Tue, 08 Nov 2022

Package rgdal updated to version 1.6-2 with previous version 1.5-32 dated 2022-05-10

Title: Bindings for the 'Geospatial' Data Abstraction Library
Description: Provides bindings to the 'Geospatial' Data Abstraction Library ('GDAL') (>= 1.11.4) and access to projection/transformation operations from the 'PROJ' library. Please note that 'rgdal' will be retired by the end of 2023, plan transition to sf/stars/'terra' functions using 'GDAL' and 'PROJ' at your earliest convenience. Use is made of classes defined in the 'sp' package. Raster and vector map data can be imported into R, and raster and vector 'sp' objects exported. The 'GDAL' and 'PROJ' libraries are external to the package, and, when installing the package from source, must be correctly installed first; it is important that 'GDAL' < 3 be matched with 'PROJ' < 6. From 'rgdal' 1.5-8, installed with to 'GDAL' >=3, 'PROJ' >=6 and 'sp' >= 1.4, coordinate reference systems use 'WKT2_2019' strings, not 'PROJ' strings. 'Windows' and 'macOS' binaries (including 'GDAL', 'PROJ' and their dependencies) are provided on 'CRAN'.
Author: Roger Bivand [cre, aut] , Tim Keitt [aut], Barry Rowlingson [aut, ctb], Edzer Pebesma [ctb], Michael Sumner [ctb], Robert Hijmans [ctb], Daniel Baston [ctb], Even Rouault [cph, ctb], Frank Warmerdam [cph, ctb], Jeroen Ooms [ctb], Colin Rundel [ctb]
Maintainer: Roger Bivand <Roger.Bivand@nhh.no>

Diff between rgdal versions 1.5-32 dated 2022-05-10 and 1.6-2 dated 2022-11-08

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Package rbmi (with last version 1.2.1) was removed from CRAN

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

2022-10-25 1.2.1
2022-05-18 1.1.4
2022-03-21 1.1.3
2022-03-08 1.1.1
2022-03-02 1.1.0

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Package hergm updated to version 4.1-10 with previous version 4.1-9 dated 2022-06-10

Title: Hierarchical Exponential-Family Random Graph Models
Description: Hierarchical exponential-family random graph models with local dependence. See Schweinberger and Luna (2018) <doi:10.18637/jss.v085.i01>.
Author: Michael Schweinberger [cre, aut], Mark S. Handcock [aut], Sergii Babkin [aut], Jonathan R. Stewart [aut], Duy Q. Vu [aut], Pamela Luna [ctb]
Maintainer: Michael Schweinberger <michael.schweinberger@psu.edu>

Diff between hergm versions 4.1-9 dated 2022-06-10 and 4.1-10 dated 2022-11-08

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Package transfR updated to version 1.0.1 with previous version 1.0.0 dated 2022-10-05

Title: Transfer of Hydrograph from Gauged to Ungauged Catchments
Description: A geomorphology-based hydrological modelling for transferring streamflow measurements from gauged to ungauged catchments. Inverse modelling enables to estimate net rainfall from streamflow measurements following Boudhraâ et al. (2018) <doi:10.1080/02626667.2018.1425801>. Resulting net rainfall is then estimated on the ungauged catchments by spatial interpolation in order to finally simulate streamflow following de Lavenne et al. (2016) <doi:10.1002/2016WR018716>.
Author: Alban de Lavenne [aut, cre] , Christophe Cudennec [ths] , Tom Loree [ctb], Herve Squividant [ctb]
Maintainer: Alban de Lavenne <alban.delavenne@inrae.fr>

Diff between transfR versions 1.0.0 dated 2022-10-05 and 1.0.1 dated 2022-11-08

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Package TDApplied updated to version 2.0.0 with previous version 0.1.3 dated 2022-10-02

Title: Machine Learning and Inference for Topological Data Analysis
Description: Topological data analysis is a powerful tool for finding non-linear global structure in whole datasets. 'TDApplied' aims to bridge topological data analysis with data, statistical and machine learning practitioners so that more analyses may benefit from the power of topological data analysis. The main tool of topological data analysis is persistent homology, which computes a shape descriptor of a dataset, called a persistence diagram. There are five goals of this package: (1) convert persistence diagrams computed using the two main R packages for topological data analysis into a data frame, (2) implement fast versions of both distance and kernel calculations for pairs of persistence diagrams, (3) provide methods for machine learning and inference for persistence diagrams which scale well, (4) deliver a fast implementation of persistent homology via a python interface, and (5) contribute tools for the interpretation of persistence diagrams.
Author: Shael Brown [aut, cre], Dr. Reza Farivar [aut, fnd]
Maintainer: Shael Brown <shaelebrown@gmail.com>

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Package pathviewr updated to version 1.1.5 with previous version 1.1.3 dated 2022-08-22

Title: Wrangle, Analyze, and Visualize Animal Movement Data
Description: Tools to import, clean, and visualize movement data, particularly from motion capture systems such as Optitrack's 'Motive', the Straw Lab's 'Flydra', or from other sources. We provide functions to remove artifacts, standardize tunnel position and tunnel axes, select a region of interest, isolate specific trajectories, fill gaps in trajectory data, and calculate 3D and per-axis velocity. For experiments of visual guidance, we also provide functions that use subject position to estimate perception of visual stimuli.
Author: Vikram B. Baliga [aut, cre] , Melissa S. Armstrong [aut] , Eric R. Press [aut] , Anne-Sophie Bonnet-Lebrun [rev], Marco Sciaini [rev]
Maintainer: Vikram B. Baliga <vbaliga87@gmail.com>

Diff between pathviewr versions 1.1.3 dated 2022-08-22 and 1.1.5 dated 2022-11-08

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Package ows4R updated to version 0.3-2 with previous version 0.3-1 dated 2022-08-19

Title: Interface to OGC Web-Services (OWS)
Description: Provides an Interface to Web-Services defined as standards by the Open Geospatial Consortium (OGC), including Web Feature Service (WFS) for vector data, Web Coverage Service (WCS), Catalogue Service (CSW) for ISO/OGC metadata, Web Processing Service (WPS) for data processes, and associated standards such as the common web-service specification (OWS) and OGC Filter Encoding. Partial support is provided for the Web Map Service (WMS). The purpose is to add support for additional OGC service standards such as Web Coverage Processing Service (WCPS), the Sensor Observation Service (SOS), or even new standard services emerging such OGC API or SensorThings.
Author: Emmanuel Blondel [aut, cre] , Alexandre Bennici [ctb] , Norbert Billet [ctb]
Maintainer: Emmanuel Blondel <emmanuel.blondel1@gmail.com>

Diff between ows4R versions 0.3-1 dated 2022-08-19 and 0.3-2 dated 2022-11-08

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Package odns updated to version 1.0.2 with previous version 1.0.1 dated 2022-08-07

Title: Access Scottish Health and Social Care Open Data
Description: Allows potential users of Scottish Health and Social Care Open Data (<https://www.opendata.nhs.scot/>) to easily explore and extract the available data.
Author: James Hardy [aut, cre]
Maintainer: James Hardy <jrh-dev@protonmail.com>

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Package netcmc updated to version 1.0.2 with previous version 1.0.1 dated 2022-06-28

Title: Spatio-Network Generalised Linear Mixed Models for Areal Unit and Network Data
Description: Implements a class of univariate and multivariate spatio-network generalised linear mixed models for areal unit and network data, with inference in a Bayesian setting using Markov chain Monte Carlo (MCMC) simulation. The response variable can be binomial, Gaussian, or Poisson. Spatial autocorrelation is modelled by a set of random effects that are assigned a conditional autoregressive (CAR) prior distribution following the Leroux model (Leroux et al. (2000) <doi:10.1007/978-1-4612-1284-3_4>). Network structures are modelled by a set of random effects that reflect a multiple membership structure (Browne et al. (2001) <doi:10.1177/1471082X0100100202>).
Author: George Gerogiannis, Mark Tranmer, Duncan Lee
Maintainer: George Gerogiannis <g.gerogiannis.1@research.gla.ac.uk>

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Package ncdfgeom updated to version 1.1.4 with previous version 1.1.3 dated 2022-07-14

Title: 'NetCDF' Geometry and Time Series
Description: Tools to create time series and geometry 'NetCDF' files.
Author: David Blodgett [aut, cre], Luke Winslow [ctb]
Maintainer: David Blodgett <dblodgett@usgs.gov>

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Package GOCompare updated to version 1.0.2 with previous version 1.0.1 dated 2022-04-29

Title: Comprehensive GO Terms Comparison Between Species
Description: Supports the assessment of functional enrichment analyses obtained for several lists of genes and provides a workflow to analyze them between two species via weighted graphs. Methods are described in Sosa et al. (2022) (Submitted to Genomics).
Author: Chrystian Camilo Sosa [aut, cre, cph] , Diana Carolina Clavijo-Buritica [aut], Mauricio Alberto Quimbaya [aut], Maria Victoria Diaz [ctb], Camila Riccio Rengifo [ctb], Nicolas Lopez-Rozo [ctb], Arlen James Mosquera [ctb], Andres Álvarez [ctb]
Maintainer: Chrystian Camilo Sosa <ccsosaa@javerianacali.edu.co>

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Package geoknife updated to version 1.6.9 with previous version 1.6.8 dated 2022-09-21

Title: Web-Processing of Large Gridded Datasets
Description: Processes gridded datasets found on the U.S. Geological Survey Geo Data Portal web application or elsewhere, using a web-enabled workflow that eliminates the need to download and store large datasets that are reliably hosted on the Internet. The package provides access to several data subset and summarization algorithms that are available on remote web processing servers (Read et al. (2015) <doi:10.1111/ecog.01880>).
Author: Jordan Read [aut], Jordan Walker [aut], Alison Appling [aut], David Blodgett [aut, cre], Emily Read [aut], Luke Winslow [aut], Lindsay Carr [aut], David Watkins [aut]
Maintainer: David Blodgett <dblodgett@usgs.gov>

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Package BAR updated to version 0.1.1 with previous version 0.1.0 dated 2022-11-07

Title: Bayesian Adaptive Randomization
Description: Bayesian adaptive randomization is also called outcome adaptive randomization, which is increasingly used in clinical trials.
Author: Chia-Wei Hsu [aut, cre], Haitao Pan [aut]
Maintainer: Chia-Wei Hsu <Chia-Wei.Hsu@stjude.org>

Diff between BAR versions 0.1.0 dated 2022-11-07 and 0.1.1 dated 2022-11-08

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Package photosynthesis updated to version 2.1.0 with previous version 2.0.3 dated 2022-08-12

Title: Tools for Plant Ecophysiology & Modeling
Description: Contains modeling and analytical tools for plant ecophysiology. MODELING: Simulate C3 photosynthesis using the Farquhar, von Caemmerer, Berry (1980) <doi:10.1007/BF00386231> model as described in Buckley and Diaz-Espejo (2015) <doi:10.1111/pce.12459>. It uses units to ensure that parameters are properly specified and transformed before calculations. Temperature response functions get automatically "baked" into all parameters based on leaf temperature following Bernacchi et al. (2002) <doi:10.1104/pp.008250>. The package includes boundary layer, cuticular, stomatal, and mesophyll conductances to CO2, which each can vary on the upper and lower portions of the leaf. Use straightforward functions to simulate photosynthesis over environmental gradients such as Photosynthetic Photon Flux Density (PPFD) and leaf temperature, or over trait gradients such as CO2 conductance or photochemistry. ANALYTICAL TOOLS: Fit ACi (Farquhar et al. (1980) <doi:10.1007/BF00386231>) and [...truncated...]
Author: Joseph Stinziano [aut] , Cassaundra Roback [aut], Demi Sargent [aut], Bridget Murphy [aut], Patrick Hudson [aut, dtc], Chris Muir [aut, cre]
Maintainer: Chris Muir <cdmuir@hawaii.edu>

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Package PAMpal updated to version 0.17.0 with previous version 0.16.0 dated 2022-03-06

Title: Load and Process Passive Acoustic Data
Description: Tools for loading and processing passive acoustic data. Read in data that has been processed in 'Pamguard' (<https://www.pamguard.org/>), apply a suite processing functions, and export data for reports or external modeling tools. Parameter calculations implement methods by Oswald et al (2007) <doi:10.1121/1.2743157>, Griffiths et al (2020) <doi:10.1121/10.0001229> and Baumann-Pickering et al (2010) <doi:10.1121/1.3479549>.
Author: Taiki Sakai [aut, cre], Jay Barlow [ctb], Emily Griffiths [ctb], Michael Oswald [ctb], Simone Baumann-Pickering [ctb], Julie Oswald [ctb]
Maintainer: Taiki Sakai <taiki.sakai@noaa.gov>

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Package BEKKs updated to version 1.4.0 with previous version 1.3.1 dated 2022-10-03

Title: Multivariate Conditional Volatility Modelling and Forecasting
Description: Methods and tools for estimating, simulating and forecasting of so-called BEKK-models (named after Baba, Engle, Kraft and Kroner) based on the fast Berndt–Hall–Hall–Hausman (BHHH) algorithm described in Hafner and Herwartz (2008) <doi:10.1007/s00184-007-0130-y>.
Author: Markus J. Fuelle [aut], Christian M. Hafner [aut], Helmut Herwartz [aut], Alexander Lange [aut, cre]
Maintainer: Alexander Lange <alexander.lange@uni-goettingen.de>

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Package RJafroc updated to version 2.1.2 with previous version 2.1.1 dated 2022-08-12

Title: Artificial Intelligence Systems and Observer Performance
Description: Analyzing the performance of artificial intelligence (AI) systems/algorithms characterized by a 'search-and-report' strategy. Historically observer performance has dealt with measuring radiologists' performances in search tasks, e.g., searching for lesions in medical images and reporting them, but the implicit location information has been ignored. The implemented methods apply to analyzing the absolute and relative performances of AI systems, comparing AI performance to a group of human readers or optimizing the reporting threshold of an AI system. In addition to performing historical receiver operating receiver operating characteristic (ROC) analysis (localization information ignored), the software also performs free-response receiver operating characteristic (FROC) analysis, where lesion localization information is used. A book using the software has been published: Chakraborty DP: Observer Performance Methods for Diagnostic Imaging - Foundations, Modeling, and Applications with R-B [...truncated...]
Author: Dev Chakraborty [cre, aut, cph], Peter Phillips [ctb], Xuetong Zhai [aut]
Maintainer: Dev Chakraborty <dpc10ster@gmail.com>

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Package pmparser updated to version 1.0.11 with previous version 1.0.10 dated 2022-04-28

Title: Create and Maintain a Relational Database of Data from PubMed/MEDLINE
Description: Provides a simple interface for extracting various elements from the publicly available PubMed XML files, incorporating PubMed's regular updates, and combining the data with the NIH Open Citation Collection. See Schoenbachler and Hughey (2021) <doi:10.7717/peerj.11071>.
Author: Jake Hughey [aut, cre], Josh Schoenbachler [aut], Elliot Outland [aut]
Maintainer: Jake Hughey <jakejhughey@gmail.com>

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Package CSCNet updated to version 0.1.2 with previous version 0.1.1 dated 2022-10-06

Title: Fitting and Tuning Regularized Cause-Specific Cox Models with Elastic-Net Penalty
Description: Flexible tools to fit, tune and obtain absolute risk predictions from regularized cause-specific cox models with elastic-net penalty.
Author: Shahin Roshani [aut, cre, cph]
Maintainer: Shahin Roshani <s.roshani@nki.nl>

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Package VFP updated to version 1.4.1 with previous version 1.4 dated 2021-12-20

Title: Variance Function Program
Description: Variance function estimation for models proposed by W. Sadler in his variance function program ('VFP', <http://www.aacb.asn.au/resources/useful-tools/variance-function-program-v14>). Here, the idea is to fit multiple variance functions to a data set and consequently assess which function reflects the relationship 'Var ~ Mean' best. For 'in-vitro diagnostic' ('IVD') assays modeling this relationship is of great importance when individual test-results are used for defining follow-up treatment of patients.
Author: Andre Schuetzenmeister [cre, aut], Florian Dufey [aut], Andrea Geistanger [ctb]
Maintainer: Andre Schuetzenmeister <andre.schuetzenmeister@roche.com>

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Package SpatialVx updated to version 1.0-1 with previous version 1.0 dated 2022-07-19

Title: Spatial Forecast Verification
Description: Spatial forecast verification refers to verifying weather forecasts when the verification set (forecast and observations) is on a spatial field, usually a high-resolution gridded spatial field. Most of the functions here require the forecast and observed fields to be gridded and on the same grid. For a thorough review of most of the methods in this package, please see Gilleland et al. (2009) <doi: 10.1175/2009WAF2222269.1> and for a tutorial on some of the main functions available here, see Gilleland (2022) <doi: 10.5065/4px3-5a05>.
Author: Eric Gilleland [aut, cre], Kim Elmore [ctb], Caren Marzban [ctb], Matt Pocernich [ctb], Gregor Skok [ctb]
Maintainer: Eric Gilleland <EricG@ucar.edu>

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Package segmented updated to version 1.6-1 with previous version 1.6-0 dated 2022-05-31

Title: Regression Models with Break-Points / Change-Points (with Possibly Random Effects) Estimation
Description: Given a regression model, segmented `updates' it by adding one or more segmented (i.e., piece-wise linear) relationships. Several variables with multiple breakpoints are allowed. The estimation method is discussed in Muggeo (2003, <doi:10.1002/sim.1545>) and illustrated in Muggeo (2008, <https://www.r-project.org/doc/Rnews/Rnews_2008-1.pdf>). An approach for hypothesis testing is presented in Muggeo (2016, <doi:10.1080/00949655.2016.1149855>), and interval estimation for the breakpoint is discussed in Muggeo (2017, <doi:10.1111/anzs.12200>). Segmented mixed models, i.e. random effects in the change point, are discussed in in Muggeo (2014, <doi:10.1177/1471082X13504721>).
Author: Vito M. R. Muggeo [aut, cre]
Maintainer: Vito M. R. Muggeo <vito.muggeo@unipa.it>

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Package jagshelper updated to version 0.1.11 with previous version 0.1.9 dated 2022-11-01

Title: Extracting and Visualizing Output from 'jagsUI'
Description: Tools are provided to streamline Bayesian analyses in 'JAGS' using the 'jagsUI' package. Included are functions for extracting output in simpler format, functions for streamlining assessment of convergence, and functions for producing summary plots of output. Also included is a function that provides a simple template for running 'JAGS' from 'R'. Referenced materials can be found at <DOI:10.1214/ss/1177011136>.
Author: Matt Tyers [aut, cre]
Maintainer: Matt Tyers <matttyersstat@gmail.com>

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Package geosimilarity updated to version 2.2 with previous version 1.1 dated 2022-05-17

Title: Geographically Optimal Similarity
Description: Understanding spatial association is essential for spatial statistical inference, including factor exploration and spatial prediction. Geographically optimal similarity (GOS) model is an effective method for spatial prediction, as described in Yongze Song (2022) <doi:10.1007/s11004-022-10036-8>. GOS was developed based on the geographical similarity principle, as described in Axing Zhu (2018) <doi:10.1080/19475683.2018.1534890>. GOS has advantages in more accurate spatial prediction using fewer samples and critically reduced prediction uncertainty.
Author: Yongze Song [aut, cre]
Maintainer: Yongze Song <yongze.song@outlook.com>

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Package BAT updated to version 2.9.2 with previous version 2.9.0 dated 2022-07-08

Title: Biodiversity Assessment Tools
Description: Includes algorithms to assess alpha and beta diversity in all their dimensions (taxonomic, phylogenetic and functional). It allows performing a number of analyses based on species identities/abundances, phylogenetic/functional distances, trees, convex-hulls or kernel density n-dimensional hypervolumes depicting species relationships. Cardoso et al. (2015) <doi:10.1111/2041-210X.12310>.
Author: Pedro Cardoso [aut, cre], Stefano Mammola [aut], Francois Rigal [aut], Jose Carvalho [aut]
Maintainer: Pedro Cardoso <pedro.cardoso@helsinki.fi>

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Package tergm updated to version 4.1.1 with previous version 4.1.0 dated 2022-06-22

Title: Fit, Simulate and Diagnose Models for Network Evolution Based on Exponential-Family Random Graph Models
Description: An integrated set of extensions to the 'ergm' package to analyze and simulate network evolution based on exponential-family random graph models (ERGM). 'tergm' is a part of the 'statnet' suite of packages for network analysis. See Krivitsky and Handcock (2014) <doi:10.1111/rssb.12014> and Carnegie, Krivitsky, Hunter, and Goodreau (2015) <doi:10.1080/10618600.2014.903087>.
Author: Pavel N. Krivitsky [aut, cre] , Mark S. Handcock [aut, ths], David R. Hunter [ctb], Steven M. Goodreau [ctb, ths], Martina Morris [ctb, ths], Nicole Bohme Carnegie [ctb], Carter T. Butts [ctb], Ayn Leslie-Cook [ctb], Skye Bender-deMoll [ctb], Li Wang [...truncated...]
Maintainer: Pavel N. Krivitsky <pavel@statnet.org>

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Package tcpl updated to version 3.0.1 with previous version 3.0.0 dated 2022-08-31

Title: ToxCast Data Analysis Pipeline
Description: A set of tools for processing and modeling high-throughput and high-content chemical screening data. The package was developed for the the chemical screening data generated by the US EPA ToxCast program, but can be used for diverse chemical screening efforts.
Author: Richard S Judson [ctb, ths], Dayne L Filer [aut], Jason Brown [cre], Sarah E Davidson-Fritz [ctb] , Madison Feshuk [ctb] , Lori Kolaczkowski [ctb], Todd Zurlinden [ctb], Parth Kothiya [ctb], Woodrow R Setzer [ctb], Matthew T Martin [ctb, ths], Katie [...truncated...]
Maintainer: Jason Brown <brown.jason@epa.gov>

Diff between tcpl versions 3.0.0 dated 2022-08-31 and 3.0.1 dated 2022-11-08

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New package TensorPreAve with initial version 0.1.1
Package: TensorPreAve
Title: Rank and Factor Loadings Estimation in Time Series Tensor Factor Models
Version: 0.1.1
Author: Weilin Chen [aut, cre]
Description: A set of functions to estimate rank and factor loadings of time series tensor factor models. A tensor is a multidimensional array. To analyze high-dimensional tensor time series, factor model is a major dimension reduction tool. 'TensorPreAve' provides functions to estimate the rank of core tensors and factor loading spaces of tensor time series. More specifically, a pre-averaging method that accumulates information from tensor fibres is used to estimate the factor loading spaces. The estimated directions corresponding to the strongest factors are then used for projecting the data for a potentially improved re-estimation of the factor loading spaces themselves. A new rank estimation method is also implemented to utilizes correlation information from the projected data. See Chen and Lam (2022) <arXiv:2208.04012> for more details.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/William-Chenwl/TensorPreAve
Imports: rTensor,MASS,stats,pracma
Depends: R (>= 2.10)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-11-07 23:32:03 UTC; William Chan
Maintainer: Weilin Chen <w.chen56@lse.ac.uk>
Repository: CRAN
Date/Publication: 2022-11-08 14:20:21 UTC

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New package SurvCorr with initial version 1.1
Package: SurvCorr
Title: Correlation of Bivariate Survival Times
Version: 1.1
Date: 2022-11-08
Depends: R (>= 3.0.2)
Imports: survival, fields
Description: Estimates correlation coefficients with associated confidence limits for bivariate, partially censored survival times. Uses the iterative multiple imputation approach proposed by Schemper, Kaider, Wakounig and Heinze (2013) <doi:10.1002/sim.5874>. Provides a scatterplot function to visualize the bivariate distribution, either on the original time scale or as copula.
License: GPL
Packaged: 2022-11-08 11:38:20 UTC; Gregor
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2022-11-08 14:10:12 UTC
Author: Georg Heinze [aut, cre], Meinhard Ploner [aut], Alexandra Kaider [aut], Gregor Steiner [aut]
Maintainer: Georg Heinze <georg.heinze@meduniwien.ac.at>

More information about SurvCorr at CRAN
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Package sf updated to version 1.0-9 with previous version 1.0-8 dated 2022-07-14

Title: Simple Features for R
Description: Support for simple features, a standardized way to encode spatial vector data. Binds to 'GDAL' for reading and writing data, to 'GEOS' for geometrical operations, and to 'PROJ' for projection conversions and datum transformations. Uses by default the 's2' package for spherical geometry operations on ellipsoidal (long/lat) coordinates.
Author: Edzer Pebesma [aut, cre] , Roger Bivand [ctb] , Etienne Racine [ctb], Michael Sumner [ctb], Ian Cook [ctb], Tim Keitt [ctb], Robin Lovelace [ctb], Hadley Wickham [ctb], Jeroen Ooms [ctb] , Kirill Mueller [ctb], Thomas Lin Pedersen [ctb], Dan Baston [c [...truncated...]
Maintainer: Edzer Pebesma <edzer.pebesma@uni-muenster.de>

Diff between sf versions 1.0-8 dated 2022-07-14 and 1.0-9 dated 2022-11-08

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More information about sf at CRAN
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Package RecordLinkage updated to version 0.4-12.4 with previous version 0.4-12.2 dated 2022-01-09

Title: Record Linkage Functions for Linking and Deduplicating Data Sets
Description: Provides functions for linking and deduplicating data sets. Methods based on a stochastic approach are implemented as well as classification algorithms from the machine learning domain. For details, see our paper "The RecordLinkage Package: Detecting Errors in Data" Sariyar M / Borg A (2010) <doi:10.32614/RJ-2010-017>.
Author: Murat Sariyar [aut, cre], Andreas Borg [aut]
Maintainer: Murat Sariyar <murat.sariyar@bfh.ch>

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Package randtoolbox updated to version 2.0.3 with previous version 2.0.2 dated 2022-08-16

Title: Toolbox for Pseudo and Quasi Random Number Generation and Random Generator Tests
Description: Provides (1) pseudo random generators - general linear congruential generators, multiple recursive generators and generalized feedback shift register (SF-Mersenne Twister algorithm (<doi:10.1007/978-3-540-74496-2_36>) and WELL (<doi:10.1145/1132973.1132974>) generators); (2) quasi random generators - the Torus algorithm, the Sobol sequence, the Halton sequence (including the Van der Corput sequence) and (3) some generator tests - the gap test, the serial test, the poker test, see, e.g., Gentle (2003) <doi:10.1007/b97336>. Take a look at the Distribution task view of types and tests of random number generators. The package can be provided without the 'rngWELL' dependency on demand. Package in Memoriam of Diethelm and Barbara Wuertz.
Author: R code by Yohan Chalabi [ctb], Christophe Dutang [aut, cre], Petr Savicky [aut], Diethelm Wuertz [aut]; C code of Knuth-TAOCP RNG by Donald Knuth [aut]; C code of Torus, Halton and Sobol sequences by Christophe Dutang [aut, cre]; C code of SFMT algor [...truncated...]
Maintainer: Christophe Dutang <dutangc@gmail.com>

Diff between randtoolbox versions 2.0.2 dated 2022-08-16 and 2.0.3 dated 2022-11-08

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New package optrefine with initial version 1.0.0
Package: optrefine
Title: Optimally Refine Strata
Version: 1.0.0
Description: Splits initial strata into refined strata that optimize covariate balance. For more information, please email the author for a copy of the accompanying manuscript. To solve the linear program, the 'Gurobi' commercial optimization software is recommended, but not required. The 'gurobi' R package can be installed following the instructions at <https://www.gurobi.com/documentation/9.1/refman/ins_the_r_package.html>.
URL: https://github.com/kkbrum/optrefine, https://kkbrum.github.io/optrefine/, https://www.gurobi.com/documentation/9.1/refman/ins_the_r_package.html
BugReports: https://github.com/kkbrum/optrefine/issues
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10), MASS, Rglpk, sampling, ggplot2
Suggests: covr, gurobi, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2022-11-07 21:31:34 UTC; katherine
Author: Katherine Brumberg [aut, cre]
Maintainer: Katherine Brumberg <kbrum@wharton.upenn.edu>
Repository: CRAN
Date/Publication: 2022-11-08 14:20:08 UTC

More information about optrefine at CRAN
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Package openair updated to version 2.12 with previous version 2.11 dated 2022-09-25

Title: Tools for the Analysis of Air Pollution Data
Description: Tools to analyse, interpret and understand air pollution data. Data are typically regular time series and air quality measurement, meteorological data and dispersion model output can be analysed. The package is described in Carslaw and Ropkins (2012, <doi:10.1016/j.envsoft.2011.09.008>) and subsequent papers.
Author: David Carslaw [aut, cre], Karl Ropkins [aut]
Maintainer: David Carslaw <david.carslaw@york.ac.uk>

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Package mFD updated to version 1.0.2 with previous version 1.0.1 dated 2021-12-16

Title: Compute and Illustrate the Multiple Facets of Functional Diversity
Description: Computing functional traits-based distances between pairs of species for species gathered in assemblages allowing to build several functional spaces. The package allows to compute functional diversity indices assessing the distribution of species (and of their dominance) in a given functional space for each assemblage and the overlap between assemblages in a given functional space, see: Chao et al. (2018) <doi:10.1002/ecm.1343>, Maire et al. (2015) <doi:10.1111/geb.12299>, Mouillot et al. (2013) <doi:10.1016/j.tree.2012.10.004>, Mouillot et al. (2014) <doi:10.1073/pnas.1317625111>, Ricotta and Szeidl (2009) <doi:10.1016/j.tpb.2009.10.001>. Graphical outputs are included. Visit the 'mFD' website for more information, documentation and examples.
Author: Camille Magneville [aut, cre, cph] , Nicolas Loiseau [aut] , Camille Albouy [aut] , Nicolas Casajus [aut] , Thomas Claverie [aut] , Arthur Escalas [aut] , Fabien Leprieur [aut] , Eva Maire [aut] , David Mouillot [aut] , Sebastien Villeger [aut]
Maintainer: Camille Magneville <camille.magneville@gmail.com>

Diff between mFD versions 1.0.1 dated 2021-12-16 and 1.0.2 dated 2022-11-08

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Package learnr updated to version 0.11.2 with previous version 0.11.1 dated 2022-10-19

Title: Interactive Tutorials for R
Description: Create interactive tutorials using R Markdown. Use a combination of narrative, figures, videos, exercises, and quizzes to create self-paced tutorials for learning about R and R packages.
Author: Garrick Aden-Buie [aut, cre] , Barret Schloerke [aut] , JJ Allaire [aut, ccp], Alexander Rossell Hayes [ctb] , Nischal Shrestha [ctb] , Angela Li [ctb] , RStudio [cph, fnd], Ajax.org B.V. [ctb, cph] , Zeno Rocha [ctb, cph] , Nick Payne [ctb, cph] , J [...truncated...]
Maintainer: Garrick Aden-Buie <garrick@rstudio.com>

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Package dexter updated to version 1.2.2 with previous version 1.2.1 dated 2022-05-24

Title: Data Management and Analysis of Tests
Description: A system for the management, assessment, and psychometric analysis of data from educational and psychological tests.
Author: Gunter Maris [aut], Timo Bechger [aut], Jesse Koops [aut, cre], Ivailo Partchev [aut]
Maintainer: Jesse Koops <jesse.koops@cito.nl>

Diff between dexter versions 1.2.1 dated 2022-05-24 and 1.2.2 dated 2022-11-08

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New package BTSR with initial version 0.1.0
Package: BTSR
Date: 2022-11-07
Title: Bounded Time Series Regression
Version: 0.1.0
Copyright: see file COPYRIGHTS
Depends: R (>= 4.0.0)
Description: Simulate, estimate and forecast a wide range of regression based dynamic models for bounded time series, covering the most commonly applied models in the literature. The main calculations are done in 'FORTRAN', which translates into very fast algorithms. The main references are Bayer et al. (2017) <doi:10.1016/j.jhydrol.2017.10.006>, Pumi et al. (2019) <doi:10.1016/j.jspi.2018.10.001>, Pumi et al. (2021) <doi:10.1111/sjos.12439> and Pumi et al. (2022) <arXiv:2211.02097>.
License: GPL (>= 3)
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2022-11-07 14:31:59 UTC; Taiane
Author: Taiane Schaedler Prass [aut, cre, com] , Guilherme Pumi [ctb, aut] , Fabio Mariano Bayer [ctb] , Jack Joseph Dongarra [ctb], Cleve Moler [ctb], Gilbert Wright Stewart [ctb], Ciyou Zhu [ctb], Richard H. Byrd [ctb], Jorge Nocedal [ctb], Jose Luis Moral [...truncated...]
Maintainer: Taiane Schaedler Prass <taianeprass@gmail.com>
Repository: CRAN
Date/Publication: 2022-11-08 14:10:19 UTC

More information about BTSR at CRAN
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Package libsoc (with last version 0.7.3) was removed from CRAN

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

2022-02-03 0.7.3
2019-05-15 0.7
2018-01-28 0.6.4

Permanent link
Package webfakes updated to version 1.1.6 with previous version 1.1.5 dated 2022-10-25

Title: Fake Web Apps for HTTP Testing
Description: Create a web app that makes it easier to test web clients without using the internet. It includes a web app framework with path matching, parameters and templates. Can parse various 'HTTP' request bodies. Can send 'JSON' data or files from the disk. Includes a web app that implements the <https://httpbin.org> web service.
Author: Gabor Csardi [aut, cre], RStudio, Pbc. [cph], Civetweb contributors [ctb] , Redoc contributors [ctb] , L. Peter Deutsch [ctb] , Martin Purschke [ctb] , Aladdin Enterprises [cph] , Maelle Salmon [ctb]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

Diff between webfakes versions 1.1.5 dated 2022-10-25 and 1.1.6 dated 2022-11-08

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New package IOLS with initial version 0.1.0
Package: IOLS
Title: Iterated Ordinary Least Squares Regression
Version: 0.1.0
Description: Addresses the 'log of zero' by developing a new family of estimators called iterated Ordinary Least Squares. This family nests standard approaches such as log-linear and Poisson regressions, offers several computational advantages, and corresponds to the correct way to perform the popular log(Y + 1) transformation. For more details about how to use it, see the notebook at: <https://www.davidbenatia.com/>.
License: GPL-3
Encoding: UTF-8
Imports: stats, utils, sandwich, matlib, boot, randomcoloR, stringr
Depends: R (>= 2.10)
LazyData: true
NeedsCompilation: no
Packaged: 2022-11-06 21:28:17 UTC; Zbalah
Author: Nassim Zbalah [cre], David Benatia [aut]
Maintainer: Nassim Zbalah <nas66.nz@gmail.com>
Repository: CRAN
Date/Publication: 2022-11-08 14:00:01 UTC

More information about IOLS at CRAN
Permanent link

Package stplanr updated to version 1.0.2 with previous version 1.0.1 dated 2022-08-19

Title: Sustainable Transport Planning
Description: Tools for transport planning with an emphasis on spatial transport data and non-motorized modes. Create geographic "desire lines" from origin-destination (OD) data (building on the 'od' package); calculate routes on the transport network locally and via interfaces to routing services such as <https://cyclestreets.net/>; calculate route segment attributes such as bearing. The package implements the 'travel flow aggregration' method described in Morgan and Lovelace (2020) <doi:10.1177/2399808320942779>. Further information on the package's aim and scope can be found in the vignettes and in a paper in the R Journal (Lovelace and Ellison 2018) <doi:10.32614/RJ-2018-053>.
Author: Robin Lovelace [aut, cre] , Richard Ellison [aut], Malcolm Morgan [aut] , Barry Rowlingson [ctb], Nick Bearman [ctb], Nikolai Berkoff [ctb], Scott Chamberlain [rev] , Mark Padgham [ctb], Andrea Gilardi [ctb]
Maintainer: Robin Lovelace <rob00x@gmail.com>

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Package mlr3tuning updated to version 0.16.0 with previous version 0.15.0 dated 2022-10-21

Title: Tuning for 'mlr3'
Description: Implements methods for hyperparameter tuning with 'mlr3', e.g. grid search, random search, generalized simulated annealing and iterated racing. Various termination criteria can be set and combined. The class 'AutoTuner' provides a convenient way to perform nested resampling in combination with 'mlr3'.
Author: Marc Becker [cre, aut] , Michel Lang [aut] , Jakob Richter [aut] , Bernd Bischl [aut] , Daniel Schalk [aut]
Maintainer: Marc Becker <marcbecker@posteo.de>

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Package hmer updated to version 1.2.0 with previous version 1.0.1 dated 2022-05-17

Title: History Matching and Emulation Package
Description: A set of objects and functions for Bayes Linear emulation and history matching. Core functionality includes automated training of emulators to data, diagnostic functions to ensure suitability, and a variety of proposal methods for generating 'waves' of points. For details on the mathematical background, there are many papers available on the topic (see references attached to function help files); for details of the functions in this package, consult the manual or help files.
Author: Andrew Iskauskas [aut, cre]
Maintainer: Andrew Iskauskas <andrew.iskauskas@durham.ac.uk>

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Package dbmss updated to version 2.7-11 with previous version 2.7-10 dated 2022-07-10

Title: Distance-Based Measures of Spatial Structures
Description: Simple computation of spatial statistic functions of distance to characterize the spatial structures of mapped objects, following Marcon, Traissac, Puech, and Lang (2015) <doi:10.18637/jss.v067.c03>. Includes classical functions (Ripley's K and others) and more recent ones used by spatial economists (Duranton and Overman's Kd, Marcon and Puech's M). Relies on 'spatstat' for some core calculation.
Author: Eric Marcon [aut, cre] , Gabriel Lang [aut] , Stephane Traissac [aut] , Florence Puech [aut]
Maintainer: Eric Marcon <eric.marcon@agroparistech.fr>

Diff between dbmss versions 2.7-10 dated 2022-07-10 and 2.7-11 dated 2022-11-08

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New package toRvik with initial version 1.1.1
Package: toRvik
Title: Extensive and Tidy NCAA Men's College Basketball Data
Version: 1.1.1
Description: An API wrapper for 'cbbstat' and a suite of functions to pull and clean detailed, extensive college basketball statistics from Barttorvik<https://barttorvik.com/>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: cli, crayon, data.table, dplyr, glue, httr, janitor, jsonlite, lubridate, magrittr, purrr, readr, rlang, rvest, stringr, tidyr, withr
Suggests: covr, DBI, knitr, rmarkdown, spelling, testthat (>= 3.0.0), tictoc
VignetteBuilder: knitr
URL: https://www.torvik.dev/, https://github.com/andreweatherman/toRvik
Language: en-US
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2022-11-07 16:05:05 UTC; Andrew
Author: Andrew Weatherman [aut, cre]
Maintainer: Andrew Weatherman <andrew@aweatherman.com>
Repository: CRAN
Date/Publication: 2022-11-08 10:50:02 UTC

More information about toRvik at CRAN
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Package readMzXmlData updated to version 2.8.2 with previous version 2.8.1 dated 2015-09-16

Title: Reads Mass Spectrometry Data in mzXML Format
Description: Functions for reading mass spectrometry data in mzXML format.
Author: Sebastian Gibb [aut, cre]
Maintainer: Sebastian Gibb <mail@sebastiangibb.de>

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Package predhy updated to version 1.2.1 with previous version 1.2.0 dated 2021-08-16

Title: Genomic Prediction of Hybrid Performance
Description: Performs genomic prediction of hybrid performance using eight GS methods including GBLUP, BayesB, RKHS, PLS, LASSO, Elastic net, Random forest and XGBoost. It also provides fast cross-validation and mating design scheme for training population (Xu S et al (2016) <doi:10.1111/tpj.13242>; Xu S (2017) <doi:10.1534/g3.116.038059>).
Author: Yang Xu, Guangning Yu, Yanru Cui, Shizhong Xu, Chenwu Xu
Maintainer: Yang Xu <xuyang_89@126.com>

Diff between predhy versions 1.2.0 dated 2021-08-16 and 1.2.1 dated 2022-11-08

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New package planningML with initial version 1.0.0
Package: planningML
Title: A Sample Size Calculator for Machine Learning Applications in Healthcare
Version: 1.0.0
Description: Advances in automated document classification has led to identifying massive numbers of clinical concepts from handwritten clinical notes. These high dimensional clinical concepts can serve as highly informative predictors in building classification algorithms for identifying patients with different clinical conditions, commonly referred to as patient phenotyping. However, from a planning perspective, it is critical to ensure that enough data is available for the phenotyping algorithm to obtain a desired classification performance. This challenge in sample size planning is further exacerbated by the high dimension of the feature space and the inherent imbalance of the response class. Currently available sample size planning methods can be categorized into: (i) model-based approaches that predict the sample size required for achieving a desired accuracy using a linear machine learning classifier and (ii) learning curve-based approaches (Figueroa et al. (2012) <doi:10.1186/1472-6947-1 [...truncated...]
Imports: tidyverse, caret, lubridate, Matrix, MESS, dplyr, pROC, stats
Depends: R (>= 3.5.0)
License: GPL-2
Encoding: UTF-8
Suggests: knitr,rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-11-06 21:08:27 UTC; rrrrrita
Author: Xinying Fang [aut, cre], Satabdi Saha [aut], Jaejoon Song [aut], Sai Dharmarajan [aut]
Maintainer: Xinying Fang <fxy950225@gmail.com>
Repository: CRAN
Date/Publication: 2022-11-08 10:20:02 UTC

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Package odetector updated to version 1.0.1 with previous version 1.0.0 dated 2022-10-04

Title: Outlier Detection Using Partitioning Clustering Algorithms
Description: An object is called "outlier" if it remarkably deviates from the other objects in a data set. Outlier detection is the process to find outliers by using the methods that are based on distance measures, clustering and spatial methods (Ben-Gal, 2005 <ISBN 0-387-24435-2>). It is one of the intensively studied research topics for identification of novelties, frauds, anomalies, deviations or exceptions in addition to its use for outlier removing in data processing. This package provides the implementations of some novel approaches to detect the outliers based on typicality degrees that are obtained with the soft partitioning clustering algorithms such as Fuzzy C-means and its variants.
Author: Zeynel Cebeci [aut, cre] , Cagatay Cebeci [ctb] , Yalcin Tahtali [ctb]
Maintainer: Zeynel Cebeci <zcebeci@cukurova.edu.tr>

Diff between odetector versions 1.0.0 dated 2022-10-04 and 1.0.1 dated 2022-11-08

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Package LUCIDus updated to version 2.2.1 with previous version 2.2 dated 2022-08-07

Title: Latent Unknown Clustering Integrating Multi-View Data
Description: An implementation of the LUCID model (Peng (2019) <doi:10.1093/bioinformatics/btz667>). LUCID conducts integrated clustering using exposures, omics data (and outcome as an option). An EM algorithm is implemented to estimate MLE of the LUCID model. LUCIDus features integrated variable selection, incorporation of missing omics data, bootstrap inference, prediction and visualization of the model.
Author: Yinqi Zhao [aut, cre] , David Conti [ths] , Jesse Goodrich [ctb] , Cheng Peng [ctb]
Maintainer: Yinqi Zhao <yinqiz@usc.edu>

Diff between LUCIDus versions 2.2 dated 2022-08-07 and 2.2.1 dated 2022-11-08

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Package LocalControlStrategy updated to version 1.4 with previous version 1.3.3 dated 2019-08-29

Title: Local Control Strategy for Robust Analysis of Cross-Sectional Data
Description: Especially when cross-sectional data are observational, effects of treatment selection bias and confounding are revealed by using the Nonparametric and Unsupervised "preprocessing" methods central to Local Control (LC) Strategy. The LC objective is to estimate the "effect-size distribution" that best quantifies a potentially causal relationship between a numeric y-Outcome variable and a t-Treatment or e-Exposure variable. Treatment variables are binary {either 1 = "new" or 0 = "control"}, while Exposure variables vary continuously over a finite range. LC Strategy starts by CLUSTERING experimental units (individual patients, US Counties, etc.) on their X-confounder characteristics. Clusters represent exclusive and exhaustive BLOCKS of relatively well-matched units. The implicit statistical model for LC is thus simple one-way ANOVA. Within-Block measures of effect-size are Local Rank Correlations (LRCs) when Exposure is numeric with (many) more than two levels. Otherwise, Treatment choic [...truncated...]
Author: Bob Obenchain
Maintainer: Bob Obenchain <wizbob@att.net>

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New package lfstat with initial version 0.9.12
Package: lfstat
Title: Calculation of Low Flow Statistics for Daily Stream Flow Data
Version: 0.9.12
Date: 2022-11-06
BugReports: https://github.com/mundl/lfstat/issues
Description: The "Manual on Low-flow Estimation and Prediction" (Gustard & Demuth (2009, ISBN:978-92-63-11029-9)), published by the World Meteorological Organisation, gives a comprehensive summary on how to analyse stream flow data focusing on low-flows. This packages provides functions to compute the described statistics and produces plots similar to the ones in the manual.
License: GPL (>= 2)
Language: en-GB
LazyLoad: yes
Depends: R (>= 2.10), xts, lmom, lattice
Imports: lmomRFA, dygraphs, zoo, latticeExtra, plyr, scales
Suggests: testthat
NeedsCompilation: no
Packaged: 2022-11-06 18:44:34 UTC; tobi
Author: Tobias Gauster [ctb, cre], Gregor Laaha [aut] , Daniel Koffler [aut]
Maintainer: Tobias Gauster <t.gauster@gmail.com>
Repository: CRAN
Date/Publication: 2022-11-08 10:20:05 UTC

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New package intensegRid with initial version 0.1.2
Package: intensegRid
Title: R Wrapper for the Carbon Intensity API
Version: 0.1.2
Author: Kasia Kulma <katarzyna.kulma@gmail.com>
Maintainer: Kasia Kulma <katarzyna.kulma@gmail.com>
Description: Electricity is not made equal and it vary in its carbon footprint (or carbon intensity) depending on its source. This package enables to access and query data provided by the Carbon Intensity API (<https://carbonintensity.org.uk/>). National Grid’s Carbon Intensity API provides an indicative trend of regional carbon intensity of the electricity system in Great Britain.
License: CC0
Encoding: UTF-8
LazyData: TRUE
URL: https://github.com/KKulma/intensegRid, https://kkulma.github.io/intensegRid/articles/intro-to-carbon-intensity.html
BugReports: https://github.com/KKulma/intensegRid/issues
Depends: R (>= 2.10)
Imports: dplyr, httr, jsonlite, lubridate, magrittr, tidyr, tibble, rlang, purrr
Suggests: utils, knitr, rmarkdown, testthat (>= 2.1.0), covr, vcr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-11-07 15:17:20 UTC; user
Repository: CRAN
Date/Publication: 2022-11-08 10:50:06 UTC

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Package htsr updated to version 1.1.5 with previous version 1.1.4 dated 2022-04-17

Title: Hydro-Meteorology Time-Series
Description: Functions for the management and treatment of hydrology and meteorology time-series stored in a 'Sqlite' data base.
Author: Pierre Chevallier [aut, cre]
Maintainer: Pierre Chevallier <pierre.chevallier@ird.fr>

Diff between htsr versions 1.1.4 dated 2022-04-17 and 1.1.5 dated 2022-11-08

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Package HDShOP updated to version 0.1.3 with previous version 0.1.2 dated 2021-10-23

Title: High-Dimensional Shrinkage Optimal Portfolios
Description: Constructs shrinkage estimators of high-dimensional mean-variance portfolios and performs high-dimensional tests on optimality of a given portfolio. The techniques developed in Bodnar et al. (2018) <doi:10.1016/j.ejor.2017.09.028>, Bodnar et al. (2019) <doi:10.1109/TSP.2019.2929964>, Bodnar et al. (2020) <doi:10.1109/TSP.2020.3037369> are central to the package. They provide simple and feasible estimators and tests for optimal portfolio weights, which are applicable for 'large p and large n' situations where p is the portfolio dimension (number of stocks) and n is the sample size. The package also includes tools for constructing portfolios based on shrinkage estimators of the mean vector and covariance matrix as well as a new Bayesian estimator for the Markowitz efficient frontier recently developed by Bauder et al. (2021) <doi:10.1080/14697688.2020.1748214>.
Author: Taras Bodnar [aut] , Solomiia Dmytriv [aut] , Yarema Okhrin [aut] , Dmitry Otryakhin [aut, cre] , Nestor Parolya [aut]
Maintainer: Dmitry Otryakhin <d.otryakhin.acad@protonmail.ch>

Diff between HDShOP versions 0.1.2 dated 2021-10-23 and 0.1.3 dated 2022-11-08

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Package FFD updated to version 1.0-9 with previous version 1.0-8 dated 2021-01-07

Title: Freedom from Disease
Description: Functions, S4 classes/methods and a graphical user interface (GUI) to design surveys to substantiate freedom from disease using a modified hypergeometric function (see Cameron and Baldock, 1997, <doi:10.1016/s0167-5877(97)00081-0>). Herd sensitivities are computed according to sampling strategies "individual sampling" or "limited sampling" (see M. Ziller, T. Selhorst, J. Teuffert, M. Kramer and H. Schlueter, 2002, <doi:10.1016/S0167-5877(01)00245-8>). Methods to compute the a-posteriori alpha-error are implemented. Risk-based targeted sampling is supported.
Author: Ian Kopacka
Maintainer: Ian Kopacka <ian.kopacka@ages.at>

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Package DynamicGP updated to version 1.1-9 with previous version 1.1-8 dated 2022-04-12

Title: Modelling and Analysis of Dynamic Computer Experiments
Description: Emulating and solving inverse problems for dynamic computer experiments. It contains two major functionalities: (1) localized GP model for large-scale dynamic computer experiments using the algorithm proposed by Zhang et al. (2018) <arXiv:1611.09488>; (2) solving inverse problems in dynamic computer experiments. The current version only supports 64-bit version of R.
Author: Ru Zhang [aut, cre], Chunfang Devon Lin [aut], Pritam Ranjan [aut], Robert B Gramacy [ctb], Nicolas Devillard [ctb], Jorge Nocedal [ctb], Jose Luis Morales [ctb], Ciyou Zhu [ctb], Richard Byrd [ctb], Peihuang Lu-Chen [ctb], Berend Hasselman [ctb], Ja [...truncated...]
Maintainer: Ru Zhang <heavenmarshal@gmail.com>

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Package CoTiMA updated to version 0.6.2 with previous version 0.5.4 dated 2022-01-20

Title: Continuous Time Meta-Analysis ('CoTiMA')
Description: The 'CoTiMA' package performs meta-analyses of correlation matrices of repeatedly measured variables taken from studies that used different time intervals. Different time intervals between measurement occasions impose problems for meta-analyses because the effects (e.g. cross-lagged effects) cannot be simply aggregated, for example, by means of common fixed or random effects analysis. However, continuous time math, which is applied in 'CoTiMA', can be used to extrapolate or intrapolate the results from all studies to any desired time lag. By this, effects obtained in studies that used different time intervals can be meta-analyzed. 'CoTiMA' fits models to empirical data using the structural equation model (SEM) package 'ctsem', the effects specified in a SEM are related to parameters that are not directly included in the model (i.e., continuous time parameters; together, they represent the continuous time structural equation model, CTSEM). Statistical model comparisons and significance [...truncated...]
Author: Christian Dormann [aut, cph], Markus Homberg [aut, com, cre], Christina Guthier [ctb], Manuel Voelkle [ctb]
Maintainer: Markus Homberg <cotima@uni-mainz.de>

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Package rmweather updated to version 0.2.4 with previous version 0.1.51 dated 2020-06-15

Title: Tools to Conduct Meteorological Normalisation on Air Quality Data
Description: An integrated set of tools to allow data users to conduct meteorological normalisation on air quality data. This meteorological normalisation technique uses predictive random forest models to remove variation of pollutant concentrations so trends and interventions can be explored in a robust way. For examples, see Grange et al. (2018) <doi:10.5194/acp-18-6223-2018> and Grange and Carslaw (2019) <doi:10.1016/j.scitotenv.2018.10.344>.
Author: Stuart K. Grange [cre, aut]
Maintainer: Stuart K. Grange <stuart.grange@york.ac.uk>

Diff between rmweather versions 0.1.51 dated 2020-06-15 and 0.2.4 dated 2022-11-08

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Package nzffdr updated to version 2.1.0 with previous version 2.0.0 dated 2022-01-16

Title: Import, Clean and Update Data from the New Zealand Freshwater Fish Database
Description: Access the New Zealand Freshwater Fish Database from R and a few functions to clean the data once in R.
Author: Finnbar Lee [aut, cre], Nick Young [aut]
Maintainer: Finnbar Lee <lee.finnbar@gmail.com>

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Package ggstar updated to version 1.0.4 with previous version 1.0.3 dated 2021-12-03

Title: Multiple Geometric Shape Point Layer for 'ggplot2'
Description: To create the multiple polygonal point layer for easily discernible shapes, we developed the package, it is like the 'geom_point' of 'ggplot2'. It can be used to draw the scatter plot.
Author: Shuangbin Xu [aut, cre]
Maintainer: Shuangbin Xu <xshuangbin@163.com>

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Package gam updated to version 1.22 with previous version 1.20.2 dated 2022-07-04

Title: Generalized Additive Models
Description: Functions for fitting and working with generalized additive models, as described in chapter 7 of "Statistical Models in S" (Chambers and Hastie (eds), 1991), and "Generalized Additive Models" (Hastie and Tibshirani, 1990).
Author: Trevor Hastie
Maintainer: Trevor Hastie <hastie@stanford.edu>

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Package dlookr updated to version 0.6.1 with previous version 0.6.0 dated 2022-06-07

Title: Tools for Data Diagnosis, Exploration, Transformation
Description: A collection of tools that support data diagnosis, exploration, and transformation. Data diagnostics provides information and visualization of missing values and outliers and unique and negative values to help you understand the distribution and quality of your data. Data exploration provides information and visualization of the descriptive statistics of univariate variables, normality tests and outliers, correlation of two variables, and relationship between target variable and predictor. Data transformation supports binning for categorizing continuous variables, imputates missing values and outliers, resolving skewness. And it creates automated reports that support these three tasks.
Author: Choonghyun Ryu [aut, cre]
Maintainer: Choonghyun Ryu <choonghyun.ryu@gmail.com>

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