Sun, 07 Feb 2021

Package VARMER updated to version 1.0.0 with previous version 0.1.1 dated 2021-02-05

Title: Variational Merging
Description: A new mathematical formulation to merge observed data with gridded images of environmental variables using partial differential equations in a variational setting. The original method was created, developed and published by Ulloa, Samaniego, Campozano and Ballari (2018) <doi:10.1002/2017JD027982>.
Author: Jacinto Ulloa [aut], Esteban Samaniego [aut], Lenin Campozano [aut], Daniela Ballari [aut], Leandro Robaina [cre, com, trl], Ronald Gualan [com]
Maintainer: Leandro Robaina <metclimaepn.libs@gmail.com>

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Package rdacca.hp updated to version 0.5-4 with previous version 0.5-3 dated 2021-02-06

Title: Hierarchical and Variation Partitioning for Canonical Analysis
Description: This function conducts variation partitioning and hierarchical partitioning to calculate the unique, shared (referred as to "common") and independent contributions of each predictor (or matrix) to explained variation (R-squared and adjusted R-squared) on canonical analysis (RDA,CCA and db-RDA), applying the hierarchy algorithm of Chevan, A. and Sutherland, M. 1991 Hierarchical Partitioning.The American Statistician, 90-96 <DOI:10.1080/00031305.1991.10475776>.
Author: Jiangshan Lai,Pedro Peres-neto
Maintainer: Jiangshan Lai <lai@ibcas.ac.cn>

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Package RankingProject updated to version 0.3.1 with previous version 0.3.0 dated 2021-02-07

Title: The Ranking Project: Visualizations for Comparing Populations
Description: Functions to generate plots and tables for comparing independently- sampled populations. Companion package to "A Primer on Visualizations for Comparing Populations, Including the Issue of Overlapping Confidence Intervals" by Wright, Klein, and Wieczorek (2019) <DOI:10.1080/00031305.2017.1392359> and "A Joint Confidence Region for an Overall Ranking of Populations" by Klein, Wright, and Wieczorek (2020) <DOI:10.1111/rssc.12402>.
Author: Jerzy Wieczorek [cre, aut], Joel Beard [ctb], Andy Liaw [ctb], Robert Gentleman [ctb], Martin Maechler [ctb]
Maintainer: Jerzy Wieczorek <jerzywieczorek@gmail.com>

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Package zipangu updated to version 0.2.3 with previous version 0.2.2 dated 2021-02-01

Title: Japanese Utility Functions and Data
Description: Some data treated by the Japanese R user require unique operations and processing. These are caused by address, Kanji, and traditional year representations. 'zipangu' transforms specific to Japan into something more general one.
Author: Shinya Uryu [aut, cre] (<https://orcid.org/0000-0002-0493-6186>), Hiroaki Yutani [ctb] (<https://orcid.org/0000-0002-3385-7233>), Kazuhiro Maeda [ctb], Mao Kobayashi [ctb]
Maintainer: Shinya Uryu <suika1127@gmail.com>

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Package txshift updated to version 0.3.5 with previous version 0.3.4 dated 2020-09-25

Title: Efficient Estimation of the Causal Effects of Stochastic Interventions
Description: Efficient estimation of the population-level causal effects of stochastic interventions on a continuous-valued exposure. Both one-step and targeted minimum loss estimators are implemented for a causal parameter defined as the counterfactual mean of an outcome of interest under a stochastic intervention that may depend on the natural value of the exposure (i.e., a modified treatment policy). To accommodate settings in which two-phase sampling is employed, procedures for making use of inverse probability of censoring weights are provided to facilitate construction of inefficient and efficient one-step and targeted minimum loss estimators. The causal parameter and its estimation were first described by Díaz and van der Laan (2013) <doi:10.1111/j.1541-0420.2011.01685.x>, while the multiply robust estimation procedure and its application to data arising in two-phase sampling designs was detailed in NS Hejazi, MJ van der Laan, HE Janes, PB Gilbert, and DC Benkeser (2020) <doi:10.1111/biom.13375>. Estimation of nuisance parameters may be enhanced through the Super Learner ensemble model in 'sl3', available for download from GitHub using 'remotes::install_github("tlverse/sl3")'.
Author: Nima Hejazi [aut, cre, cph] (<https://orcid.org/0000-0002-7127-2789>), David Benkeser [aut] (<https://orcid.org/0000-0002-1019-8343>), Iván Díaz [ctb] (<https://orcid.org/0000-0001-9056-2047>), Jeremy Coyle [ctb] (<https://orcid.org/0000-0002-9874-6649>), Mark van der Laan [ctb, ths] (<https://orcid.org/0000-0003-1432-5511>)
Maintainer: Nima Hejazi <nh@nimahejazi.org>

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Package Qtools updated to version 1.5.4 with previous version 1.5.3 dated 2020-11-27

Title: Utilities for Quantiles
Description: Functions for unconditional and conditional quantiles. These include methods for transformation-based quantile regression, quantile-based measures of location, scale and shape, methods for quantiles of discrete variables, quantile-based multiple imputation, restricted quantile regression, and directional quantile classification. A vignette is given in Geraci (2016, The R Journal) <doi:10.32614/RJ-2016-037> and included in the package.
Author: Marco Geraci [aut, cph, cre] (<https://orcid.org/0000-0002-6311-8685>), Alessio Farcomeni [ctb] (Contributions to midrq code, <https://orcid.org/0000-0002-7104-5826>), Cinzia Viroli [ctb] (Contributions to dqc code, <https://orcid.org/0000-0002-3278-5266>)
Maintainer: Marco Geraci <marco.geraci@uniroma1.it>

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Package PopVar updated to version 1.3.0 with previous version 1.2.1 dated 2015-07-08

Title: Genomic Breeding Tools: Genetic Variance Prediction and Cross-Validation
Description: The main attribute of 'PopVar' is the prediction of genetic variance in bi-parental populations, from which the package derives its name. 'PopVar' contains a set of functions that use phenotypic and genotypic data from a set of candidate parents to 1) predict the mean, genetic variance, and superior progeny value of all, or a defined set of pairwise bi-parental crosses, and 2) perform cross-validation to estimate genome-wide prediction accuracy of multiple statistical models. More details are available in Mohammadi, Tiede, and Smith (2015, <doi:10.2135/cropsci2015.01.0030>). A dataset 'think_barley.rda' is included for reference and examples.
Author: Tyler Tiede [aut], Jeffrey Neyhart [aut, ctb, cre] (<https://orcid.org/0000-0002-1991-5310>), Mohsen Mohammadi [ctb] (<https://orcid.org/0000-0002-4536-1200>), Kevin Smith [ctb] (<https://orcid.org/0000-0001-8253-3326>)
Maintainer: Jeffrey Neyhart <neyhartje@gmail.com>

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Package metR updated to version 0.9.1 with previous version 0.9.0 dated 2020-11-25

Title: Tools for Easier Analysis of Meteorological Fields
Description: Many useful functions and extensions for dealing with meteorological data in the tidy data framework. Extends 'ggplot2' for better plotting of scalar and vector fields and provides commonly used analysis methods in the atmospheric sciences.
Author: Elio Campitelli [cre, aut] (<https://orcid.org/0000-0002-7742-9230>)
Maintainer: Elio Campitelli <elio.campitelli@cima.fcen.uba.ar>

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Package mde updated to version 0.3.0 with previous version 0.2.1 dated 2020-06-27

Title: Missing Data Explorer
Description: Correct identification and handling of missing data is one of the most important steps in any analysis. To aid this process, 'mde' provides a very easy to use yet robust framework to quickly get an idea of where the missing data lies and therefore find the most appropriate action to take. Graham WJ (2009) <doi:10.1146/annurev.psych.58.110405.085530>.
Author: Nelson Gonzabato [aut, cre]
Maintainer: Nelson Gonzabato <gonzabato@hotmail.com>

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Package lmSubsets updated to version 0.5-2 with previous version 0.5-1 dated 2020-05-23

Title: Exact Variable-Subset Selection in Linear Regression
Description: Exact and approximation algorithms for variable-subset selection in ordinary linear regression models. Either compute all submodels with the lowest residual sum of squares, or determine the single-best submodel according to a pre-determined statistical criterion. Hofmann et al. (2020) <doi:10.18637/jss.v093.i03>.
Author: Marc Hofmann [aut, cre], Cristian Gatu [aut], Erricos J. Kontoghiorghes [aut], Ana Colubi [aut], Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>), Martin Moene [cph] (for the GSL Lite library), Microsoft Corporation [cph] (for the GSL Lite library), Free Software Foundation, Inc. [cph] (for snippets from the GNU ISO C++ Library)
Maintainer: Marc Hofmann <marc.hofmann@gmail.com>

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Package autoharp (with last version 0.0.4) was removed from CRAN

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

2021-01-22 0.0.4

Permanent link
Package casebase updated to version 0.9.1 with previous version 0.9.0 dated 2020-07-05

Title: Fitting Flexible Smooth-in-Time Hazards and Risk Functions via Logistic and Multinomial Regression
Description: Fit flexible and fully parametric hazard regression models to survival data with single event type or multiple competing causes via logistic and multinomial regression. Our formulation allows for arbitrary functional forms of time and its interactions with other predictors for time-dependent hazards and hazard ratios. From the fitted hazard model, we provide functions to readily calculate and plot cumulative incidence and survival curves for a given covariate profile. This approach accommodates any log-linear hazard function of prognostic time, treatment, and covariates, and readily allows for non-proportionality. We also provide a plot method for visualizing incidence density via population time plots. Based on the case-base sampling approach of Hanley and Miettinen (2009) <DOI:10.2202/1557-4679.1125>, Saarela and Arjas (2015) <DOI:10.1111/sjos.12125>, and Saarela (2015) <DOI:10.1007/s10985-015-9352-x>.
Author: Sahir Bhatnagar [aut, cre] (http://sahirbhatnagar.com/), Maxime Turgeon [aut] (<https://orcid.org/0000-0003-4863-6035>), Jesse Islam [aut] (https://www.jesseislam.com/), Olli Saarela [aut] (http://individual.utoronto.ca/osaarela/), James Hanley [aut] (http://www.medicine.mcgill.ca/epidemiology/hanley/)
Maintainer: Sahir Bhatnagar <sahir.bhatnagar@gmail.com>

Diff between casebase versions 0.9.0 dated 2020-07-05 and 0.9.1 dated 2021-02-07

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Package GWmodel updated to version 2.2-3 with previous version 2.2-2 dated 2020-11-22

Title: Geographically-Weighted Models
Description: Techniques from a particular branch of spatial statistics,termed geographically-weighted (GW) models. GW models suit situations when data are not described well by some global model, but where there are spatial regions where a suitably localised calibration provides a better description. 'GWmodel' includes functions to calibrate: GW summary statistics (Brunsdon et al., 2002)<doi: 10.1016/s0198-9715(01)00009-6>, GW principal components analysis (Harris et al., 2011)<doi: 10.1080/13658816.2011.554838>, GW discriminant analysis (Brunsdon et al., 2007)<doi: 10.1111/j.1538-4632.2007.00709.x> and various forms of GW regression (Brunsdon et al., 1996)<doi: 10.1111/j.1538-4632.1996.tb00936.x>; some of which are provided in basic and robust (outlier resistant) forms.
Author: Binbin Lu[aut], Paul Harris[aut], Martin Charlton[aut], Chris Brunsdon[aut], Tomoki Nakaya[aut], Daisuke Murakami[aut],Isabella Gollini[ctb], Yigong Hu[ctb], Fiona H Evans[ctb]
Maintainer: Binbin Lu <binbinlu@whu.edu.cn>

Diff between GWmodel versions 2.2-2 dated 2020-11-22 and 2.2-3 dated 2021-02-07

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New package Rwtss with initial version 0.8.0
Package: Rwtss
Title: Client for Web Time-Series Service
Version: 0.8.0
Authors@R: c(person(given = "Gilberto", family = "Queiroz", role = c("aut"), email ="gilberto.queiroz@inpe.br", comment = c(ORCID = "0000-0001-7534-0219")), person(given = "Gilberto", family = "Camara", role = c("aut", "cre"), email = "gilberto.camara@inpe.br", comment = c(ORCID = "0000-0002-3681-487X")), person(given = "Pedro", family = "Andrade", role = c("aut"), email = "pedro.andrade@inpe.br", comment = c(ORCID = "0000-0001-8675-4046")), person(given = "Felipe", family = "Souza", role = c('aut'), email = 'felipe.carvalho@inpe.br'), person(given = "Luiz", family = "Assis", role = c("aut"), email ="luiz.assis@inpe.br") )
Maintainer: Gilberto Camara <gilberto.camara@inpe.br>
Description: Allows remote access to satellite image time series provided by web time series services (WTSS). The WTSS API includes functions for listing the data sets available in WTSS servers, describing the contents of a data set, and retrieving a time series based on spatial location and temporal filters.
URL: https://github.com/e-sensing/Rwtss/
BugReports: https://github.com/e-sensing/Rwtss/issues
ByteCompile: true
LazyData: true
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.6.0)
Imports: assertthat, dplyr, geosphere, ggplot2, reshape2, jsonlite, lubridate, magrittr, purrr, httr, stats, stringr, tibble, zoo
RoxygenNote: 7.1.1
Suggests: bfast, knitr, rmarkdown, roxygen2, testthat, spelling, vcr
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2021-02-01 21:25:09 UTC; gilbertocamara
Author: Gilberto Queiroz [aut] (<https://orcid.org/0000-0001-7534-0219>), Gilberto Camara [aut, cre] (<https://orcid.org/0000-0002-3681-487X>), Pedro Andrade [aut] (<https://orcid.org/0000-0001-8675-4046>), Felipe Souza [aut], Luiz Assis [aut]
Repository: CRAN
Date/Publication: 2021-02-07 10:50:08 UTC

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New package osmgeosample with initial version 0.1
Package: osmgeosample
Title: Construction of Geostatistical Sampling Designs with OSM Data
Version: 0.1
Authors@R: c( person("Henry", "Crosby", email = "henry.crosby@warwick.ac.uk", role = "cre"), person("Godwin", "Yeobah", email = "Godwin.Yeobah@warwick.ac.uk", role = "aut"), person("Joao", "Porto De Albuquerque", email = "J.Porto@warwick.ac.uk", role = "aut") )
Maintainer: Henry Crosby <henry.crosby@warwick.ac.uk>
Imports: dplyr, geoR, graphics, mapview, nngeo, osmdata, pdist, processx, rgdal, sp, splancs, stats, qpdf, Rcpp, tibble, sf, methods
Depends: R (>= 3.0.0)
Suggests: PrevMap, rmarkdown, markdown, leafem, viridisLite,raster, knitr, testthat
Description: The utilisation of the functionality provided by the 'OSMData' and 'geosample' to allow users to create spatially continuous or discrete random samples from a pre-defined spatial border using OSM data. Reference: Joao Porto de Albuquerque, Godwin Yeboah, Vangelis Pitidis, Philipp Ulbrich (2019) <doi:10.13140/RG.2.2.13710.20804>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: yes
LinkingTo: Rcpp
Packaged: 2021-02-01 20:25:30 UTC; henry
Author: Henry Crosby [cre], Godwin Yeobah [aut], Joao Porto De Albuquerque [aut]
Repository: CRAN
Date/Publication: 2021-02-07 10:40:02 UTC

More information about osmgeosample at CRAN
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New package mlsbm with initial version 0.99.2
Package: mlsbm
Title: Efficient Estimation of Bayesian SBMs & MLSBMs
Version: 0.99.2
Authors@R: c(person(given = "Carter", family = "Allen", role = c("aut", "cre"), email = "carter.allen12@gmail.com", comment = c(ORCID = "0000-0001-6937-7234")), person(given = "Dongjun", family = "Chung", role = c("aut")))
Description: Fit Bayesian stochastic block models (SBMs) and multi-level stochastic block models (MLSBMs) using efficient Gibbs sampling implemented in 'Rcpp'. The models assume symmetric, non-reflexive graphs (no self-loops) with unweighted, binary edges. Data are input as a symmetric binary adjacency matrix (SBMs), or list of such matrices (MLSBMs).
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp
Depends: R (>= 2.10)
NeedsCompilation: yes
Packaged: 2021-02-01 21:22:53 UTC; carterallen
Author: Carter Allen [aut, cre] (<https://orcid.org/0000-0001-6937-7234>), Dongjun Chung [aut]
Maintainer: Carter Allen <carter.allen12@gmail.com>
Repository: CRAN
Date/Publication: 2021-02-07 10:50:02 UTC

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New package cronologia with initial version 0.1.0
Package: cronologia
Type: Package
Title: Create an HTML Vertical Timeline from a Data Frame in 'rmarkdown' and 'shiny'
Version: 0.1.0
Author: Mohamed El Fodil Ihaddaden
Maintainer: Mohamed El Fodil Ihaddaden <ihaddaden.fodeil@gmail.com>
Description: Creates an HTML vertical timeline from a data frame as an input for 'rmarkdown' documents and 'shiny' applications.
License: AGPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: htmltools, glue
RoxygenNote: 7.1.1
URL: https://github.com/feddelegrand7/cronologia
BugReports: https://github.com/feddelegrand7/cronologia/issues
Suggests: testthat (>= 2.0.0), covr
Config/testthat/edition: 2
NeedsCompilation: no
Packaged: 2021-02-01 23:55:11 UTC; Administrateur
Repository: CRAN
Date/Publication: 2021-02-07 10:50:05 UTC

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New package CEDARS with initial version 1.90
Package: CEDARS
Type: Package
Title: Simple and Efficient Pipeline for Electronic Health Record Annotation
Description: Streamlined annotation pipeline for collection and aggregation of time-to-event data in retrospective clinical studies. 'CEDARS' aims to systematize and accelerate the review of electronic health record (EHR) corpora. It accomplishes those goals by deploying natural language processing as a tool to assist detection and characterization of clinical events by human abstractors. The online user manual presents the necessary steps to install 'CEDARS', process EHR corpora and obtain clinical event dates: <https://cedars.io>.
Version: 1.90
Authors@R: person("Simon", "Mantha", email = "smantha@cedars.io", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-4277-5261"))
Imports: fastmatch, jsonlite, mongolite, parallel, readr, shiny, udpipe, utils
License: GPL-3
URL: https://cedars.io (main) https://github.com/simon-hans/CEDARS (devel)
BugReports: https://github.com/simon-hans/CEDARS/issues
Depends: R (>= 3.5.0)
RoxygenNote: 7.1.1
Language: en-US
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2021-01-31 23:38:20 UTC; manthas
Author: Simon Mantha [aut, cre] (<https://orcid.org/0000-0003-4277-5261>)
Maintainer: Simon Mantha <smantha@cedars.io>
Repository: CRAN
Date/Publication: 2021-02-07 10:40:08 UTC

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New package benford with initial version 0.1.0
Package: benford
Type: Package
Title: Benford's Analysis on Large Data Sets
Version: 0.1.0
Author: Vitor Hugo Moreau
Maintainer: Vitor Hugo Moreau <vitorhmc@ufba.br>
Description: Perform the Benford's Analysis to a data set in order to evaluate if it contains human fabricated data. For more details on the method see Moreau, 2021, Model Assist. Statist. Appl., in press.
License: Creative Commons Attribution 4.0 International License
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2021-02-01 20:31:58 UTC; vhmoreau
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2021-02-07 10:40:05 UTC

More information about benford at CRAN
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Package webchem updated to version 1.1.1 with previous version 1.1.0 dated 2020-10-02

Title: Chemical Information from the Web
Description: Chemical information from around the web. This package interacts with a suite of web services for chemical information. Sources include: Alan Wood's Compendium of Pesticide Common Names, Chemical Identifier Resolver, ChEBI, Chemical Translation Service, ChemIDplus, ChemSpider, ETOX, Flavornet, NIST Chemistry WebBook, OPSIN, PAN Pesticide Database, PubChem, SRS, Wikidata.
Author: Eduard Szöcs [aut], Robert Allaway [ctb], Daniel Muench [ctb], Johannes Ranke [ctb], Andreas Scharmüller [ctb], Eric R Scott [ctb], Jan Stanstrup [ctb], João Vitor F Cavalcante [ctb], Gordon Getzinger [ctb], Tamás Stirling [ctb, cre]
Maintainer: Tamás Stirling <stirling.tamas@gmail.com>

Diff between webchem versions 1.1.0 dated 2020-10-02 and 1.1.1 dated 2021-02-07

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Package RankingProject updated to version 0.3.0 with previous version 0.2.0 dated 2020-01-29

Title: The Ranking Project: Visualizations for Comparing Populations
Description: Functions to generate plots and tables for comparing independently- sampled populations. Companion package to "A Primer on Visualizations for Comparing Populations, Including the Issue of Overlapping Confidence Intervals" by Wright, Klein, and Wieczorek (2019) <DOI:10.1080/00031305.2017.1392359> and "A Joint Confidence Region for an Overall Ranking of Populations" by Klein, Wright, and Wieczorek (2020) <DOI:10.1111/rssc.12402>.
Author: Jerzy Wieczorek [cre, aut], Joel Beard [ctb], Andy Liaw [ctb], Robert Gentleman [ctb], Martin Maechler [ctb]
Maintainer: Jerzy Wieczorek <jerzywieczorek@gmail.com>

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Package Pareto updated to version 2.3.0 with previous version 2.2.2 dated 2021-01-27

Title: The Pareto, Piecewise Pareto and Generalized Pareto Distribution
Description: Utilities for the Pareto, piecewise Pareto and generalized Pareto distribution that are useful for reinsurance pricing. In particular, the package provides a non-trivial algorithm that can be used to match the expected losses of a tower of reinsurance layers with a layer-independent collective risk model. The theoretical background of the matching algorithm and most other methods are described in Ulrich Riegel (2018) <doi:10.1007/s13385-018-0177-3>.
Author: Ulrich Riegel [aut, cre]
Maintainer: Ulrich Riegel <ulrich.riegel@gmx.de>

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Package ks updated to version 1.12.0 with previous version 1.11.7 dated 2020-02-11

Title: Kernel Smoothing
Description: Kernel smoothers for univariate and multivariate data, including densities, density derivatives, cumulative distributions, clustering, classification, density ridges, significant modal regions, and two-sample hypothesis tests. Chacon & Duong (2018) <doi:10.1201/9780429485572>.
Author: Tarn Duong [aut, cre], Matt Wand [ctb], Jose Chacon [ctb], Artur Gramacki [ctb]
Maintainer: Tarn Duong <tarn.duong@gmail.com>

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Package alakazam updated to version 1.1.0 with previous version 1.0.2 dated 2020-07-18

Title: Immunoglobulin Clonal Lineage and Diversity Analysis
Description: Provides methods for high-throughput adaptive immune receptor repertoire sequencing (AIRR-Seq; Rep-Seq) analysis. In particular, immunoglobulin (Ig) sequence lineage reconstruction, lineage topology analysis, diversity profiling, amino acid property analysis and gene usage. Citations: Gupta and Vander Heiden, et al (2017) <doi:10.1093/bioinformatics/btv359>, Stern, Yaari and Vander Heiden, et al (2014) <doi:10.1126/scitranslmed.3008879>.
Author: Namita Gupta [aut], Susanna Marquez [aut], Nima Nouri [aut], Ruoyi Jiang [aut], Julian Zhou [aut], Kenneth Hoehn [aut], Daniel Gadala-Maria [ctb], Edel Aron [ctb], Jason Vander Heiden [cre, aut], Steven Kleinstein [aut, cph]
Maintainer: Jason Vander Heiden <jason.vanderheiden@gmail.com>

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