Sun, 25 Feb 2018

Package SVMMaj updated to version 0.2-8 with previous version 0.2-2 dated 2011-01-13

Title: Implementation of the SVM-Maj Algorithm
Description: Implements the SVM-Maj algorithm to train data with support vector machine as described in Groenen et al. (2008) <doi:10.1007/s11634-008-0020-9>. This algorithm uses two efficient updates, one for linear kernel and one for the nonlinear kernel.
Author: Hoksan Yip, Patrick J.F. Groenen, Georgi Nalbantov
Maintainer: Hok San Yip <hoksan@gmail.com>

Diff between SVMMaj versions 0.2-2 dated 2011-01-13 and 0.2-8 dated 2018-02-25

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Package pollen updated to version 0.70.0 with previous version 0.53.00 dated 2017-07-21

Title: Analysis of Aerobiological Data
Description: Supports analysis of aerobiological data. Available features include determination of pollen season limits, replacement of outliers (Kasprzyk and Walanus (2014) <doi:10.1007/s10453-014-9332-8>), and calculation of growing degree days.
Author: Jakub Nowosad [aut, cre] (<https://orcid.org/0000-0002-1057-3721>)
Maintainer: Jakub Nowosad <nowosad.jakub@gmail.com>

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Package pillar updated to version 1.2.0 with previous version 1.1.0 dated 2018-01-14

Title: Coloured Formatting for Columns
Description: Provides a 'pillar' generic designed for formatting columns of data using the full range of colours provided by modern terminals.
Author: Kirill Müller [aut, cre], Hadley Wickham [aut], RStudio [cph]
Maintainer: Kirill Müller <krlmlr+r@mailbox.org>

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More information about pillar at CRAN
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Package mctest updated to version 1.2 with previous version 1.1.1 dated 2017-10-28

Title: Multicollinearity Diagnostic Measures
Description: Package computes popular and widely used multicollinearity diagnostic measures. Package also indicates which regressors may be the reason of collinearity among regressors.
Author: Dr. Muhammad Imdad Ullah and Dr. Muhammad Aslam
Maintainer: Dr. Muhammad Imdad Ullah <mimdadasad@gmail.com>

Diff between mctest versions 1.1.1 dated 2017-10-28 and 1.2 dated 2018-02-25

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Package KGode updated to version 1.0.1 with previous version 1.0.0 dated 2017-10-23

Title: Kernel Based Gradient Matching for Parameter Inference in Ordinary Differential Equations
Description: The kernel ridge regression and the gradient matching algorithm proposed in Niu et al. (2016) <http://jmlr.org/proceedings/papers/v48/niu16.html> and the warping algorithm proposed in Niu et al. (2017) <DOI:10.1007/s00180-017-0753-z> are implemented for parameter inference in differential equations. Four schemes are provided for improving parameter estimation in odes by using the odes regularisation and warping.
Author: Mu Niu [aut, cre]
Maintainer: Mu Niu <mu.niu@plymouth.ac.uk>

Diff between KGode versions 1.0.0 dated 2017-10-23 and 1.0.1 dated 2018-02-25

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Package tidypredict updated to version 0.2.0 with previous version 0.1.0 dated 2018-01-17

Title: Run Predictions Inside the Database
Description: It parses a fitted 'R' model object, and returns a formula in 'Tidy Eval' code that calculates the predictions. It works with several databases back-ends because it leverages 'dplyr' and 'dbplyr' for the final 'SQL' translation of the algorithm. It currently supports lm(), glm(), randomForest() and ranger() models.
Author: Edgar Ruiz [aut, cre]
Maintainer: Edgar Ruiz <edgar@rstudio.com>

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Package EDMeasure updated to version 1.2.0 with previous version 1.1.0 dated 2018-02-13

Title: Energy-Based Dependence Measures
Description: Implementations of (1) mutual dependence measures and mutual independence tests in Jin, Z., and Matteson, D. S. (2017) <arXiv:1709.02532>; (2) independent component analysis methods based on mutual dependence measures in Jin, Z., and Matteson, D. S. (2017) <arXiv:1709.02532> and Pfister, N., et al. (2018) <doi:10.1111/rssb.12235>; (3) conditional mean dependence measures and conditional mean independence tests in Shao, X., and Zhang, J. (2014) <doi:10.1080/01621459.2014.887012>, Park, T., et al. (2015) <doi:10.1214/15-EJS1047>, and Lee, C. E., and Shao, X. (2017) <doi:10.1080/01621459.2016.1240083>.
Author: Ze Jin [aut, cre], Shun Yao [aut], David S. Matteson [aut], Xiaofeng Shao [aut]
Maintainer: Ze Jin <zj58@cornell.edu>

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Package stoRy updated to version 0.1.2 with previous version 0.1.1 dated 2017-07-14

Title: Functions for the Analysis of Star Trek Thematic Data
Description: An implementation of 1) the hypergeometric test for over-representation of literary themes in a storyset (a list of stories) relative to a background list of stories, and 2) a recommendation system that takes a user-selected story as input and returns a ranked list of similar stories on the basis of shared themes. The package is currently implemented for the episodes of the Star Trek television franchise series The Original Series (TOS), The Animated Series (TAS), The Next Generation (TNG), and Voyager (VOY).
Author: Paul Sheridan, Mikael Onsjö
Maintainer: Paul Sheridan <paul.sheridan.stats@gmail.com>

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Package rvinecopulib updated to version 0.2.6.1.1 with previous version 0.2.5.1.0 dated 2018-01-14

Title: High Performance Algorithms for Vine Copula Modeling
Description: Provides an interface to 'vinecopulib', a C++ library for vine copula modeling based on 'Boost' and 'Eigen'. The 'rvinecopulib' package implements the core features of the popular 'VineCopula' package, in particular inference algorithms for both vine copula and bivariate copula models. Advantages over 'VineCopula' are a sleeker and more modern API, improved performances, especially in high dimensions, nonparametric and multi-parameter families. The 'rvinecopulib' package includes 'vinecopulib' as header-only C++ library (currently version 0.2.6). Thus users do not need to install 'vinecopulib' itself in order to use 'rvinecopulib'. Since their initial releases, 'vinecopulib' is licensed under the MIT License, and 'rvinecopulib' is licensed under the GNU GPL version 3.
Author: Thomas Nagler [aut, cre], Thibault Vatter [aut]
Maintainer: Thomas Nagler <info@vinecopulib.org>

Diff between rvinecopulib versions 0.2.5.1.0 dated 2018-01-14 and 0.2.6.1.1 dated 2018-02-25

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Package jpmesh updated to version 1.1.0 with previous version 1.0.1 dated 2017-12-03

Title: Utilities for Japanese Mesh Code
Description: Helpful functions for using mesh code (80km to 125m) data in Japan. Visualize mesh code using 'ggplot2' and 'leaflet', etc.
Author: Shinya Uryu [aut, cre] (<https://orcid.org/0000-0002-0493-6186>)
Maintainer: Shinya Uryu <suika1127@gmail.com>

Diff between jpmesh versions 1.0.1 dated 2017-12-03 and 1.1.0 dated 2018-02-25

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Package gam updated to version 1.15 with previous version 1.14-4 dated 2017-04-25

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

Diff between gam versions 1.14-4 dated 2017-04-25 and 1.15 dated 2018-02-25

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Package snakecase updated to version 0.9.0 with previous version 0.8.1 dated 2018-01-21

Title: Convert Strings into any Case
Description: A consistent, flexible and easy to use tool to parse and convert strings into cases like snake or camel among others.
Author: Malte Grosser [aut, cre]
Maintainer: Malte Grosser <malte.grosser@gmail.com>

Diff between snakecase versions 0.8.1 dated 2018-01-21 and 0.9.0 dated 2018-02-25

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Package secr updated to version 3.1.5 with previous version 3.1.3 dated 2017-12-03

Title: Spatially Explicit Capture-Recapture
Description: Functions to estimate the density and size of a spatially distributed animal population sampled with an array of passive detectors, such as traps, or by searching polygons or transects. Models incorporating distance-dependent detection are fitted by maximizing the likelihood. Tools are included for data manipulation and model selection.
Author: Murray Efford
Maintainer: Murray Efford <murray.efford@otago.ac.nz>

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Package rpgm updated to version 1.1.2 with previous version 1.1.1 dated 2017-11-14

Title: Fast Simulation of Normal/Exponential Random Variables and Stochastic Differential Equations / Poisson Processes
Description: Fast simulation of some random variables than the usual native functions, including rnorm() and rexp(), using Ziggurat method, reference: MARSAGLIA, George, TSANG, Wai Wan, and al. (2000) <doi:10.18637/jss.v005.i08>, and fast simulation of stochastic differential equations / Poisson processes.
Author: Nicolas Baradel
Maintainer: Nicolas Baradel - PGM Solutions <nicolas.baradel@pgm-solutions.com>

Diff between rpgm versions 1.1.1 dated 2017-11-14 and 1.1.2 dated 2018-02-25

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More information about rpgm at CRAN
Permanent link

Package NSM3 updated to version 1.11 with previous version 1.10 dated 2017-09-20

Title: Functions and Datasets to Accompany Hollander, Wolfe, and Chicken - Nonparametric Statistical Methods, Third Edition
Description: Designed to replace the tables which were in the back of the first two editions of Hollander and Wolfe - Nonparametric Statistical Methods. Exact procedures are performed when computationally possible. Monte Carlo and Asymptotic procedures are performed otherwise. For those procedures included in the base packages, our code simply provides a wrapper to standardize the output with the other procedures in the package.
Author: Grant Schneider, Eric Chicken, Rachel Becvarik
Maintainer: Grant Schneider <schneider.393@osu.edu>

Diff between NSM3 versions 1.10 dated 2017-09-20 and 1.11 dated 2018-02-25

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Package fdapace updated to version 0.4.0 with previous version 0.3.0 dated 2017-01-25

Title: Functional Data Analysis and Empirical Dynamics
Description: Provides implementation of various methods of Functional Data Analysis (FDA) and Empirical Dynamics. The core of this package is Functional Principal Component Analysis (FPCA), a key technique for functional data analysis, for sparsely or densely sampled random trajectories and time courses, via the Principal Analysis by Conditional Estimation (PACE) algorithm or numerical integration. PACE is useful for the analysis of data that have been generated by a sample of underlying (but usually not fully observed) random trajectories. It does not rely on pre-smoothing of trajectories, which is problematic if functional data are sparsely sampled. PACE provides options for functional regression and correlation, for Longitudinal Data Analysis, the analysis of stochastic processes from samples of realized trajectories, and for the analysis of underlying dynamics. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue".
Author: Xiongtao Dai [aut], Pantelis Z. Hadjipantelis [aut, cre], Kynghee Han [aut], Hao Ji [aut], Shu-Chin Lin [ctb], Hans-Georg Mueller [cph, ths], Jane-Ling Wang [cph, ths]
Maintainer: Pantelis Z. Hadjipantelis <pantelis@ucdavis.edu>

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Package ADMM updated to version 0.2.2 with previous version 0.2.1 dated 2018-02-05

Title: Algorithms using Alternating Direction Method of Multipliers
Description: Provides algorithms to solve popular optimization problems in statistics such as regression or denoising based on Alternating Direction Method of Multipliers (ADMM). See Boyd et al (2010) <doi:10.1561/2200000016> for complete introduction to the method.
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>), Xiaozhi Zhu [aut]
Maintainer: Kisung You <kyou@nd.edu>

Diff between ADMM versions 0.2.1 dated 2018-02-05 and 0.2.2 dated 2018-02-25

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Package nzpullover updated to version 0.3.0 with previous version 0.0.2 dated 2017-01-29

Title: Driving Offences in New Zealand Between 2009 and 2016
Description: Datasets of driving offences and fines in New Zealand between 2009 and 2017. Originally published by the New Zealand Police at <http://www.police.govt.nz/about-us/publication/road-policing-driver-offence-data-january-2009-december-2017>.
Author: Duncan Garmonsway [aut, cre]
Maintainer: Duncan Garmonsway <nacnudus@gmail.com>

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Package Rcssplot updated to version 0.3.0 with previous version 0.2.0.0 dated 2017-03-06

Title: Styling of Graphics using Cascading Style Sheets
Description: Provides a means to style plots through cascading style sheets. This separates the aesthetics from the data crunching in plots and charts.
Author: Tomasz Konopka [aut, cre]
Maintainer: Tomasz Konopka <tokonopka@gmail.com>

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Package zoib updated to version 1.5.0 with previous version 1.4.2 dated 2016-10-18

Title: Bayesian Inference for Beta Regression and Zero-or-One Inflated Beta Regression
Description: Fits beta regression and zero-or-one inflated beta regression and obtains Bayesian Inference of the model via the Markov Chain Monte Carlo approach implemented in JAGS.
Author: Fang Liu <fang.liu.131@nd.edu> with contributions from Yunchuan Kong
Maintainer: Fang Liu <fang.liu.131@nd.edu>

Diff between zoib versions 1.4.2 dated 2016-10-18 and 1.5.0 dated 2018-02-25

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Built and running on Debian GNU/Linux using R, littler and blosxom. Styled with Bootstrap.