWS') Athena <https://aws.amazon.com/athena/>. To do this 'Python' 'Boto3' Software Development Kit ('SDK') <https://boto3.amazonaws.com/v1/documentation/api/latest/index.html> is used as a driver.
Author: Dyfan Jones [aut, cre]
Maintainer: Dyfan Jones <dyfan.r.jones@gmail.com>

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Package NTS updated to version 1.1.2 with previous version 1.1.1 dated 2020-08-05

Title: Nonlinear Time Series Analysis
Description: Simulation, estimation, prediction procedure, and model identification methods for nonlinear time series analysis, including threshold autoregressive models, Markov-switching models, convolutional functional autoregressive models, nonlinearity tests, Kalman filters and various sequential Monte Carlo methods. More examples and details about this package can be found in the book "Nonlinear Time Series Analysis" by Ruey S. Tsay and Rong Chen, John Wiley & Sons, 2018 (ISBN: 978-1-119-26407-1).
Author: Ruey Tsay [aut], Rong Chen [aut], Xialu Liu [aut, cre]
Maintainer: Xialu Liu <xialu.liu@sdsu.edu>

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Package MSEtool updated to version 2.0.0 with previous version 1.7.0 dated 2020-06-24

Title: Management Strategy Evaluation Toolkit
Description: Simulation tools for management strategy evaluation are provided for the 'DLMtool' operating model to inform data-rich fisheries. 'MSEtool' provides complementary assessment models of varying complexity with standardized reporting, diagnostic tools for evaluating assessment models within closed-loop simulation, and helper functions for building more complex operating models and model-based management procedures.
Author: Quang Huynh [aut], Tom Carruthers [aut, cre], Adrian Hordyk [aut], Chris Grandin [ctb] (iSCAM functions)
Maintainer: Tom Carruthers <t.carruthers@oceans.ubc.ca>

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Package ipaddress updated to version 0.4.0 with previous version 0.3.0 dated 2020-05-12

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

Diff between ipaddress versions 0.3.0 dated 2020-05-12 and 0.4.0 dated 2020-08-06

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Package hts updated to version 6.0.1 with previous version 6.0.0 dated 2020-04-03

Title: Hierarchical and Grouped Time Series
Description: Provides methods for analysing and forecasting hierarchical and grouped time series. The available forecast methods include bottom-up, top-down, optimal combination reconciliation (Hyndman et al. 2011) <doi:10.1016/j.csda.2011.03.006>, and trace minimization reconciliation (Wickramasuriya et al. 2018) <doi:10.1080/01621459.2018.1448825>.
Author: Rob Hyndman [aut] (Package creator), Alan Lee [aut] (Fast computation using recursive methods), Earo Wang [aut, cre], Shanika Wickramasuriya [aut] (Reconciliation via trace minimization)
Maintainer: Earo Wang <earo.wang@gmail.com>

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Package hscovar updated to version 0.4.0 with previous version 0.2.1 dated 2020-04-15

Title: Calculation of Covariance Between Markers for Half-Sib Families
Description: The theoretical covariance between pairs of markers is calculated from either paternal haplotypes and maternal linkage disequilibrium (LD) or vise versa. A genetic map is required. Grouping of markers is based on the correlation matrix and a representative marker is suggested for each group. Employing the correlation matrix, optimal sample size can be derived for association studies based on a SNP-BLUP approach. The implementation relies on paternal half-sib families and biallelic markers. If maternal half-sib families are used, the roles of sire/dam are swapped. Multiple families can be considered. Wittenburg, Bonk, Doschoris, Reyer (2019) "Design of Experiments for Fine-Mapping Quantitative Trait Loci in Livestock Populations" <doi:10.1101/2019.12.17.879106>. Carlson, Eberle, Rieder, Yi, Kruglyak, Nickerson (2004) "Selecting a maximally informative set of single-nucleotide polymorphisms for association analyses using linkage disequilibrium" <doi:10.1086/381000>.
Author: Dörte Wittenburg [aut, cre], Michael Doschoris [aut], Jan Klosa [ctb]
Maintainer: Dörte Wittenburg <wittenburg@fbn-dummerstorf.de>

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Package socialmixr updated to version 0.1.7 with previous version 0.1.6 dated 2020-01-10

Title: Social Mixing Matrices for Infectious Disease Modelling
Description: Provides methods for sampling contact matrices from diary data for use in infectious disease modelling, as discussed in Mossong et al. (2008) <doi:10.1371/journal.pmed.0050074>.
Author: Sebastian Funk [aut, cre], Maria Bekker-Nielsen Dunbar [ctb], Carl A. B. Pearson [ctb], Sam Clifford [ctb], Christopher Jarvis [ctb], Alexis Robert [ctb]
Maintainer: Sebastian Funk <sebastian.funk@lshtm.ac.uk>

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Package shinybrms updated to version 1.3.0 with previous version 1.2.1 dated 2020-06-25

Title: Graphical User Interface ('Shiny' App) for Package 'brms'
Description: A graphical user interface (GUI) for fitting Bayesian regression models using the package 'brms' which in turn relies on 'Stan' (<https://mc-stan.org/>). The 'shinybrms' GUI is a 'Shiny' (<https://shiny.rstudio.com/>) app.
Author: Frank Weber [aut, cre] (<https://orcid.org/0000-0002-4842-7922>)
Maintainer: Frank Weber <fweber144@protonmail.com>

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Package oceanis updated to version 1.7.5 with previous version 1.7.4 dated 2020-07-03

Title: Cartography for Statistical Analysis
Description: Creating maps for statistical analysis such as proportional circles, chroropleth, typology and flows. Some functions use 'shiny' or 'leaflet' technologies for dynamism and interactivity. The great features are : - Create maps in a web environment where the parameters are modifiable on the fly ('shiny' and 'leaflet' technology). - Create interactive maps through zoom and pop-up ('leaflet' technology). - Create frozen maps with the possibility to add labels.
Author: Sébastien CALVET - PSAR-AT - DR Provence-Alpes-Cote d'Azur - INSEE [cre, aut], Sophie AUDRIC - PSAR-AT - DR Provence-Alpes-Cote d'Azur - INSEE [aut], SED - DR Hauts-de-France - INSEE [ctb], PSAR-SL - DR Auvergne-Rhone-Alpes - INSEE [ctb], PSAR-EEP - DR Occitanie - INSEE [ctb], SED - DR Pays-de-la-Loire - INSEE [ctb]
Maintainer: Sébastien CALVET <sebastien.calvet@insee.fr>

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 R/plot_ronds_classes.R                 |   16 +--
 R/plot_saphirs.R                       |   12 +-
 R/plot_typo.R                          |    6 -
 R/plot_typo_symboles.R                 |    8 -
 R/set_fonds_simples.R                  |    2 
 R/set_pop_up.R                         |   29 ++---
 R/shiny_classes.R                      |   50 ++++-----
 R/shiny_classes_ronds.R                |   68 ++++++------
 R/shiny_joignantes.R                   |   52 ++++-----
 R/shiny_oursins.R                      |   52 ++++-----
 R/shiny_ronds.R                        |   80 +++++++--------
 R/shiny_ronds_classes.R                |   68 ++++++------
 R/shiny_saphirs.R                      |   58 +++++-----
 R/shiny_typo.R                         |   48 ++++-----
 inst/doc/integration_shiny.html        |    4 
 inst/doc/oceanis.html                  |  176 ++++++++++++++++-----------------
 man/set_pop_up.Rd                      |   15 +-
 51 files changed, 893 insertions(+), 867 deletions(-)

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New package garma with initial version 0.9.2
Package: garma
Type: Package
Title: Fitting and Forecasting Gegenbauer ARMA Time Series Models
Version: 0.9.2
Date: 2020-07-26
Authors@R: person("Richard", "Hunt", email = "maint@huntemail.id.au", role = c("aut", "cre"))
Maintainer: Richard Hunt <maint@huntemail.id.au>
Description: Methods for estimating long memory-seasonal/cyclical Gegenbauer univariate time series processes. See for example (2018) <doi:10.1214/18-STS649>. Refer to the vignette for details of fitting these processes.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: assertthat, zoo, forecast, lubridate, FKF, signal, pracma, nloptr, Rsolnp, ggplot2, Rdpack (>= 0.7)
Suggests: longmemo, tidyverse, BB, GA, pso, dfoptim, testthat, knitr, rmarkdown
RoxygenNote: 7.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-08-02 02:21:38 UTC; richard
Author: Richard Hunt [aut, cre]
Repository: CRAN
Date/Publication: 2020-08-06 08:10:02 UTC

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New package qpmadr with initial version 0.1.0
Package: qpmadr
Type: Package
Title: Interface to the 'qpmad' Quadratic Programming Solver
Version: 0.1.0
Date: 2020-07-16
Authors@R: c(person("Eric", "Anderson", email="anderic1@gmx.com", role=c("aut","cre")), person("Alexander", "Sherikov", role=c("cph", "ctb")))
Description: Efficiently solve quadratic problems with linear inequality, equality and box constraints. The method used is outlined in D. Goldfarb, and A. Idnani (1983) <doi:10.1007/BF02591962>.
License: GPL (>= 3)
URL: https://github.com/anderic1/qpmadr
BugReports: https://github.com/anderic1/qpmadr/issues
Depends: R (>= 3.0.2)
Imports: Rcpp, checkmate
LinkingTo: Rcpp, RcppEigen (>= 0.3.3.3.0)
RoxygenNote: 7.1.0
Encoding: UTF-8
Suggests: tinytest
NeedsCompilation: yes
Packaged: 2020-07-17 06:33:08 UTC; hhh
Author: Eric Anderson [aut, cre], Alexander Sherikov [cph, ctb]
Maintainer: Eric Anderson <anderic1@gmx.com>
Repository: CRAN
Date/Publication: 2020-08-06 07:20:02 UTC

More information about qpmadr at CRAN
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Package miic (with last version 1.4.2) was removed from CRAN

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

2020-07-31 1.4.2
2020-07-22 1.4.0

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Package genvar (with last version 0.0.2.0) was removed from CRAN

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

2020-01-21 0.0.2.0
2019-10-13 0.0.1.4

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Package distillery updated to version 1.1 with previous version 1.0-7 dated 2020-04-17

Title: Method Functions for Confidence Intervals and to Distill Information from an Object
Description: Some very simple method functions for confidence interval calculation, bootstrap resampling aimed at atmospheric science applications, and to distill pertinent information from a potentially complex object; primarily used in common with packages extRemes and SpatialVx.
Author: Eric Gilleland
Maintainer: Eric Gilleland <ericg@ucar.edu>

Diff between distillery versions 1.0-7 dated 2020-04-17 and 1.1 dated 2020-08-06

 DESCRIPTION       |   10 +++++-----
 MD5               |    4 +++-
 R/MatrixSqrt.R    |only
 man/MatrixSqrt.Rd |only
 4 files changed, 8 insertions(+), 6 deletions(-)

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