Sun, 16 Apr 2023

Package xts updated to version 0.13.1 with previous version 0.13.0 dated 2023-02-20

Title: eXtensible Time Series
Description: Provide for uniform handling of R's different time-based data classes by extending zoo, maximizing native format information preservation and allowing for user level customization and extension, while simplifying cross-class interoperability.
Author: Jeffrey A. Ryan [aut, cph], Joshua M. Ulrich [cre, aut], Ross Bennett [ctb], Corwin Joy [ctb]
Maintainer: Joshua M. Ulrich <josh.m.ulrich@gmail.com>

Diff between xts versions 0.13.0 dated 2023-02-20 and 0.13.1 dated 2023-04-16

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 xts-0.13.1/xts/R/tzone.R                                |   29 ++-
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 xts-0.13.1/xts/R/xts.methods.R                          |    4 
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Permanent link

Package eseis updated to version 0.7.2 with previous version 0.6.0 dated 2021-11-26

Title: Environmental Seismology Toolbox
Description: Environmental seismology is a scientific field that studies the seismic signals, emitted by Earth surface processes. This package provides all relevant functions to read/write seismic data files, prepare, analyse and visualise seismic data, and generate reports of the processing history.
Author: Michael Dietze [cre, aut, trl], Christoph Burow [ctb], Sophie Lagarde [ctb, trl]
Maintainer: Michael Dietze <michael.dietze@uni-goettingen.de>

Diff between eseis versions 0.6.0 dated 2021-11-26 and 0.7.2 dated 2023-04-16

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Package mzipmed updated to version 1.3.0 with previous version 1.2.5 dated 2023-03-21

Title: Mediation using MZIP Model
Description: We implement functions allowing for mediation analysis to be performed in cases where the mediator is a count variable with excess zeroes. First a function is provided allowing users to perform analysis for zero-inflated count variables using the marginalized zero-inflated Poisson (MZIP) model (Long et al. 2014 <DOI:10.1002/sim.6293>). Using the counterfactual approach to mediation and MZIP we can obtain natural direct and indirect effects for the overall population. Using delta method processes variance estimation can be performed instantaneously. Alternatively, bootstrap standard errors can be used. We also provide functions for cases with exposure-mediator interactions with four-way decomposition of total effect.
Author: Andrew Sims [aut, cre] , Dustin Long [aut], Hemant Tiwari [aut], Leann Long [aut]
Maintainer: Andrew Sims <ams329@uab.edu>

Diff between mzipmed versions 1.2.5 dated 2023-03-21 and 1.3.0 dated 2023-04-16

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Package MetricsWeighted updated to version 1.0.0 with previous version 0.5.5 dated 2023-03-24

Title: Weighted Metrics and Performance Measures for Machine Learning
Description: Provides weighted versions of several metrics and performance measures used in machine learning, including average unit deviances of the Bernoulli, Tweedie, Poisson, and Gamma distributions, see Jorgensen B. (1997, ISBN: 978-0412997112). The package also contains a weighted version of generalized R-squared, see e.g. Cohen, J. et al. (2002, ISBN: 978-0805822236). Furthermore, 'dplyr' chains are supported.
Author: Michael Mayer [aut, cre], Christian Lorentzen [ctb]
Maintainer: Michael Mayer <mayermichael79@gmail.com>

Diff between MetricsWeighted versions 0.5.5 dated 2023-03-24 and 1.0.0 dated 2023-04-16

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Permanent link

Package lactater updated to version 0.1.4 with previous version 0.1.2 dated 2023-02-22

Title: Tools for Analyzing Lactate Thresholds
Description: Set of tools for analyzing lactate thresholds from a step incremental test to exhaustion. Easily analyze the methods Log-log, Onset of Blood Lactate Accumulation (OBLA), Baseline plus (Bsln+), Dmax, Lactate Turning Point (LTP), and Lactate / Intensity ratio (LTratio) in cycling, running, or swimming. Beaver WL, Wasserman K, Whipp BJ (1985) <doi:10.1152/jappl.1985.59.6.1936>. Heck H, Mader A, Hess G, Mücke S, Müller R, Hollmann W (1985) <doi:10.1055/s-2008-1025824>. Kindermann W, Simon G, Keul J (1979) <doi:10.1007/BF00421101>. Skinner JS, Mclellan TH (1980) <doi:10.1080/02701367.1980.10609285>. Berg A, Jakob E, Lehmann M, Dickhuth HH, Huber G, Keul J (1990) <PMID:2408033>. Zoladz JA, Rademaker AC, Sargeant AJ (1995) <doi:10.1113/jphysiol.1995.sp020959>. Cheng B, Kuipers H, Snyder A, Keizer H, Jeukendrup A, Hesselink M (1992) <doi:10.1055/s-2007-1021309>. Bishop D, Jenkins DG, Mackinnon LT (1998) <doi:10.1097/00005768-199808000-00014>. Hug [...truncated...]
Author: Felipe Mattioni Maturana [aut, cre]
Maintainer: Felipe Mattioni Maturana <felipe.mattioni@med.uni-tuebingen.de>

Diff between lactater versions 0.1.2 dated 2023-02-22 and 0.1.4 dated 2023-04-16

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Package gamlr updated to version 1.13-8 with previous version 1.13-7 dated 2021-05-07

Title: Gamma Lasso Regression
Description: The gamma lasso algorithm provides regularization paths corresponding to a range of non-convex cost functions between L0 and L1 norms. As much as possible, usage for this package is analogous to that for the glmnet package (which does the same thing for penalization between L1 and L2 norms). For details see: Taddy (2017 JCGS), 'One-Step Estimator Paths for Concave Regularization', <arXiv:1308.5623>.
Author: Matt Taddy <mataddy@gmail.com>
Maintainer: Matt Taddy <mataddy@gmail.com>

Diff between gamlr versions 1.13-7 dated 2021-05-07 and 1.13-8 dated 2023-04-16

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More information about gamlr at CRAN
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Package vcdExtra updated to version 0.8-4 with previous version 0.8-3 dated 2023-03-04

Title: 'vcd' Extensions and Additions
Description: Provides additional data sets, methods and documentation to complement the 'vcd' package for Visualizing Categorical Data and the 'gnm' package for Generalized Nonlinear Models. In particular, 'vcdExtra' extends mosaic, assoc and sieve plots from 'vcd' to handle 'glm()' and 'gnm()' models and adds a 3D version in 'mosaic3d'. Additionally, methods are provided for comparing and visualizing lists of 'glm' and 'loglm' objects. This package is now a support package for the book, "Discrete Data Analysis with R" by Michael Friendly and David Meyer.
Author: Michael Friendly [aut, cre] , Heather Turner [ctb], David Meyer [ctb], Achim Zeileis [ctb] , Duncan Murdoch [ctb], David Firth [ctb], Matt Kumar [ctb], Shuguang Sun [ctb]
Maintainer: Michael Friendly <friendly@yorku.ca>

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New package robustfa with initial version 1.1-0
Package: robustfa
Title: Object Oriented Solution for Robust Factor Analysis
Version: 1.1-0
Date: 2023-03-21
Author: Frederic Bertrand [cre] , Ying-Ying Zhang [aut]
Maintainer: Frederic Bertrand <frederic.bertrand@utt.fr>
Description: Outliers virtually exist in any datasets of any application field. To avoid the impact of outliers, we need to use robust estimators. Classical estimators of multivariate mean and covariance matrix are the sample mean and the sample covariance matrix. Outliers will affect the sample mean and the sample covariance matrix, and thus they will affect the classical factor analysis which depends on the classical estimators (Pison, G., Rousseeuw, P.J., Filzmoser, P. and Croux, C. (2003) <doi:10.1016/S0047-259X(02)00007-6>). So it is necessary to use the robust estimators of the sample mean and the sample covariance matrix. There are several robust estimators in the literature: Minimum Covariance Determinant estimator, Orthogonalized Gnanadesikan-Kettenring, Minimum Volume Ellipsoid, M, S, and Stahel-Donoho. The most direct way to make multivariate analysis more robust is to replace the sample mean and the sample covariance matrix of the classical estimators to robust estimators (Maronna [...truncated...]
License: GPL (>= 2)
Depends: rrcov, R (>= 2.15.0)
Imports: methods, stats4, stats
Suggests: grid, lattice, cluster, mclust, MASS, ellipse, knitr, rmarkdown
LazyLoad: yes
LazyData: yes
Encoding: UTF-8
VignetteBuilder: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2023-04-16 08:04:40 UTC; fbertran
Repository: CRAN
Date/Publication: 2023-04-16 14:40:02 UTC

More information about robustfa at CRAN
Permanent link

Package geomander updated to version 2.2.1 with previous version 2.1.0 dated 2022-06-23

Title: Geographic Tools for Studying Gerrymandering
Description: A compilation of tools to complete common tasks for studying gerrymandering. This focuses on the geographic tool side of common problems, such as linking different levels of spatial units or estimating how to break up units. Functions exist for creating redistricting-focused data for the US.
Author: Christopher T. Kenny [aut, cre]
Maintainer: Christopher T. Kenny <christopherkenny@fas.harvard.edu>

Diff between geomander versions 2.1.0 dated 2022-06-23 and 2.2.1 dated 2023-04-16

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Package geofi updated to version 1.0.9 with previous version 1.0.8 dated 2023-02-16

Title: Access Finnish Geospatial Data
Description: Tools for reading Finnish open geospatial data in R.
Author: Markus Kainu [aut, cre] , Joona Lehtomaki [aut] , Juuso Parkkinen [ctb] , Jani Miettinen [ctb], Pyry Kantanen [ctb], Sampo Vesanen [ctb], Leo Lahti [aut]
Maintainer: Markus Kainu <markus.kainu@kapsi.fi>

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Permanent link

Package innsight updated to version 0.2.0 with previous version 0.1.1 dated 2022-08-29

Title: Get the Insights of your Neural Network
Description: Interpretability methods to analyze the behavior and individual predictions of modern neural networks. Implemented methods are: 'Connection Weights' described by Olden et al. (2004) <doi:10.1016/j.ecolmodel.2004.03.013>, Layer-wise Relevance Propagation ('LRP') described by Bach et al. (2015) <doi:10.1371/journal.pone.0130140>, Deep Learning Important Features ('DeepLIFT') described by Shrikumar et al. (2017) <arXiv:1704.02685> and gradient-based methods like 'SmoothGrad' described by Smilkov et al. (2017) <arXiv:1706.03825>, 'Gradient x Input' described by Baehrens et al. (2009) <arXiv:0912.1128> or 'Vanilla Gradient'.
Author: Niklas Koenen [aut, cre] , Raphael Baudeu [ctb]
Maintainer: Niklas Koenen <niklas.koenen@gmail.com>

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Package nestedcv updated to version 0.6.1 with previous version 0.4.4 dated 2022-12-05

Title: Nested Cross-Validation with 'glmnet' and 'caret'
Description: Implements nested k*l-fold cross-validation for lasso and elastic-net regularised linear models via the 'glmnet' package and other machine learning models via the 'caret' package. Cross-validation of 'glmnet' alpha mixing parameter and embedded fast filter functions for feature selection are provided. Described as double cross-validation by Stone (1977) <doi:10.1111/j.2517-6161.1977.tb01603.x>. Also implemented is a method using outer CV to measure unbiased model performance metrics when fitting Bayesian linear and logistic regression shrinkage models using the horseshoe prior over parameters to encourage a sparse model as described by Piironen & Vehtari (2017) <doi:10.1214/17-EJS1337SI>.
Author: Myles Lewis [aut, cre] , Athina Spiliopoulou [aut] , Katriona Goldmann [aut]
Maintainer: Myles Lewis <myles.lewis@qmul.ac.uk>

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Package canadacovid (with last version 0.3.4) was removed from CRAN

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

2022-08-22 0.3.4
2022-02-07 0.3.3
2022-01-17 0.3.1

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Package USgas updated to version 0.1.2 with previous version 0.1.1 dated 2021-05-26

Title: The Demand for Natural Gas in the US
Description: Provides an overview of the demand for natural gas in the US by state and country level. Data source: US Energy Information Administration <https://www.eia.gov/>.
Author: Rami Krispin [aut, cre]
Maintainer: Rami Krispin <rami.krispin@gmail.com>

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Package TSSS updated to version 1.3.4-2 with previous version 1.3.4 dated 2023-03-24

Title: Time Series Analysis with State Space Model
Description: Functions for statistical analysis, modeling and simulation of time series with state space model, based on the methodology in Kitagawa (2020, ISBN: 978-0-367-18733-0).
Author: The Institute of Statistical Mathematics, based on the program by Genshiro Kitagawa
Maintainer: Masami Saga <msaga@mtb.biglobe.ne.jp>

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Package SynthETIC updated to version 1.0.4 with previous version 1.0.2 dated 2021-09-02

Title: Synthetic Experience Tracking Insurance Claims
Description: Creation of an individual claims simulator which generates various features of non-life insurance claims. An initial set of test parameters, designed to mirror the experience of an Auto Liability portfolio, were set up and applied by default to generate a realistic test data set of individual claims (see vignette). The simulated data set then allows practitioners to back-test the validity of various reserving models and to prove and/or disprove certain actuarial assumptions made in claims modelling. The distributional assumptions used to generate this data set can be easily modified by users to match their experiences. Reference: Avanzi B, Taylor G, Wang M, Wong B (2020) "SynthETIC: an individual insurance claim simulator with feature control" <arXiv:2008.05693>.
Author: Benjamin Avanzi [aut], Greg Taylor [aut], Melantha Wang [aut, cre], Bernard Wong [aut]
Maintainer: Melantha Wang <wang.melantha@gmail.com>

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Package SPLICE updated to version 1.1.1 with previous version 1.1.0 dated 2022-03-05

Title: Synthetic Paid Loss and Incurred Cost Experience (SPLICE) Simulator
Description: An extension to the individual claim simulator called 'SynthETIC' (on CRAN), to simulate the evolution of case estimates of incurred losses through the lifetime of an insurance claim. The transactional simulation output now comprises key dates, and both claim payments and revisions of estimated incurred losses. An initial set of test parameters, designed to mirror the experience of a real insurance portfolio, were set up and applied by default to generate a realistic test data set of incurred histories (see vignette). However, the distributional assumptions used to generate this data set can be easily modified by users to match their experiences. Reference: Avanzi B, Taylor G, Wang M (2021) "SPLICE: A Synthetic Paid Loss and Incurred Cost Experience Simulator" <arXiv:2109.04058>.
Author: Benjamin Avanzi [aut], Greg Taylor [aut], Melantha Wang [aut, cre], William Ho [rev]
Maintainer: Melantha Wang <wang.melantha@gmail.com>

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Package EasyDescribe updated to version 0.1.2 with previous version 0.1.1 dated 2022-01-21

Title: A Convenient Way of Descriptive Statistics
Description: Descriptive Statistics is essential for publishing articles. This package can perform descriptive statistics according to different data types. If the data is a continuous variable, the mean and standard deviation or median and quartiles are automatically output; if the data is a categorical variable, the number and percentage are automatically output. In addition, if you enter two variables in this package, the two variables will be described and their relationships will be tested automatically according to their data types. For example, if one of the two input variables is a categorical variable, another variable will be described hierarchically based on the categorical variable and the statistical differences between different groups will be compared using appropriate statistical methods. And for groups of more than two, the post hoc test will be applied. For more information on the methods we used, please see the following references: Libiseller, C. and Grimvall, A. (2002) <doi: [...truncated...]
Author: Xiuquan Nie [aut, cph, cre], Mengyi Wang [ctb, rev], Weihong Chen [fnd]
Maintainer: Xiuquan Nie <niexiuquan1995@foxmail.com>

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