Mon, 01 Mar 2021

Package packageRank updated to version 0.4.0 with previous version 0.3.5 dated 2020-05-08

Title: Computation and Visualization of Package Download Counts and Percentiles
Description: Compute and visualize the cross-sectional and longitudinal number and rank percentile of package downloads from RStudio's CRAN mirror.
Author: Peter Li [aut, cre]
Maintainer: Peter Li <lindbrook@gmail.com>

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Package bestNormalize updated to version 1.7.0 with previous version 1.6.1 dated 2020-06-08

Title: Normalizing Transformation Functions
Description: Estimate a suite of normalizing transformations, including a new adaptation of a technique based on ranks which can guarantee normally distributed transformed data if there are no ties: ordered quantile normalization (ORQ). ORQ normalization combines a rank-mapping approach with a shifted logit approximation that allows the transformation to work on data outside the original domain. It is also able to handle new data within the original domain via linear interpolation. The package is built to estimate the best normalizing transformation for a vector consistently and accurately. It implements the Box-Cox transformation, the Yeo-Johnson transformation, three types of Lambert WxF transformations, and the ordered quantile normalization transformation. It estimates the normalization efficacy of other commonly used transformations, and it allows users to specify custom transformations or normalization statistics. Finally, functionality can be integrated into a machine learning workflow via recipes.
Author: Ryan Andrew Peterson [aut, cre]
Maintainer: Ryan Andrew Peterson <ryan.a.peterson@cuanschutz.edu>

Diff between bestNormalize versions 1.6.1 dated 2020-06-08 and 1.7.0 dated 2021-03-01

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Package autostsm updated to version 1.2.1 with previous version 1.2 dated 2021-02-05

Title: Automatic Structural Time Series Models
Description: Automatic model selection for structural time series decomposition into trend, cycle, and seasonal components using the Kalman filter. See Koopman, Siem Jan and Marius Ooms (2012) "Forecasting Economic Time Series Using Unobserved Components Time Series Models <doi:10.1093/oxfordhb/9780195398649.013.0006>.
Author: Alex Hubbard
Maintainer: Alex Hubbard <hubbard.alex@gmail.com>

Diff between autostsm versions 1.2 dated 2021-02-05 and 1.2.1 dated 2021-03-01

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Package sparklyr.flint updated to version 0.2.1 with previous version 0.2.0 dated 2020-09-25

Title: Sparklyr Extension for 'Flint'
Description: This sparklyr extension makes 'Flint' time series library functionalities (<https://github.com/twosigma/flint>) easily accessible through R.
Author: Yitao Li [aut, cre] (<https://orcid.org/0000-0002-1261-905X>)
Maintainer: Yitao Li <yitao@rstudio.com>

Diff between sparklyr.flint versions 0.2.0 dated 2020-09-25 and 0.2.1 dated 2021-03-01

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Package MomTrunc updated to version 5.97 with previous version 5.91 dated 2020-11-05

Title: Moments of Folded and Doubly Truncated Multivariate Distributions
Description: It computes arbitrary products moments (mean vector and variance-covariance matrix), for some double truncated (and folded) multivariate distributions. These distributions belong to the family of selection elliptical distributions, which includes well known skewed distributions as the unified skew-t distribution (SUT) and its particular cases as the extended skew-t (EST), skew-t (ST) and the symmetric student-t (T) distribution. Analogous normal cases unified skew-normal (SUN), extended skew-normal (ESN), skew-normal (SN), and symmetric normal (N) are also included. Density, probabilities and random deviates are also offered for these members. References used for this package: Arellano-Valle, R. B. & Genton, M. G. (2005). On fundamental skew distributions. Journal of Multivariate Analysis, 96, 93-116. Galarza C.E., Matos L.A., Dey D.K. & Lachos V.H. (2019) On Moments of Folded and Truncated Multivariate Extended Skew-Normal Distributions. Technical report. ID 19-14. University of Connecticut. <https://stat.uconn.edu/tech-reports-2019/>.
Author: Christian E. Galarza, Raymond Kan and Victor H. Lachos
Maintainer: Christian E. Galarza <cgalarza88@gmail.com>

Diff between MomTrunc versions 5.91 dated 2020-11-05 and 5.97 dated 2021-03-01

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Package FMM updated to version 0.1.2 with previous version 0.1.1 dated 2021-01-22

Title: Rhythmic Patterns Modeling by FMM Models
Description: Provides a collection of functions to fit and explore single, multi-component and restricted Frequency Modulated Moebius (FMM) models. 'FMM' is a nonlinear parametric regression model capable of fitting non-sinusoidal shapes in rhythmic patterns. Details about the mathematical formulation of 'FMM' models can be found in Rueda et al. (2019) <doi:10.1038/s41598-019-54569-1>.
Author: Adrian Lamela, Itziar Fernandez, Yolanda Larriba, Alejandro Rodriguez, Cristina Rueda
Maintainer: Itziar Fernandez <itziar.fernandez@uva.es>

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Package vimp updated to version 2.1.9 with previous version 2.1.6 dated 2021-01-08

Title: Perform Inference on Algorithm-Agnostic Variable Importance
Description: Calculate point estimates of and valid confidence intervals for nonparametric, algorithm-agnostic variable importance measures in high and low dimensions, using flexible estimators of the underlying regression functions. For more information about the methods, please see Williamson et al. (Biometrics, 2020), Williamson et al. (arXiv, 2020+) <arXiv:2004.03683>, and Williamson and Feng (ICML, 2020).
Author: Brian D. Williamson [aut, cre] (<https://orcid.org/0000-0002-7024-548X>), Jean Feng [ctb], Noah Simon [ths] (<https://orcid.org/0000-0002-8985-2474>), Marco Carone [ths] (<https://orcid.org/0000-0003-2106-0953>)
Maintainer: Brian D. Williamson <bwillia2@fredhutch.org>

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Package rio updated to version 0.5.26 with previous version 0.5.16 dated 2018-11-26

Title: A Swiss-Army Knife for Data I/O
Description: Streamlined data import and export by making assumptions that the user is probably willing to make: 'import()' and 'export()' determine the data structure from the file extension, reasonable defaults are used for data import and export (e.g., 'stringsAsFactors=FALSE'), web-based import is natively supported (including from SSL/HTTPS), compressed files can be read directly without explicit decompression, and fast import packages are used where appropriate. An additional convenience function, 'convert()', provides a simple method for converting between file types.
Author: Jason Becker [ctb], Chung-hong Chan [aut], Geoffrey CH Chan [ctb], Thomas J. Leeper [aut, cre] (<https://orcid.org/0000-0003-4097-6326>), Christopher Gandrud [ctb], Andrew MacDonald [ctb], Ista Zahn [ctb], Stanislaus Stadlmann [ctb], Ruaridh Williamson [ctb], Patrick Kennedy [ctb], Ryan Price [ctb], Trevor L Davis [ctb], Nathan Day [ctb], Bill Denney [ctb] (<https://orcid.org/0000-0002-5759-428X>), Alex Bokov [ctb] (<https://orcid.org/0000-0002-0511-9815>)
Maintainer: Thomas J. Leeper <thosjleeper@gmail.com>

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Package RJcluster updated to version 0.1.1 with previous version 0.1.0 dated 2020-09-23

Title: RJ Clustering Algorithm
Description: Clustering algorithm for high dimensional data. This algorithm is ideal for data where n << p.
Author: Rachael Shudde [aut, cre], Shahina Rahman [aut], Valen Johnson [aut]
Maintainer: Rachael Shudde <rachael.shudde@gmail.com>

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Package r2dii.data updated to version 0.1.9 with previous version 0.1.8 dated 2021-02-22

Title: Datasets to Align Financial Markets with Climate Goals
Description: These datasets support the implementation in R of the software 'PACTA' (Paris Agreement Capital Transition Assessment), which is a free tool that calculates the alignment between financial assets and climate scenarios (<https://2degrees-investing.org/>). Financial institutions use 'PACTA' to study how their capital allocation impacts the climate. Because both financial institutions and market data providers keep their data private, this package provides fake, public data to enable the development and use of 'PACTA' in R.
Author: Mauro Lepore [aut, cre, ctr] (<https://orcid.org/0000-0002-1986-7988>), Jackson Hoffart [aut, dtc] (<https://orcid.org/0000-0002-8600-5042>), Klaus Hagedorn [aut], 2 Degrees Investing Initiative [cph, fnd]
Maintainer: Mauro Lepore <maurolepore@gmail.com>

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Package vtable updated to version 1.2.7 with previous version 1.2.6 dated 2020-10-13

Title: Variable Table for Variable Documentation
Description: Automatically generates HTML variable documentation including variable names, labels, classes, value labels (if applicable), value ranges, and summary statistics. See the vignette "vtable" for a package overview.
Author: Nick Huntington-Klein [aut, cre]
Maintainer: Nick Huntington-Klein <nhuntington-klein@seattleu.edu>

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Package params updated to version 0.7.3 with previous version 0.6.1 dated 2016-04-18

Title: Simplify Parameters
Description: An interface to simplify organizing parameters used in a package, using external configuration files. This attempts to provide a cleaner alternative to options().
Author: Sahil Seth [aut, cre], Yihui Xie [ctb] (kable from knitr R/table.R)
Maintainer: Sahil Seth <me@sahilseth.com>

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Package isotree updated to version 0.2.7 with previous version 0.1.28 dated 2021-01-13

Title: Isolation-Based Outlier Detection
Description: Fast and multi-threaded implementation of isolation forest (Liu, Ting, Zhou (2008) <doi:10.1109/ICDM.2008.17>), extended isolation forest (Hariri, Kind, Brunner (2018) <arXiv:1811.02141>), SCiForest (Liu, Ting, Zhou (2010) <doi:10.1007/978-3-642-15883-4_18>), and fair-cut forest (Cortes (2019) <arXiv:1911.06646>), for isolation-based outlier detection, clustered outlier detection, distance or similarity approximation (Cortes (2019) <arXiv:1910.12362>), and imputation of missing values (Cortes (2019) <arXiv:1911.06646>), based on random or guided decision tree splitting. Provides simple heuristics for fitting the model to categorical columns and handling missing data, and offers options for varying between random and guided splits, and for using different splitting criteria.
Author: David Cortes
Maintainer: David Cortes <david.cortes.rivera@gmail.com>

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Package pkgcache updated to version 1.2.0 with previous version 1.1.1 dated 2020-10-11

Title: Cache 'CRAN'-Like Metadata and R Packages
Description: Metadata and package cache for CRAN-like repositories. This is a utility package to be used by package management tools that want to take advantage of caching.
Author: Gábor Csárdi [aut, cre]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>

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Package fmpcloudr updated to version 0.1.5 with previous version 0.1.4 dated 2021-02-22

Title: R Access to the 'FMP Cloud' and 'Financial Modeling Prep' API
Description: Use R to access to the 'FMP Cloud' API <https://fmpcloud.io/> and 'Financial Modeling Prep' API <https://financialmodelingprep.com/developer/docs/>. Data available includes stock prices, market indexes, company fundamentals, 13F holdings data, and much more. A valid API token must be set to enable functions.
Author: Anthony Balentine [aut, cre]
Maintainer: Anthony Balentine <exploringfinance1@gmail.com>

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Package cmfrec updated to version 2.4.5 with previous version 2.4.2 dated 2021-01-10

Title: Collective Matrix Factorization for Recommender Systems
Description: Collective matrix factorization (a.k.a. multi-view or multi-way factorization, Singh, Gordon, (2008) <doi:10.1145/1401890.1401969>) tries to approximate a matrix 'X' as the product of two low-dimensional matrices aided with secondary information matrices about rows and/or columns of 'X' which are also factorized using the same latent components. The intended usage is for recommender systems, dimensionality reduction, and missing value imputation. Implements extensions of the original model (Cortes, (2018) <arXiv:1809.00366>) and can produce different factorizations such as the weighted 'implicit-feedback' model (Hu, Koren, Volinsky, (2008) <doi:10.1109/ICDM.2008.22>), the 'weighted-lambda-regularization' model, (Zhou, Wilkinson, Schreiber, Pan, (2008) <doi:10.1007/978-3-540-68880-8_32>), or the enhanced model with 'implicit features' (Rendle, Zhang, Koren, (2019) <arXiv:1905.01395>), with or without side information. Can use gradient-based procedures or alternating-least squares procedures (Koren, Bell, Volinsky, (2009) <doi:10.1109/MC.2009.263>), with either a Cholesky solver, a faster conjugate gradient solver (Takacs, Pilaszy, Tikk, (2011) <doi:10.1145/2043932.2043987>), or a non-negative coordinate descent solver (Franc, Hlavac, Navara, (2005) <doi:10.1007/11556121_50>), providing efficient methods for sparse and dense data, and mixtures thereof. Supports L1 and L2 regularization in the main models, offers alternative most-popular and content-based models, and implements functionality for cold-start recommendations and imputation of 2D data.
Author: David Cortes [aut, cre, cph], Jorge Nocedal [cph], Naoaki Okazaki [cph]
Maintainer: David Cortes <david.cortes.rivera@gmail.com>

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Package runexp updated to version 0.2.0 with previous version 0.1.0 dated 2021-02-15

Title: Softball Run Expectancy using Markov Chains and Simulation
Description: Implements two methods of estimating runs scored in a softball scenario: (1) theoretical expectation using discrete Markov chains and (2) empirical distribution using multinomial random simulation. Scores are based on player-specific input probabilities (out, single, double, triple, walk, and homerun). Optional inputs include probability of attempting a steal, probability of succeeding in an attempted steal, and an indicator of whether a player is "fast" (e.g. the player could stretch home). These probabilities may be calculated from common player statistics that are publicly available on team's webpages. Scores are evaluated based on a nine-player lineup and may be used to compare lineups, evaluate base scenarios, and compare the offensive potential of individual players. Manuscript forthcoming. See Bukiet & Harold (1997) <doi:10.1287/opre.45.1.14> for implementation of discrete Markov chains.
Author: Annie Sauer [aut, cre], Sierra Merkes [aut]
Maintainer: Annie Sauer <anniees@vt.edu>

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Package rBiasCorrection updated to version 0.2.7 with previous version 0.2.6 dated 2021-02-13

Title: Correct Bias in DNA Methylation Analyses
Description: Implementation of the algorithms (with minor modifications) to correct bias in quantitative DNA methylation analyses as described by Moskalev et al. (2011) <doi:10.1093/nar/gkr213>.
Author: Lorenz A. Kapsner [cre, aut, cph] (<https://orcid.org/0000-0003-1866-860X>), Evgeny A. Moskalev [aut]
Maintainer: Lorenz A. Kapsner <lorenz.kapsner@gmail.com>

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Package NetMix updated to version 0.2.0 with previous version 0.1.5 dated 2020-01-14

Title: Dynamic Mixed-Membership Network Regression Model
Description: Stochastic collapsed variational inference on mixed-membership stochastic blockmodel for networks, incorporating node-level predictors of mixed-membership vectors, as well as dyad-level predictors. For networks observed over time, the model defines a hidden Markov process that allows the effects of node-level predictors to evolve in discrete, historical periods. In addition, the package offers a variety of utilities for exploring results of estimation, including tools for conducting posterior predictive checks of goodness-of-fit and several plotting functions. The package implements methods described in Olivella, Pratt and Imai (2019) 'Dynamic Stochastic Blockmodel Regression for Social Networks: Application to International Conflicts', available at <https://www.santiagoolivella.info/pdfs/socnet.pdf>.
Author: Santiago Olivella [aut, cre], Adeline Lo [aut, cre], Tyler Pratt [aut, cre], Kosuke Imai [aut, cre]
Maintainer: Santiago Olivella <olivella@unc.edu>

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Package decisionSupport updated to version 1.106 with previous version 1.105.3 dated 2020-05-12

Title: Quantitative Support of Decision Making under Uncertainty
Description: Supporting the quantitative analysis of binary welfare based decision making processes using Monte Carlo simulations. Decision support is given on two levels: (i) The actual decision level is to choose between two alternatives under probabilistic uncertainty. This package calculates the optimal decision based on maximizing expected welfare. (ii) The meta decision level is to allocate resources to reduce the uncertainty in the underlying decision problem, i.e to increase the current information to improve the actual decision making process. This problem is dealt with using the Value of Information Analysis. The Expected Value of Information for arbitrary prospective estimates can be calculated as well as Individual Expected Value of Perfect Information. The probabilistic calculations are done via Monte Carlo simulations. This Monte Carlo functionality can be used on its own.
Author: Eike Luedeling [cre, aut] (University of Bonn), Lutz Goehring [aut] (ICRAF and Lutz Goehring Consulting), Katja Schiffers [aut] (University of Bonn), Cory Whitney [aut] (University of Bonn), Eduardo Fernandez [aut] (University of Bonn)
Maintainer: Eike Luedeling <eike@eikeluedeling.com>

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Package CruzPlot updated to version 1.4.5 with previous version 1.4.4 dated 2021-01-25

Title: Plot Shipboard DAS Data
Description: A utility program oriented to create maps, plot data, and do basic data summaries of 'DAS' data <https://swfsc-publications.fisheries.noaa.gov/publications/TM/SWFSC/NOAA-TM-NMFS-SWFSC-305.PDF> produced by 'WinCruz' from the Southwest Fisheries Science Center. <https://www.fisheries.noaa.gov/west-coast/science-data/california-current-marine-mammal-assessment-program>.
Author: Sam Woodman [aut, cre] (<https://orcid.org/0000-0001-6071-8186>), Tim Gerrodette [aut]
Maintainer: Sam Woodman <sam.woodman@noaa.gov>

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Package qwraps2 updated to version 0.5.1 with previous version 0.5.0 dated 2020-09-01

Title: Quick Wraps 2
Description: A collection of (wrapper) functions the creator found useful for quickly placing data summaries and formatted regression results into '.Rnw' or '.Rmd' files. Functions for generating commonly used graphics, such as receiver operating curves or Bland-Altman plots, are also provided by 'qwraps2'. 'qwraps2' is a updated version of a package 'qwraps'. The original version 'qwraps' was never submitted to CRAN but can be found at <https://github.com/dewittpe/qwraps/>. The implementation and limited scope of the functions within 'qwraps2' <https://github.com/dewittpe/qwraps2/> is fundamentally different from 'qwraps'.
Author: Peter DeWitt [aut, cre], Tell Bennett [ctb]
Maintainer: Peter DeWitt <dewittpe@gmail.com>

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Package quarks updated to version 1.0.5 with previous version 1.0.4 dated 2021-02-21

Title: Simple Methods for Calculating Value at Risk and Expected Shortfall
Description: Enables the user to calculate Value at Risk (VaR) and Expected Shortfall (ES) by means of various types of historical simulation. Currently plain historical simulation as well as age- and volatility-weighted historical simulation are implemented in this package. Volatility weighting is carried out via an exponentially weighted moving average (EWMA). The methods of the package are described in Gurrola-Perez, P. and Murphy, D. (2015) <https://EconPapers.repec.org/RePEc:boe:boeewp:0525>.
Author: Sebastian Letmathe [aut, cre] (Paderborn University, Germany)
Maintainer: Sebastian Letmathe <sebastian.letmathe@uni-paderborn.de>

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Package czso updated to version 0.3.4 with previous version 0.3.2 dated 2020-10-22

Title: Use Open Data from the Czech Statistical Office in R
Description: Get programmatic access to the open data provided by the Czech Statistical Office (CZSO, <https://czso.cz>).
Author: Petr Bouchal [aut, cre] (<https://orcid.org/0000-0002-0471-716X>), Jindra Lacko [ctb]
Maintainer: Petr Bouchal <pbouchal@gmail.com>

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Package BiasCorrector updated to version 0.1.3 with previous version 0.1.2 dated 2020-09-22

Title: A GUI to Correct Measurement Bias in DNA Methylation Analyses
Description: A GUI to correct measurement bias in DNA methylation analyses. The 'BiasCorrector' package just wraps the functions implemented in the 'R' package 'rBiasCorrection' into a shiny web application in order to make them more easily accessible.
Author: Lorenz A. Kapsner [cre, aut, cph] (<https://orcid.org/0000-0003-1866-860X>), Evgeny A. Moskalev [aut]
Maintainer: Lorenz A. Kapsner <lorenz.kapsner@gmail.com>

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Package RobinHood updated to version 1.6 with previous version 1.5 dated 2021-01-06

Title: Interface for the RobinHood.com No Commission Investing Platform
Description: Execute API calls to the RobinHood <https://robinhood.com> investing platform. Functionality includes accessing account data and current holdings, retrieving investment statistics and quotes, placing and canceling orders, getting market trading hours, searching investments by popular tag, and interacting with watch lists.
Author: Joseph Blubaugh
Maintainer: Joseph Blubaugh <jestonblu@gmail.com>

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Package ChaosGame updated to version 1.0 with previous version 0.4 dated 2018-12-18

Title: Chaos Game
Description: The main objective of the package is to enter a word of at least two letters based on which an Iterated Function System with Probabilities is constructed, and a two-dimensional fractal containing the chosen word infinitely often is generated via the Chaos Game. Additionally, the package allows to project the two-dimensional fractal on several three-dimensional surfaces and to transform the fractal into another fractal with uniform marginals.
Author: Florian Griessenberger [aut, cre], Manuela Schreyer [aut], Johannes Bartel [aut], Wolfgang Trutschnig [aut]
Maintainer: Florian Griessenberger <florian.griessenberger@sbg.ac.at>

Diff between ChaosGame versions 0.4 dated 2018-12-18 and 1.0 dated 2021-03-01

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Package RPushbullet updated to version 0.3.4 with previous version 0.3.3 dated 2020-01-19

Title: R Interface to the Pushbullet Messaging Service
Description: An R interface to the Pushbullet messaging service which provides fast and efficient notifications (and file transfer) between computers, phones and tablets. An account has to be registered at the site <https://www.pushbullet.com> site to obtain a (free) API key.
Author: Dirk Eddelbuettel with contributions by Bill Evans, Mike Birdgeneau, Henrik Bengtsson, Seth Wenchel, Colin Gillespie and Chan-Yub Park
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package fixest updated to version 0.8.3 with previous version 0.8.2 dated 2021-02-11

Title: Fast Fixed-Effects Estimations
Description: Fast and user-friendly estimation of econometric models with multiple fixed-effects. Includes ordinary least squares (OLS), generalized linear models (GLM) and the negative binomial. The core of the package is based on optimized parallel C++ code, scaling especially well for large data sets. The method to obtain the fixed-effects coefficients is based on Berge (2018) <https://wwwen.uni.lu/content/download/110162/1299525/file/2018_13>. Further provides tools to export and view the results of several estimations with intuitive design to cluster the standard-errors.
Author: Laurent Berge [aut, cre], Sebastian Krantz [ctb]
Maintainer: Laurent Berge <laurent.berge@u-bordeaux.fr>

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Package fftwtools updated to version 0.9-11 with previous version 0.9-10 dated 2021-02-22

Title: Wrapper for 'FFTW3' Includes: One-Dimensional, Two-Dimensional, Three-Dimensional, and Multivariate Transforms
Description: Provides a wrapper for several 'FFTW' functions. This package provides access to the two-dimensional 'FFT', the multivariate 'FFT', and the one-dimensional real to complex 'FFT' using the 'FFTW3' library. The package includes the functions fftw() and mvfftw() which are designed to mimic the functionality of the R functions fft() and mvfft(). The 'FFT' functions have a parameter that allows them to not return the redundant complex conjugate when the input is real data.
Author: Karim Rahim <karim.rahim@queensu.ca>
Maintainer: Karim Rahim <karim.rahim@queensu.ca>

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Package singcar updated to version 0.1.3 with previous version 0.1.2 dated 2021-01-07

Title: Comparing Single Cases to Small Samples
Description: When comparing single cases to control populations and no parameters are known researchers and clinicians must estimate these with a control sample. This is often done when testing a case's abnormality on some variable or testing abnormality of the discrepancy between two variables. Appropriate frequentist and Bayesian methods for doing this are here implemented, including tests allowing for the inclusion of covariates. These have been developed first and foremost by John Crawford and Paul Garthwaite, e.g. in Crawford and Howell (1998) <doi:10.1076/clin.12.4.482.7241>, Crawford and Garthwaite (2005) <doi:10.1037/0894-4105.19.3.318>, Crawford and Garthwaite (2007) <doi:10.1080/02643290701290146> and Crawford, Garthwaite and Ryan (2011) <doi:10.1016/j.cortex.2011.02.017>. The package is also equipped with power calculators for each method.
Author: Jonathan Rittmo [aut, cre] (<https://orcid.org/0000-0001-5075-0166>), Robert McIntosh [aut] (<https://orcid.org/0000-0002-7615-6699>)
Maintainer: Jonathan Rittmo <j.rittmo@gmail.com>

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Package RespirAnalyzer updated to version 1.0.1 with previous version 1.0.0 dated 2021-02-25

Title: Analysis Functions of Respiratory Data
Description: Provides functions for the complete analysis of respiratory data. Consists of a set of functions that allow to preprocessing respiratory data, calculate both regular statistics and nonlinear statistics, conduct group comparison and visualize the results. Especially, Power Spectral Density ('PSD') (A. Eke (2000) <doi:10.1007/s004249900135>), 'MultiScale Entropy(MSE)' ('Madalena Costa(2002)' <doi:10.1103/PhysRevLett.89.068102>) and 'MultiFractal Detrended Fluctuation Analysis(MFDFA)' ('Jan W.Kantelhardt' (2002) <doi:10.1016/S0378-4371(02)01383-3>) were applied for the analysis of respiratory data.
Author: Xiaohua Douglas Zhang [aut, cph], Teng Zhang [aut], Xinzheng Dong [aut, cre]
Maintainer: Xinzheng Dong <dong.xinzheng@foxmail.com>

Diff between RespirAnalyzer versions 1.0.0 dated 2021-02-25 and 1.0.1 dated 2021-03-01

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Package RcmdrPlugin.UCA updated to version 4.3-4 with previous version 4.3-3 dated 2021-02-23

Title: UCA Rcmdr Plug-in
Description: Some extensions to Rcmdr (R Commander), randomness test, variance test for one normal sample and predictions using active model, made by R-UCA project and used in teaching statistics at University of Cadiz (UCA).
Author: Manuel Munoz-Marquez <manuel.munoz@uca.es>
Maintainer: Manuel Munoz-Marquez <manuel.munoz@uca.es>

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Package gkgraphR updated to version 1.0.2 with previous version 1.0.1 dated 2020-08-04

Title: Accessing the Official 'Google Knowledge Graph' API
Description: A simple way to interact with and extract data from the official 'Google Knowledge Graph' API <https://developers.google.com/knowledge-graph/>.
Author: Ricardo Correia [aut, cre] (<https://orcid.org/0000-0001-7359-9091>)
Maintainer: Ricardo Correia <rahc85@gmail.com>

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Package ggrastr updated to version 0.2.3 with previous version 0.2.2 dated 2021-02-19

Title: Rasterize Layers for 'ggplot2'
Description: Rasterize only specific layers of a 'ggplot2' plot while simultaneously keeping all labels and text in vector format. This allows users to keep plots within the reasonable size limit without loosing vector properties of the scale-sensitive information.
Author: Viktor Petukhov [aut, cph], Teun van den Brand [aut], Evan Biederstedt [cre, aut]
Maintainer: Evan Biederstedt <evan.biederstedt@gmail.com>

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Package GEInter updated to version 0.2.0 with previous version 0.1.0 dated 2021-01-21

Title: Robust Gene-Environment Interaction Analysis
Description: For the risk, progression, and response to treatment of many complex diseases, it has been increasingly recognized that gene-environment interactions play important roles beyond the main genetic and environmental effects. In practical interaction analyses, outliers in response variables and covariates are not uncommon. In addition, missingness in environmental factors is routinely encountered in epidemiological studies. The developed package consists of five robust approaches to address the outliers problems, among which two approaches can also accommodate missingness in environmental factors. Both continuous and right censored responses are considered. The proposed approaches are based on penalization and sparse boosting techniques for identifying important interactions, which are realized using efficient algorithms. Beyond the gene-environment analysis, the developed package can also be adopted to conduct analysis on interactions between other types of low-dimensional and high-dimensional data. (Mengyun Wu et al (2017), <doi:10.1080/00949655.2018.1523411>; Mengyun Wu et al (2017), <doi:10.1002/gepi.22055>; Yaqing Xu et al (2018), <doi:10.1080/00949655.2018.1523411>; Yaqing Xu et al (2019), <doi:10.1016/j.ygeno.2018.07.006>).
Author: Mengyun Wu [aut], Xing Qin [aut, cre], Shuangge Ma [aut]
Maintainer: Xing Qin <qin.xing@163.sufe.edu.cn>

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Package CopulaCenR updated to version 1.1.3 with previous version 1.1.2 dated 2019-03-20

Title: Copula-Based Regression Models for Bivariate Censored Data
Description: Copula-based regression models for bivariate censored data, including bivariate right-censored data and bivariate interval-censored data. Currently supports Clayton, Gumbel, Frank, Joe, AMH and Copula2 copula models. For marginal models, it supports parametric (Weibull, Loglogistic, Gompertz) and semiparametric (Cox and transformation) models. Includes methods for convenient prediction and plotting. Also provides a bivariate time-to-event simulation function. Method details can be found in Sun et.al (2019) Lifetime Data Analysis and Sun et.al (In Press) Biostatistics.
Author: Tao Sun, Ying Ding
Maintainer: Tao Sun <tao.sun@pitt.edu>

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More information about CopulaCenR at CRAN
Permanent link

Package c060 updated to version 0.2-6 with previous version 0.2-5 dated 2019-11-29

Title: Extended Inference for Lasso and Elastic-Net Regularized Cox and Generalized Linear Models
Description: The c060 package provides additional functions to perform stability selection, model validation and parameter tuning for glmnet models.
Author: Martin Sill, Thomas Hielscher, Manuela Zucknick, Natalia Becker.
Maintainer: Frederic Bertrand <frederic.bertrand@utt.fr>

Diff between c060 versions 0.2-5 dated 2019-11-29 and 0.2-6 dated 2021-03-01

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More information about c060 at CRAN
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Package BIRDS updated to version 0.1.27.1 with previous version 0.1.2 dated 2020-10-08

Title: Biodiversity Information Review and Decision Support
Description: It helps making the evaluation and preparation of biodiversity data easy, systematic and reproducible. It also helps the users to overlay the point observations into a custom grid that is useful for further analysis. The review summarise statistics that helps evaluate whether a set of species observations is fit-for-use and take decisions upon its use of on further analyses. It does so by quantifying the sampling effort (amount of effort expended during an event) and data completeness (data gaps) to help judge whether the data is representative, valid and fit for any intended purpose. The 'BIRDS' package is most useful when working with heterogeneous data sets with variation in the sampling process, i.e. where data have been collected and reported in various ways and therefore varying in sampling effort and data completeness (i.e. how well the reported observations describe the true state). Primary biodiversity data (PBD) combining data from different data sets, like e.g. Global Biodiversity Information Facility (GBIF) mediated data, commonly vary in the ways data has been generated - containing opportunistically collected presence-only data together with and data from systematic monitoring programs. The set of tools provided is aimed at understanding the process that generated the data (i.e. observing, recording and reporting species into databases). References: Ruete (2015) <doi:10.3897/BDJ.3.e5361>; Szabo, Vesk, Baxter & Possingham (2010) <doi:10.1890/09-0877.1>; Telfer, Preston 6 Rothery (2002) <doi:10.1016/S0006-3207(02)00050-2>.
Author: Debora Arlt [aut] (<https://orcid.org/0000-0003-0874-4250>), Alejandro Ruete [aut, cre] (<https://orcid.org/0000-0001-7681-2812>), Anton Hammarström [aut]
Maintainer: Alejandro Ruete <aleruete@gmail.com>

Diff between BIRDS versions 0.1.2 dated 2020-10-08 and 0.1.27.1 dated 2021-03-01

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Package sparta updated to version 0.7.1 with previous version 0.7.0 dated 2020-12-16

Title: Sparse Tables
Description: Fast Multiplication and Marginalization of Sparse Tables.
Author: Mads Lindskou [aut, cre]
Maintainer: Mads Lindskou <mads@math.aau.dk>

Diff between sparta versions 0.7.0 dated 2020-12-16 and 0.7.1 dated 2021-03-01

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Package mathjaxr updated to version 1.4-0 with previous version 1.2-0 dated 2021-01-30

Title: Using 'Mathjax' in Rd Files
Description: Provides 'MathJax' and macros to enable its use within Rd files for rendering equations in the HTML help files.
Author: Wolfgang Viechtbauer [aut, cre] (<https://orcid.org/0000-0003-3463-4063>)
Maintainer: Wolfgang Viechtbauer <wvb@wvbauer.com>

Diff between mathjaxr versions 1.2-0 dated 2021-01-30 and 1.4-0 dated 2021-03-01

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More information about mathjaxr at CRAN
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Package POSetR updated to version 1.0.1 with previous version 1.0 dated 2021-02-15

Title: Partially Ordered Sets in R
Description: Provides a set of basic tools for generating, analyzing, summarizing and visualizing finite partially ordered sets. In particular, it implements flexible and very efficient algorithms for the extraction of linear extensions and for the computation of mutual ranking probabilities and other user-defined functionals, over them. The package is meant as a computationally efficient "engine", for the implementation of data analysis procedures, on systems of multidimensional ordinal indicators and partially ordered data, in the spirit of Fattore, M. (2016) "Partially ordered sets and the measurement of multidimensional ordinal deprivation", Social Indicators Research <DOI:10.1007/s11205-015-1059-6>, and Fattore M. and Arcagni, A. (2018) "A reduced posetic approach to the measurement of multidimensional ordinal deprivation", Social Indicators Research <DOI:10.1007/s11205-016-1501-4>.
Author: Alberto Arcagni [aut, cre], Alessandro Avellone [aut], Marco Fattore [aut]
Maintainer: Alberto Arcagni <alberto.arcagni@uniroma1.it>

Diff between POSetR versions 1.0 dated 2021-02-15 and 1.0.1 dated 2021-03-01

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Package politeness updated to version 0.7.7 with previous version 0.7.6 dated 2021-01-13

Title: Detecting Politeness Features in Text
Description: Detecting markers of politeness in English natural language. This package allows researchers to easily visualize and quantify politeness between groups of documents. This package combines prior research on the linguistic markers of politeness. We thank the Spencer Foundation, the Hewlett Foundation, and Harvard's Institute for Quantitative Social Science for support.
Author: Mike Yeomans, Alejandro Kantor, Dustin Tingley
Maintainer: Mike Yeomans <mk.yeomans@gmail.com>

Diff between politeness versions 0.7.6 dated 2021-01-13 and 0.7.7 dated 2021-03-01

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Package drawsample updated to version 1.0.0 with previous version 0.1.1 dated 2020-12-02

Title: Draw Samples with the Desired Properties from a Data Set
Description: A tool to sample data with the desired properties.Samples can be drawn by purposive sampling with determining distributional conditions, such as deviation from normality (skewness and kurtosis), and sample size in quantitative research studies. For purposive sampling, a researcher has something in mind and participants that fit the purpose of the study are included (Etikan,Musa, & Alkassim, 2015) <doi:10.11648/j.ajtas.20160501.11>.Purposive sampling can be useful for answering many research questions (Klar & Leeper, 2019) <doi:10.1002/9781119083771.ch21>.
Author: Kubra Atalay Kabasakal [aut, cre] (<https://orcid.org/0000-0002-3580-5568>), Huseyin Yıldız [ctb] (<https://orcid.org/0000-0003-2387-263X>)
Maintainer: Kubra Atalay Kabasakal <katalay@hacettepe.edu.tr>

Diff between drawsample versions 0.1.1 dated 2020-12-02 and 1.0.0 dated 2021-03-01

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New package taxalight with initial version 0.1.1
Package: taxalight
Version: 0.1.1
Title: A Lightweight and Lightning-Fast Taxonomic Naming Interface
Description: Creates a local Lightning Memory-Mapped Database ('LMDB') of many commonly used taxonomic authorities and provides functions that can quickly query this data. Supported taxonomic authorities include the Integrated Taxonomic Information System ('ITIS'), National Center for Biotechnology Information ('NCBI'), Global Biodiversity Information Facility ('GBIF'), Catalogue of Life ('COL'), and Open Tree Taxonomy ('OTT'). Name and identifier resolution using 'LMDB' can be hundreds of times faster than either relational databases or internet-based queries. Precise data provenance information for data derived from naming providers is also included.
Authors@R: c( person("Carl", "Boettiger", , "cboettig@gmail.com", c("aut", "cre"), comment = c(ORCID = "0000-0002-1642-628X")), person("Kari", "Norman", role= "aut", comment = c(ORCID = "0000-0002-2029-2325")) )
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
ByteCompile: true
Depends: R (>= 4.0)
Imports: thor, contentid
Suggests: jsonlite, spelling, testthat, covr, knitr, rmarkdown, progress, utf8
URL: https://github.com/cboettig/taxalight
BugReports: https://github.com/cboettig/taxalight
Language: en-US
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-27 04:16:04 UTC; cboettig
Author: Carl Boettiger [aut, cre] (<https://orcid.org/0000-0002-1642-628X>), Kari Norman [aut] (<https://orcid.org/0000-0002-2029-2325>)
Maintainer: Carl Boettiger <cboettig@gmail.com>
Repository: CRAN
Date/Publication: 2021-03-01 10:20:02 UTC

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New package metro with initial version 0.9.1
Package: metro
Title: Washington Metropolitan Area Transit Authority API
Version: 0.9.1
Authors@R: person(given = "Kiernan", family = "Nicholls", role = c("aut", "cre"), email = "kiernann@protonmail.com")
Description: The Washington Metropolitan Area Transit Authority is a government agency operating light rail and passenger buses in the Washington D.C. area. With a free developer account, access their 'Metro Transparent Data Sets API' <https://developer.wmata.com/> to return data frames of transit data for easy analysis.
License: MIT + file LICENSE
URL: https://github.com/kiernann/metro, https://kiernann.com/metro/
BugReports: https://github.com/kiernann/metro/issues
Depends: R (>= 2.10)
Imports: geodist (>= 0.0.6), hms (>= 1.0.0), httr (>= 1.4.2), jsonlite (>= 1.7.1), tibble (>= 3.0.4)
Suggests: covr (>= 3.5.1), spelling (>= 2.2), testthat (>= 3.0.0)
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-26 17:31:14 UTC; kiernan
Author: Kiernan Nicholls [aut, cre]
Maintainer: Kiernan Nicholls <kiernann@protonmail.com>
Repository: CRAN
Date/Publication: 2021-03-01 10:10:02 UTC

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New package domir with initial version 0.0.0
Package: domir
Title: Tools to Support Relative Importance Analysis
Version: 0.0.0
Date: 2021-2-27
Authors@R: person(given = "Joseph", family = "Luchman", role = c("aut", "cre"), email = "jluchman@gmail.com", comment = c(ORCID = "0000-0002-8886-9717"))
Description: Provides tools that support relative importance analysis focusing on dominance analysis. Dominance analysis is a methodology for determining the relative importance of predictors/features/independent variables (Azen, R., & Budescu, D. V. (2003) <doi:10.1037/1082-989X.8.2.129>; Groemping, U. (2007) <doi:10.1198/000313007X188252>) as well as parameter estimates (Luchman, J. N, Lei, X., & Kaplan, S. (2020) <doi:10.47263/JASEM.4(2)02>). These tools are intended to extend relative importance analysis to, effectively, any statistical or machine learning function as defined or desired by the user-especially those where the user wants to use custom importance/fit metric or modeling function.
Imports: methods, datasets
Suggests: dominanceanalysis, relaimpo, yhat
License: GPL (>= 2)
URL: <https://github.com/jluchman/domir>
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-27 15:32:28 UTC; josephluchman
Author: Joseph Luchman [aut, cre] (<https://orcid.org/0000-0002-8886-9717>)
Maintainer: Joseph Luchman <jluchman@gmail.com>
Repository: CRAN
Date/Publication: 2021-03-01 10:40:02 UTC

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Package xtensor updated to version 0.13.2-0 with previous version 0.11.1-0 dated 2019-06-22

Title: Headers for the 'xtensor' Library
Description: The 'xtensor' C++ library for numerical analysis with multi-dimensional array expressions is provided as a header-only C++14 library. It offers an extensible expression system enabling lazy broadcasting; an API following the idioms of the C++ standard library; and tools to manipulate array expressions and build upon 'xtensor'.
Author: Johan Mabille, Sylvain Corlay and Wolf Vollprecht
Maintainer: Sylvain Corlay <sylvain.corlay@gmail.com>

Diff between xtensor versions 0.11.1-0 dated 2019-06-22 and 0.13.2-0 dated 2021-03-01

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 xtensor-0.13.2-0/xtensor/LICENSE                                                  |    2 
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 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_avx512_bool.hpp           |   87 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_avx512_complex.hpp        |   18 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_avx512_conversion.hpp     |  119 +
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_avx512_double.hpp         |   25 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_avx512_float.hpp          |   26 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_avx512_int16.hpp          |  144 +
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_avx512_int32.hpp          |   30 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_avx512_int64.hpp          |   37 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_avx512_int8.hpp           |   97 -
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_avx512_int_base.hpp       |   75 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_avx_complex.hpp           |    4 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_avx_conversion.hpp        |   91 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_avx_double.hpp            |   35 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_avx_float.hpp             |   37 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_avx_int16.hpp             |  102 -
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_avx_int32.hpp             |   83 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_avx_int64.hpp             |   70 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_avx_int8.hpp              |   70 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_avx_int_base.hpp          |   75 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_base.hpp                  |  139 +
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_base_bool.hpp             |   97 +
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_complex_base.hpp          |    6 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_fallback.hpp              |   46 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_int_conversion.hpp        |    4 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_neon_bool.hpp             |   99 -
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_neon_complex.hpp          |    6 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_neon_conversion.hpp       |   31 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_neon_double.hpp           |   23 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_neon_float.hpp            |   26 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_neon_int16.hpp            |   45 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_neon_int32.hpp            |   38 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_neon_int64.hpp            |   52 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_neon_int8.hpp             |   45 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_neon_uint16.hpp           |   36 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_neon_uint32.hpp           |   29 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_neon_uint64.hpp           |   43 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_neon_uint8.hpp            |   41 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_neon_utils.hpp            |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_sse_complex.hpp           |    4 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_sse_conversion.hpp        |   43 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_sse_double.hpp            |   33 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_sse_float.hpp             |   35 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_sse_int16.hpp             |   52 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_sse_int32.hpp             |   52 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_sse_int64.hpp             |   56 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_sse_int8.hpp              |   43 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_sse_int_base.hpp          |   56 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_traits.hpp                |  147 -
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_types_include.hpp         |   22 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/types/xsimd_utils.hpp                 |    8 
 xtensor-0.13.2-0/xtensor/inst/include/xsimd/xsimd.hpp                             |    4 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor-r/rarray.hpp                        |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor-r/rcontainer.hpp                    |   27 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor-r/rcpp_extensions.hpp               |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor-r/roptional.hpp                     |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor-r/rtensor.hpp                       |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor-r/rvectorize.hpp                    |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor-r/xtensor_r_config.hpp              |    7 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xaccessible.hpp                     |    6 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xaccumulator.hpp                    |  138 -
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xadapt.hpp                          |  150 +
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xarray.hpp                          |    4 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xassign.hpp                         |  221 +-
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xaxis_iterator.hpp                  |  217 +-
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xaxis_slice_iterator.hpp            |only
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xbroadcast.hpp                      |   42 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xbuffer_adaptor.hpp                 |  295 ++-
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xbuilder.hpp                        |  377 ++--
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xchunked_array.hpp                  |only
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xcomplex.hpp                        |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xcontainer.hpp                      |   87 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xcsv.hpp                            |   69 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xdynamic_view.hpp                   |    5 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xeval.hpp                           |  121 +
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xexception.hpp                      |  105 -
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xexpression.hpp                     |  112 -
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xexpression_holder.hpp              |   37 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xexpression_traits.hpp              |   57 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xfixed.hpp                          |  264 +-
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xfunction.hpp                       |  152 -
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xfunctor_view.hpp                   |   39 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xgenerator.hpp                      |   34 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xhistogram.hpp                      |  245 +-
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xindex_view.hpp                     |   41 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xinfo.hpp                           |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xio.hpp                             |   37 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xiterable.hpp                       |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xiterator.hpp                       |   50 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xjson.hpp                           |   55 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xlayout.hpp                         |   10 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xmanipulation.hpp                   |  420 +++-
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xmasked_view.hpp                    |   34 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xmath.hpp                           |  941 +++++-----
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xmime.hpp                           |   13 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xnoalias.hpp                        |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xnorm.hpp                           |   47 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xnpy.hpp                            |  146 -
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xoffset_view.hpp                    |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xoperation.hpp                      |   94 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xoptional.hpp                       |  175 +
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xoptional_assembly.hpp              |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xoptional_assembly_base.hpp         |   21 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xoptional_assembly_storage.hpp      |    4 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xpad.hpp                            |  200 +-
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xrandom.hpp                         |  563 +++++
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xreducer.hpp                        |  251 ++
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xrepeat.hpp                         |only
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xscalar.hpp                         |   34 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xsemantic.hpp                       |   58 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xset_operation.hpp                  |only
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xshape.hpp                          |   89 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xslice.hpp                          |   96 -
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xsort.hpp                           |   53 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xstorage.hpp                        |  145 +
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xstrided_view.hpp                   |  106 -
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xstrided_view_base.hpp              |   64 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xstrides.hpp                        |    8 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xtensor.hpp                         |    8 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xtensor_config.hpp                  |   43 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xtensor_forward.hpp                 |   14 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xtensor_simd.hpp                    |  108 +
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xutils.hpp                          |  116 +
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xvectorize.hpp                      |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xview.hpp                           |  188 +
 xtensor-0.13.2-0/xtensor/inst/include/xtensor/xview_utils.hpp                     |    9 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xany.hpp                                |   15 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xbase64.hpp                             |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xbasic_fixed_string.hpp                 |   74 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xclosure.hpp                            |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xcomplex.hpp                            |   46 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xcomplex_sequence.hpp                   |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xdynamic_bitset.hpp                     |   20 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xfunctional.hpp                         |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xhalf_float.hpp                         |only
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xhalf_float_impl.hpp                    |only
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xhash.hpp                               |   85 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xhierarchy_generator.hpp                |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xiterator_base.hpp                      |  193 ++
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xjson.hpp                               |   24 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xmasked_value.hpp                       |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xmasked_value_meta.hpp                  |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xmeta_utils.hpp                         |   95 -
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xmultimethods.hpp                       |only
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xoptional.hpp                           |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xoptional_meta.hpp                      |    7 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xoptional_sequence.hpp                  |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xplatform.hpp                           |only
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xsequence.hpp                           |   20 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xspan.hpp                               |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xspan_impl.hpp                          |    8 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xsystem.hpp                             |only
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xtl_config.hpp                          |   17 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xtype_traits.hpp                        |   88 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xvariant.hpp                            |    3 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xvariant_impl.hpp                       |   33 
 xtensor-0.13.2-0/xtensor/inst/include/xtl/xvisitor.hpp                            |only
 xtensor-0.13.2-0/xtensor/man/xtensor-package.Rd                                   |    4 
 xtensor-0.13.2-0/xtensor/tools/vendor                                             |   16 
 195 files changed, 8633 insertions(+), 2728 deletions(-)

More information about xtensor at CRAN
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New package SignacX with initial version 2.2.0
Package: SignacX
Version: 2.2.0
Date: 2021-02-24
Title: Cell Type Identification and Discovery from Single Cell Gene Expression Data
Authors@R: c( person(given = "Mathew", family = "Chamberlain", email = "mathew.chamberlain@sanofi.com", role = c( "aut","cre")), person(given = "Virginia", family = "Savova", email = "virginia.savova@sanofi.com", role = c( "aut")), person(given = "Richa", family = "Hanamsagar", email = "richa.hanamsagar@sanofi.com", role = c( "aut")), person(given = "Frank", family = "Nestle", email = "frank.nestle@sanofi.com", role = c( "aut")), person(given = "Emanuele", family = "de Rinaldis", email = "Emanuele.deRinaldis@sanofi.com", role = c( "aut")), person("Sanofi US", role = "fnd"))
Maintainer: Mathew Chamberlain <mathew.chamberlain@sanofi.com>
URL: https://github.com/mathewchamberlain/SignacX
BugReports: https://github.com/mathewchamberlain/SignacX/issues
Imports: neuralnet, lme4, methods, Matrix, pbmcapply, Seurat(>= 3.2.0), RJSONIO, igraph (>= 1.2.1), jsonlite (>= 1.5), RColorBrewer (>= 1.1.2), stats
Suggests: hdf5r, rhdf5, knitr, rmarkdown, formatR
Description: An implementation of neural networks trained with flow-sorted gene expression data to classify cellular phenotypes in single cell RNA-sequencing data. See Chamberlain M et al. (2021) <doi:10.1101/2021.02.01.429207> for more details.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-02-26 12:18:12 UTC; i0369218
Author: Mathew Chamberlain [aut, cre], Virginia Savova [aut], Richa Hanamsagar [aut], Frank Nestle [aut], Emanuele de Rinaldis [aut], Sanofi US [fnd]
Repository: CRAN
Date/Publication: 2021-03-01 09:30:05 UTC

More information about SignacX at CRAN
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New package PolicyPortfolios with initial version 0.2.2
Package: PolicyPortfolios
Title: Tools for Managing, Measuring and Visualizing Policy Portfolios
Description: Tools for simplifying the creation and management of data structures suitable for dealing with policy portfolios, that is, two-dimensional spaces of policy instruments and policy targets. The package also allows to generate measures of portfolio characteristics and facilitates their visualization.
Version: 0.2.2
Authors@R: person(given = "Xavier", family = "Fernández i Marín", email = "xavier.fim@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-9522-8870"))
Depends: R (>= 3.5), dplyr (>= 1.0),
Imports: ggplot2, vegan, ineq, mgcv, reshape2,
Suggests: testthat, devtools, rmarkdown, knitr, tidyr,
License: GPL-3
URL: http://xavier-fim.net/packages/PolicyPortfolios/, https://github.com/xfim/PolicyPortfolios
BugReports: https://github.com/xfim/PolicyPortfolios/issues
Encoding: UTF-8
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-02-26 11:52:02 UTC; xavier
Author: Xavier Fernández i Marín [aut, cre] (<https://orcid.org/0000-0002-9522-8870>)
Maintainer: Xavier Fernández i Marín <xavier.fim@gmail.com>
Repository: CRAN
Date/Publication: 2021-03-01 09:20:12 UTC

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New package mapsf with initial version 0.1.1
Package: mapsf
Title: Thematic Cartography
Version: 0.1.1
Authors@R: c( person("Timothée", "Giraud", email = "timothee.giraud@cnrs.fr", role = c("cre","aut"), comment = c(ORCID = "0000-0002-1932-3323")), person("Diego", "Hernangómez", role = "ctb", comment=c(ORCID="0000-0001-8457-4658")), person("Hugues", "Pecout", role = "ctb"), person("Ian", "Fellows", role = "cph", comment = "No overlap algorithm for labels, from wordcloud package"), person("Jim", "Lemon", role = "cph", comment = "Arc drawing algorithm for annotations, from plotrix package"), person("Florian", "Zenoni", role = "cph", comment = "Orthographic projection visualisation") )
Description: Create and integrate thematic maps in your workflow. This package helps to design various cartographic representations such as proportional symbols, choropleth or typology maps. It also offers several functions to display layout elements that improve the graphic presentation of maps (e.g. scale bar, north arrow, title, labels). 'mapsf' maps 'sf' objects on 'base' graphics.
License: GPL-3
LazyData: true
URL: https://github.com/riatelab/mapsf/, https://riatelab.github.io/mapsf/
BugReports: https://github.com/riatelab/mapsf/issues/
Depends: R (>= 3.5.0), sf
Imports: classInt, graphics, methods, Rcpp, stats, utils, grDevices
Suggests: raster, rgdal, lwgeom, knitr, rmarkdown, tinytest, covr
LinkingTo: Rcpp
Encoding: UTF-8
RoxygenNote: 7.1.1
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: yes
Packaged: 2021-02-25 14:11:00 UTC; tim
Author: Timothée Giraud [cre, aut] (<https://orcid.org/0000-0002-1932-3323>), Diego Hernangómez [ctb] (<https://orcid.org/0000-0001-8457-4658>), Hugues Pecout [ctb], Ian Fellows [cph] (No overlap algorithm for labels, from wordcloud package), Jim Lemon [cph] (Arc drawing algorithm for annotations, from plotrix package), Florian Zenoni [cph] (Orthographic projection visualisation)
Maintainer: Timothée Giraud <timothee.giraud@cnrs.fr>
Repository: CRAN
Date/Publication: 2021-03-01 09:10:02 UTC

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New package KernelICA with initial version 0.1.0
Package: KernelICA
Type: Package
Title: Kernel Independent Component Analysis
Version: 0.1.0
Date: 2021-02-26
Authors@R: c(person( given = "Christoph L.", family = "Koesner", role = c("aut", "cre"), email = "christoph@koesner.at", comment = c(ORCID = "0000-0002-2061-8022")), person( given = "Klaus", family = "Nordhausen", role = "aut", comment = c(ORCID = "0000-0002-3758-8501")))
Maintainer: Christoph L. Koesner <christoph@koesner.at>
Description: The kernel independent component analysis (kernel ICA) method introduced by Bach and Jordan (2003) <doi:10.1162/153244303768966085>. The incomplete Cholesky decomposition used in kernel ICA is provided as separate function.
License: GPL (>= 2)
Imports: inline, methods, ManifoldOptim, JADE, ICtest
Depends: Rcpp
LinkingTo: Rcpp, RcppArmadillo, ManifoldOptim, RcppEigen
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2021-02-26 22:56:51 UTC; christoph
Author: Christoph L. Koesner [aut, cre] (<https://orcid.org/0000-0002-2061-8022>), Klaus Nordhausen [aut] (<https://orcid.org/0000-0002-3758-8501>)
Repository: CRAN
Date/Publication: 2021-03-01 09:50:02 UTC

More information about KernelICA at CRAN
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New package itraxR with initial version 1.1
Package: itraxR
Type: Package
Title: Itrax Data Analysis Tools
Version: 1.1
Author: Thomas Bishop
Maintainer: Thomas Bishop <tombishopemail@gmail.com>
URL: https://thomasbishop.uk
BugReports: https://github.com/tombishop1/itraxR/issues
Description: Parse, trim, join, visualise and analyse data from Itrax sediment core multi-parameter scanners manufactured by Cox Analytical Systems, Sweden. Functions are provided for parsing XRF-peak area files, line-scan optical images, and radiographic images, alongside accompanying metadata. A variety of data wrangling tasks like trimming, joining and reducing XRF-peak area data are simplified. Principle component analysis (PCA), cluster analysis and associated multivariate methods are implemented with appropriate data transformation.
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.1.1
LazyData: true
Depends: dplyr, ggplot2, ggfortify, grid, R (>= 3.5.0)
Imports: readr, chemometrics, tiff, janitor, ggcorrplot, rlang, compositions, tidyr, broom
NeedsCompilation: no
Packaged: 2021-02-25 15:58:48 UTC; tombi
Repository: CRAN
Date/Publication: 2021-03-01 09:20:02 UTC

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New package ggside with initial version 0.0.1.3
Package: ggside
Type: Package
Title: Side Grammar Graphics
Version: 0.0.1.3
Authors@R: person(given = "Justin", family = "Landis", role = c("aut", "cre"), email = "jtlandis314@gmail.com")
Maintainer: Justin Landis <jtlandis314@gmail.com>
Description: The grammar of graphics as shown in 'ggplot2' has provided an expressive API for users to build plots. 'ggside' extends 'ggplot2' by allowing users to add graphical information about one of the main panel's axis using a familiar 'ggplot2' style API with tidy data. This package is particularly useful for visualising metadata on a discrete axis, or summary graphics on a continuous axis such as a boxplot or a density distribution.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
VignetteBuilder: knitr
Depends: ggplot2 (>= 3.0.0)
Imports: grid, gtable, rlang, scales, utils, glue, stats
Suggests: tidyr, dplyr, testthat, knitr, rmarkdown, vdiffr, ggdendro, viridis
NeedsCompilation: no
Packaged: 2021-02-25 14:50:26 UTC; jtlandis
Author: Justin Landis [aut, cre]
Repository: CRAN
Date/Publication: 2021-03-01 09:10:06 UTC

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New package FORTLS with initial version 1.0.0
Package: FORTLS
Title: Automatic Processing of TLS Point Cloud Data for Forestry Purposes
Version: 1.0.0
Date: 2021-02-13
Authors@R: c( person("Juan Alberto", "Molina-Valero", role = c("aut", "cph", "cre"), email = "juanalberto.molina.valero@usc.es"), person("María José", "Ginzo Villamayor", role = c("aut", "com")), person("Manuel Antonio", "Novo Pérez", role = c("aut", "com")), person("Adela", "Martínez-Calvo", role = c("aut", "com")), person("Juan Gabriel", "Álvarez-González", role = c("aut", "ths")), person("Fernando", "Montes", role = "aut"), person("César", "Pérez-Cruzado", role = c("aut", "ths")))
Author: Juan Alberto Molina-Valero [aut, cph, cre], María José Ginzo Villamayor [aut, com], Manuel Antonio Novo Pérez [aut, com], Adela Martínez-Calvo [aut, com], Juan Gabriel Álvarez-González [aut, ths], Fernando Montes [aut], César Pérez-Cruzado [aut, ths]
Maintainer: Juan Alberto Molina-Valero <juanalberto.molina.valero@usc.es>
Description: Process automation of Terrestrial Laser Scanner (TLS) point cloud data derived from single scans. 'FORTLS' enables (i) detection of trees and estimation of diameter at breast height (dbh), (ii) estimation of some stand variables (e.g. density, basal area, mean and dominant height), (iii) computation of metrics related to important forest attributes estimated in Forest Inventories (FIs) at stand level and (iv) optimization of plot design for combining TLS data and field measured data. Documentation about 'FORTLS' is described in Molina-Valero et al. (2020, <doi:10.3390/IECF2020-08066>).
URL: https://github.com/Molina-Valero/FORTLS
BugReports: https://github.com/Molina-Valero/FORTLS/issues
License: GPL-3
Depends: R (>= 3.5.0)
Imports: dbscan, Distance, ggvoronoi, htmlwidgets, lidR, plotly, progress, Rcpp(>= 1.0.5), raster, scales, sp, tidyr, vroom
Suggests: testthat
LinkingTo: Rcpp, RcppEigen
Encoding: UTF-8
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2021-02-26 16:01:11 UTC; Usuario
Repository: CRAN
Date/Publication: 2021-03-01 09:40:08 UTC

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New package dipm with initial version 1.0
Package: dipm
Title: Depth Importance in Precision Medicine (DIPM) Method
Version: 1.0
Date: 2021-02-24
Authors@R: c(person(given = "Cai", family = "Li", role = c("aut", "cre"), email = "cai.li@yale.edu"), person(given = "Victoria", family = "Chen", role = "aut", email = "victoria.chen@yale.edu"), person(given = "Heping", family = "Zhang", role = "aut", email = "heping.zhang@yale.edu"))
Maintainer: Cai Li <cai.li@yale.edu>
Description: An implementation of the Depth Importance in Precision Medicine (DIPM) method in Chen and Zhang (2020) <doi:10.1093/biostatistics/kxaa021> and Chen and Zhang (2020) <doi:10.1007/978-3-030-46161-4_16>. The DIPM method is a classification tree that searches for subgroups with especially poor or strong performance in a given treatment group.
Depends: R (>= 3.0.0)
Imports: stats, utils, survival, partykit (>= 1.2-6), ggplot2, grid
NeedsCompilation: yes
License: GPL (>= 2)
Encoding: UTF-8
LazyLoad: yes
LazyData: true
Repository: CRAN
RoxygenNote: 7.1.1
Packaged: 2021-02-26 20:42:27 UTC; cli9
Author: Cai Li [aut, cre], Victoria Chen [aut], Heping Zhang [aut]
Date/Publication: 2021-03-01 09:40:05 UTC

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New package data.validator with initial version 0.1.4
Package: data.validator
Type: Package
Title: Automatic Data Validation and Reporting
Version: 0.1.4
Authors@R: c(person("Krystian", "Igras", email = "krystian@appsilon.com", role = c("aut")), person("Marcin", "Dubel", email = "marcin@appsilon.com", role = c("aut")), person("Paweł", "Przytuła", email = "pawel@appsilon.com", role = c("aut")), person("Dominik", "Krzeminski", email = "dominik@appsilon.com", role = c("ctb", "cre")), person(family = "Appsilon Sp. z o.o.", role = c("cph")))
Description: Validate dataset by columns and rows using convenient predicates inspired by 'assertr' package. Generate good looking HTML report or print console output to display in logs of your data processing pipeline.
BugReports: https://github.com/Appsilon/data.validator/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: TRUE
RoxygenNote: 7.1.1
Imports: shiny, assertr (>= 2.8), shiny.semantic (>= 0.3.3), knitr, purrr, dplyr, tidyr, utils, R6, rlang, rmarkdown, htmltools, htmlwidgets, tibble
Suggests: testthat, covr
Collate: 'results_parsers.R' 'semantic_report_constructors.R' 'utils.R' 'report.R' 'assertions.R'
NeedsCompilation: no
Packaged: 2021-02-26 10:22:19 UTC; dominik
Author: Krystian Igras [aut], Marcin Dubel [aut], Paweł Przytuła [aut], Dominik Krzeminski [ctb, cre], Appsilon Sp. z o.o. [cph]
Maintainer: Dominik Krzeminski <dominik@appsilon.com>
Repository: CRAN
Date/Publication: 2021-03-01 09:20:05 UTC

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New package dadjokeapi with initial version 1.0.2
Package: dadjokeapi
Type: Package
Title: Return a Random Dad Joke
Version: 1.0.2
Authors@R: c(person("Jeffrey", "Hollister", email = "hollister.jeff@epa.gov", role = c("aut", "cre")), person("Antoine Bichat",role = c("ctb")), person("Brett Langdon", role = c("cph")))
URL: https://github.com/jhollist/dadjokeapi/
BugReports: https://github.com/jhollist/dadjokeapi/issues/
Maintainer: Jeffrey Hollister <hollister.jeff@epa.gov>
Description: What is funnier than a dad joke? A dad joke in R! This package utilizes the API for <https://icanhazdadjoke.com> and returns dad jokes from several API endpoints.
License: MIT + file LICENSE
Depends: R (>= 3.5.0)
Imports: httr, beepr, curl, dplyr, png
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat, mockery
NeedsCompilation: no
Packaged: 2021-02-25 18:28:38 UTC; JHollist
Author: Jeffrey Hollister [aut, cre], Antoine Bichat [ctb], Brett Langdon [cph]
Repository: CRAN
Date/Publication: 2021-03-01 09:20:09 UTC

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New package bgumbel with initial version 0.0.1
Package: bgumbel
Title: Bimodal Gumbel Distribution
Version: 0.0.1
Authors@R: c(person(given = "Pedro", family = "C. Brom", role = c("aut", "cre", "cph"), email = "pcbrom@gmail.com", comment = c(ORCID = "https://orcid.org/0000-0002-1288-7695", Lattes = "http://lattes.cnpq.br/0154064396756002")), person(given = "Cira", family = "E. G. Otiniano", role = c("aut", "cph"), email = "ciragotiniano@gmail.com", comment = c(ORCID = "https://orcid.org/0000-0002-5619-0478")), person(given = "Roberto", family = "Vila", role = c("aut", "cph"), email = "rovig161@gmail.com", comment = c(ORCID = "https://orcid.org/0000-0003-1073-0114")), person(given = "Marcelo", family = "B. Pereira", role = c("aut", "cph"), email = "m.p.bourguignon@gmail.com", comment = c(ORCID = "https://orcid.org/0000-0002-1182-5193")))
Description: Bimodal Gumbel distribution. General functions for performing extreme value analysis.
Imports: MCMCpack, coda, MASS
License: MIT + file LICENSE
Language: en-US
Encoding: UTF-8
LazyData: true
Date: 2021-02-17
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-26 13:56:09 UTC; pcbrom
Author: Pedro C. Brom [aut, cre, cph] (<https://orcid.org/0000-0002-1288-7695>, http://lattes.cnpq.br/0154064396756002), Cira E. G. Otiniano [aut, cph] (<https://orcid.org/0000-0002-5619-0478>), Roberto Vila [aut, cph] (<https://orcid.org/0000-0003-1073-0114>), Marcelo B. Pereira [aut, cph] (<https://orcid.org/0000-0002-1182-5193>)
Maintainer: Pedro C. Brom <pcbrom@gmail.com>
Repository: CRAN
Date/Publication: 2021-03-01 09:30:02 UTC

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New package adobeanalyticsr with initial version 0.1.5
Package: adobeanalyticsr
Type: Package
Version: 0.1.5
Title: R Client for 'Adobe Analytics' API 2.0
Description: Connect to the 'Adobe Analytics' API v2.0 <https://github.com/AdobeDocs/analytics-2.0-apis> which powers 'Analysis Workspace'. The package was developed with the analyst in mind, and it will continue to be developed with the guiding principles of iterative, repeatable, timely analysis.
Authors@R: c( person("Ben", "Woodard", email = "benrwoodard@gmail.com", role = c("aut", "cre")), person("Tim", "Wilson", email = "timwilson7@gmail.com", role = c("aut", "ctb")), person("Mark", "Edmondson", role = "ctb") )
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.2.0)
Imports: assertthat (>= 0.2.0), jsonlite (>= 1.5), dplyr (>= 0.8.1), stringr (>= 1.4.0), purrrlyr (>= 0.0.6), purrr (>= 0.3.3), httr (>= 1.3.1), tidyr (>= 1.0.0), rlang (>= 0.4.8), lubridate (>= 1.7.9), ggplot2 (>= 3.3.2), scales (>= 1.1.1), lifecycle, glue, tibble, knitr
RoxygenNote: 7.1.1
Suggests: testthat, rmarkdown
RdMacros: lifecycle
VignetteBuilder: knitr
BugReports: https://github.com/benrwoodard/adobeanalyticsr/issues
URL: https://github.com/benrwoodard/adobeanalyticsr
NeedsCompilation: no
Packaged: 2021-02-26 02:28:56 UTC; ben.woodard
Author: Ben Woodard [aut, cre], Tim Wilson [aut, ctb], Mark Edmondson [ctb]
Maintainer: Ben Woodard <benrwoodard@gmail.com>
Repository: CRAN
Date/Publication: 2021-03-01 09:10:10 UTC

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New package postGGIR with initial version 1.0.0
Package: postGGIR
Version: 1.0.0
Title: Data Processing after Running 'GGIR' for Accelerometer Data
Description: Generate all necessary R/Rmd/shell files for data processing after running 'GGIR' (v2.0) for accelerometer data. In part 1, all csv files in the GGIR output directory were read, transformed and then merged. In part 2, the GGIR output files were checked and summarized in one excel sheet. In part 3, the merged data was cleaned according to the number of valid hours on each night and the number of valid days for each subject. In part 4, the cleaned activity data was imputed by the average Euclidean norm minus one (ENMO) over all the valid days for each subject. Finally, a comprehensive report of data processing was created using Rmarkdown, and the report includes few exploratory plots and multiple commonly used features extracted from minute level actigraphy data.
Authors@R: c( person(given = "Wei", family = "Guo", role = c("aut", "cre"), email = "wei.guo3@nih.gov"), person(given = "Vadim", family = "Zipunnikov", role = c("aut"), email = "vzipunni@jhsph.edu"), person(given = "Kathleen", family = "Merikangas", role = c("aut"), email = "merikank@mail.nih.gov") )
Maintainer: Wei Guo <wei.guo3@nih.gov>
License: GPL-3
Imports: refund, denseFLMM, dplyr, xlsx, survival, stats, tidyr, zoo, ineq, cosinor, abind, accelerometry, minpack.lm, kableExtra, GGIR
Depends: R (>= 3.6.0)
Suggests: knitr, rmarkdown
Encoding: UTF-8
LazyData: TRUE
ByteCompile: true
Type: Package
VignetteBuilder: knitr
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-23 15:44:04 UTC; guow4
Author: Wei Guo [aut, cre], Vadim Zipunnikov [aut], Kathleen Merikangas [aut]
Repository: CRAN
Date/Publication: 2021-03-01 09:00:02 UTC

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New package mlrintermbo with initial version 0.5.0
Package: mlrintermbo
Title: Model-Based Optimization for 'mlr3' Through 'mlrMBO'
Description: The 'mlrMBO' package can ordinarily not be used for optimization within 'mlr3', because of incompatibilities of their respective class systems. 'mlrintermbo' offers a compatibility interface that provides 'mlrMBO' as an 'mlr3tuning' 'Tuner' object, for tuning of machine learning algorithms within 'mlr3', as well as a 'bbotk' 'Optimizer' object for optimization of general objective functions using the 'bbotk' black box optimization framework. The control parameters of 'mlrMBO' are faithfully reproduced as a 'paradox' 'ParamSet'.
Authors@R: c( person("Martin", "Binder", email = "developer.mb706@doublecaret.com", role = c("aut", "cre")))
URL: https://github.com/mb706/mlrintermbo
BugReports: https://github.com/mb706/mlrintermbo/issues
License: LGPL-3
Encoding: UTF-8
Imports: backports, checkmate, data.table, mlr3misc (>= 0.1.4), paradox, R6, lhs, callr, bbotk, mlr3tuning
Suggests: mlr, ParamHelpers, testthat, rgenoud, DiceKriging, emoa, cmaesr, randomForest, smoof, lgr, mlr3, mlr3learners, mlr3pipelines, mlrMBO, ranger, rpart
LazyData: yes
ByteCompile: yes
Version: 0.5.0
RoxygenNote: 7.1.1
Collate: 'utils.R' 'CapsuledMlr3Learner.R' 'ParamHelpersParamSet.R' 'optimize.R' 'paramset.R' 'TunerInterMBO.R' 'surrogates.R' 'zzz.R'
NeedsCompilation: no
Packaged: 2021-02-24 23:08:46 UTC; user
Author: Martin Binder [aut, cre]
Maintainer: Martin Binder <developer.mb706@doublecaret.com>
Repository: CRAN
Date/Publication: 2021-03-01 09:00:06 UTC

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New package MARVEL with initial version 1.0.0
Package: MARVEL
Title: Revealing Splicing Dynamics at Single-Cell Resolution
Version: 1.0.0
Description: Alternative splicing represents an additional and underappreciated layer of complexity underlying gene expression profiles. Nevertheless, there remains hitherto a paucity of softwares to investigate splicing dynamics at single-cell resolution. 'MARVEL' quantifies percent spliced-in (PSI) values for the five primary exon-level splicing events, namely skipped-exon (SE), mutually exclusive exons (MXE), retained intron (RI), alternative 5' and 3' splice sites (A5SS and A3SS, respectively). Additionally, 'MARVEL' performs differential splicing analysis to identify splicing events whose PSI distribution differ between groups of cells. Finally, 'MARVEL' models the PSI distribution for each event as a beta distribution and categorises each distribution into modalities (inspired by Song (2017) <doi:10.1016/j.molcel.2017.06.003>).
Imports: AnnotationDbi (>= 1.48.0), dplyr (>= 1.0.1), FactoMineR (>= 2.3), factoextra (>= 1.0.7), fitdistrplus (>= 1.1-1), ggplot2 (>= 3.3.2), GO.db (>= 3.10.0), GOstats (>= 2.52.0), methods, plyr (>= 1.8.4), kableExtra (>= 1.3.1), org.Hs.eg.db (>= 3.10.0), parallel, stringr (>= 1.4.0)
Encoding: UTF-8
Author: Sean Wen
Maintainer: Sean Wen <sean.wenwx@gmail.com>
License: GPL-3
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
ByteCompile: true
NeedsCompilation: no
Packaged: 2021-02-25 08:27:19 UTC; seanwen
Repository: CRAN
Date/Publication: 2021-03-01 09:00:09 UTC

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New package GPIC with initial version 0.1.0
Package: GPIC
Type: Package
Title: Quantifying Group Performance in Individual Competitions
Version: 0.1.0
Authors@R: person("Duy Nghia", "Pham", email = "nghiapham@yandex.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-1349-1710"))
Description: Compute the GPIC index as described in Pham (2020) <doi:10.35542/osf.io/ajz5v>.
Depends: R (>= 4.0.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-25 10:00:52 UTC; nghia
Author: Duy Nghia Pham [aut, cre] (<https://orcid.org/0000-0003-1349-1710>)
Maintainer: Duy Nghia Pham <nghiapham@yandex.com>
Repository: CRAN
Date/Publication: 2021-03-01 09:00:13 UTC

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Package someMTP updated to version 1.4.1.1 with previous version 1.4.1 dated 2013-11-04

Title: Some Multiple Testing Procedures
Description: It's a collection of functions for Multiplicity Correction and Multiple Testing.
Author: livio finos
Maintainer: livio finos <livio@stat.unipd.it>

Diff between someMTP versions 1.4.1 dated 2013-11-04 and 1.4.1.1 dated 2021-03-01

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Package genetics updated to version 1.3.8.1.3 with previous version 1.3.8.1.2 dated 2019-04-22

Title: Population Genetics
Description: Classes and methods for handling genetic data. Includes classes to represent genotypes and haplotypes at single markers up to multiple markers on multiple chromosomes. Function include allele frequencies, flagging homo/heterozygotes, flagging carriers of certain alleles, estimating and testing for Hardy-Weinberg disequilibrium, estimating and testing for linkage disequilibrium, ...
Author: Gregory Warnes, with contributions from Gregor Gorjanc, Friedrich Leisch, and Michael Man.
Maintainer: Gregory Warnes <greg@warnes.net>

Diff between genetics versions 1.3.8.1.2 dated 2019-04-22 and 1.3.8.1.3 dated 2021-03-01

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Package CCA updated to version 1.2.1 with previous version 1.2 dated 2009-03-11

Title: Canonical Correlation Analysis
Description: Provides a set of functions that extend the 'cancor' function with new numerical and graphical outputs. It also include a regularized extension of the canonical correlation analysis to deal with datasets with more variables than observations.
Author: Ignacio Gonz<e1>lez, S<e9>bastien D<e9>jean
Maintainer: S<e9>bastien D<e9>jean <sebastien.dejean@math.univ-toulouse.fr>

Diff between CCA versions 1.2 dated 2009-03-11 and 1.2.1 dated 2021-03-01

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Package BigQuic updated to version 1.1-9.1 with previous version 1.1-9 dated 2020-05-15

Title: Big Quadratic Inverse Covariance Estimation
Description: Use Newton's method, coordinate descent, and METIS clustering to solve the L1 regularized Gaussian MLE inverse covariance matrix estimation problem.
Author: Khalid B. Kunji [aut, cre], Cho-Jui Hsieh [ctb], Matyas A. Sustik [ctb], Inderjit S. Dhillon [ctb], Pradeep Ravikumar [ctb], Tuo Zhao [ctb], Xingguo Li [ctb], Han Liu [ctb], Kathryn Roeder [ctb], John Lafferty [ctb], Larry Wasserman [ctb], George Karypis [ctb], Melissa O'Neill [ctb], Richard Henderson [ctb]
Maintainer: Khalid B. Kunji <kkunji@hbku.edu.qa>

Diff between BigQuic versions 1.1-9 dated 2020-05-15 and 1.1-9.1 dated 2021-03-01

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Package powerSurvEpi updated to version 0.1.3 with previous version 0.1.1 dated 2021-01-08

Title: Power and Sample Size Calculation for Survival Analysis of Epidemiological Studies
Description: Functions to calculate power and sample size for testing main effect or interaction effect in the survival analysis of epidemiological studies (non-randomized studies), taking into account the correlation between the covariate of the interest and other covariates. Some calculations also take into account the competing risks and stratified analysis. This package also includes a set of functions to calculate power and sample size for testing main effect in the survival analysis of randomized clinical trials and conditional logistic regression for nested case-control study.
Author: Weiliang Qiu, Jorge Chavarro, Ross Lazarus, Bernard Rosner, Jing Ma.
Maintainer: Weiliang Qiu <weiliang.qiu@gmail.com>

Diff between powerSurvEpi versions 0.1.1 dated 2021-01-08 and 0.1.3 dated 2021-03-01

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Package nptest updated to version 1.0-3 with previous version 1.0-2 dated 2020-10-01

Title: Nonparametric Bootstrap and Permutation Tests
Description: Robust nonparametric bootstrap and permutation tests for location, correlation, and regression problems, as described in Helwig (2019a) <doi:10.1002/wics.1457> and Helwig (2019b) <doi:10.1016/j.neuroimage.2019.116030>. Univariate and multivariate tests are supported. For each problem, exact tests and Monte Carlo approximations are available. Five different nonparametric bootstrap confidence intervals are implemented. Parallel computing is implemented via the 'parallel' package.
Author: Nathaniel E. Helwig <helwig@umn.edu>
Maintainer: Nathaniel E. Helwig <helwig@umn.edu>

Diff between nptest versions 1.0-2 dated 2020-10-01 and 1.0-3 dated 2021-03-01

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Package IndependenceTests (with last version 0.5) was removed from CRAN

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

2020-12-18 0.5

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Package MASSExtra updated to version 1.1.1 with previous version 1.0.2 dated 2020-12-11

Title: Some 'MASS' Enhancements
Description: Some enhancements, extensions and additions to the facilities of the recommended 'MASS' package that are useful mainly for teaching purposes, with more convenient default settings and user interfaces. Key functions from 'MASS' are imported and re-exported to avoid masking conflicts. In addition we provide some additional functions mainly used to illustrate coding paradigms and techniques, such as Gramm-Schmidt orthogonalisation and generalised eigenvalue problems.
Author: Bill Venables
Maintainer: Bill Venables <bill.venables@gmail.com>

Diff between MASSExtra versions 1.0.2 dated 2020-12-11 and 1.1.1 dated 2021-03-01

 MASSExtra-1.0.2/MASSExtra/inst/doc/rationale.pdf  |only
 MASSExtra-1.1.1/MASSExtra/DESCRIPTION             |   10 +-
 MASSExtra-1.1.1/MASSExtra/MD5                     |   17 ++--
 MASSExtra-1.1.1/MASSExtra/NAMESPACE               |    9 ++
 MASSExtra-1.1.1/MASSExtra/R/kde_2d_mass.R         |only
 MASSExtra-1.1.1/MASSExtra/build/vignette.rds      |binary
 MASSExtra-1.1.1/MASSExtra/inst/doc/rationale.R    |   25 +++++--
 MASSExtra-1.1.1/MASSExtra/inst/doc/rationale.Rmd  |   76 +++++++++++++++++++---
 MASSExtra-1.1.1/MASSExtra/inst/doc/rationale.html |only
 MASSExtra-1.1.1/MASSExtra/man/kde_1d.Rd           |only
 MASSExtra-1.1.1/MASSExtra/man/kde_2d.Rd           |only
 MASSExtra-1.1.1/MASSExtra/vignettes/rationale.Rmd |   76 +++++++++++++++++++---
 12 files changed, 180 insertions(+), 33 deletions(-)

More information about MASSExtra at CRAN
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