Thu, 10 Jan 2019

Package nprobust updated to version 0.1.4 with previous version 0.1.3 dated 2018-05-01

Title: Nonparametric Robust Estimation and Inference Methods using Local Polynomial Regression and Kernel Density Estimation
Description: Tools for data-driven statistical analysis using local polynomial regression and kernel density estimation methods as described in Calonico, Cattaneo and Farrell (2018): lprobust() for local polynomial point estimation and robust bias-corrected inference and kdrobust() for kernel density point estimation and robust bias-corrected inference. Several optimal bandwidth selection procedures are computed by lpbwselect() and kdbwselect() for local polynomial and kernel density estimation, respectively. Finally, nprobust.plot() for density and regression plots with robust confidence interval.
Author: Sebastian Calonico <scalonico@bus.miami.edu>, Matias D. Cattaneo <cattaneo@umich.edu>, Max H. Farrell <max.farrell@chicagobooth.edu>
Maintainer: Sebastian Calonico <scalonico@bus.miami.edu>

Diff between nprobust versions 0.1.3 dated 2018-05-01 and 0.1.4 dated 2019-01-10

 DESCRIPTION             |    8 +-
 MD5                     |   24 +++---
 R/lpbwselect.R          |    7 +
 R/lprobust.R            |  185 ++++++++++++++++++++++++++++++++++++++++++------
 R/npfunctions.R         |    5 +
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 man/kdrobust.Rd         |   10 +-
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 13 files changed, 228 insertions(+), 63 deletions(-)

More information about nprobust at CRAN
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Package geojsonsf updated to version 1.3.0 with previous version 1.2.1 dated 2018-11-22

Title: GeoJSON to Simple Feature Converter
Description: Converts Between GeoJSON and simple feature objects.
Author: David Cooley [aut, cre]
Maintainer: David Cooley <dcooley@symbolix.com.au>

Diff between geojsonsf versions 1.2.1 dated 2018-11-22 and 1.3.0 dated 2019-01-10

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 geojsonsf-1.3.0/geojsonsf/NAMESPACE                                                        |    1 
 geojsonsf-1.3.0/geojsonsf/NEWS.md                                                          |   12 
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 geojsonsf-1.3.0/geojsonsf/R/geojson_sf.R                                                   |    3 
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 geojsonsf-1.3.0/geojsonsf/man/df_geojson.Rd                                                |    8 
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 geojsonsf-1.3.0/geojsonsf/src/RcppExports.cpp                                              |   49 
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 geojsonsf-1.3.0/geojsonsf/src/geojson_to_sf.cpp                                            |  558 ----------
 geojsonsf-1.3.0/geojsonsf/src/geojson_to_wkt.cpp                                           |   55 
 geojsonsf-1.3.0/geojsonsf/src/geojson_wkt.cpp                                              |   20 
 geojsonsf-1.3.0/geojsonsf/src/read_geojson.cpp                                             |   13 
 geojsonsf-1.3.0/geojsonsf/src/sf_geojson.cpp                                               |  272 ----
 geojsonsf-1.3.0/geojsonsf/tests/testthat/test-df_geojson.R                                 |   11 
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 geojsonsf-1.3.0/geojsonsf/tests/testthat/test-geojson_sf.R                                 |   11 
 geojsonsf-1.3.0/geojsonsf/tests/testthat/test-sf_geojson.R                                 |    5 
 45 files changed, 349 insertions(+), 1547 deletions(-)

More information about geojsonsf at CRAN
Permanent link

Package cliqueMS updated to version 0.2.4 with previous version 0.2.3 dated 2018-11-15

Title: Annotation of Isotopes, Adducts and Fragmentation Adducts for in-Source LC/MS Metabolomics Data
Description: Annotates data from liquid chromatography coupled to mass spectrometry (LC/MS) metabolomics experiments. Based on a network algorithm (O.Senan, A. Aguilar- Mogas, M. Navarro, O. Yanes, R.Guimerà and M. Sales-Pardo, Metabolomics Conference (2016), Dublin), 'CliqueMS' builds a weighted similarity network where nodes are features and edges are weighted according to the similarity of this features. Then it searches for the most plausible division of the similarity network into cliques (fully connected components). Finally it annotates metabolites within each clique, obtaining for each annotated metabolite the neutral mass and their features, corresponding to isotopes, ionization adducts and fragmentation adducts of that metabolite.
Author: Oriol Senan Campos [aut, cre], Antoni Aguilar-Mogas [aut], Jordi Capellades [aut], Miriam Navarro [aut], Oscar Yanes [aut], Roger Guimerà [aut], Marta Sales-Pardo [aut]
Maintainer: Oriol Senan Campos <oriol.senan@urv.cat>

Diff between cliqueMS versions 0.2.3 dated 2018-11-15 and 0.2.4 dated 2019-01-10

 DESCRIPTION                     |    8 +--
 MD5                             |   12 ++--
 NEWS.md                         |    7 ++
 R/findAnnotation.R              |   21 +++++++
 inst/doc/annotate_features.html |   62 +++++++++++------------
 src/annotationCliqueMSR.h       |  106 ++++++++++++++++++++++++++++++++--------
 src/networkCliqueMSR.h          |   62 ++++++++++++-----------
 7 files changed, 187 insertions(+), 91 deletions(-)

More information about cliqueMS at CRAN
Permanent link

Package SSDforR updated to version 1.5 with previous version 1.4.21 dated 2018-10-06

Title: Functions to Analyze Single System Data
Description: Functions to visually and statistically analyze single system data.
Author: Charles Auerbach [aut, cre], Wendy Zeitlin [aut]
Maintainer: Charles Auerbach <auerbach@yu.edu>

Diff between SSDforR versions 1.4.21 dated 2018-10-06 and 1.5 dated 2019-01-10

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More information about SSDforR at CRAN
Permanent link

Package h2o updated to version 3.22.1.1 with previous version 3.20.0.8 dated 2018-09-25

Title: R Interface for 'H2O'
Description: R interface for 'H2O', the scalable open source machine learning platform that offers parallelized implementations of many supervised and unsupervised machine learning algorithms such as Generalized Linear Models, Gradient Boosting Machines (including XGBoost), Random Forests, Deep Neural Networks (Deep Learning), Stacked Ensembles, Naive Bayes, Cox Proportional Hazards, K-Means, PCA, Word2Vec, as well as a fully automatic machine learning algorithm (AutoML).
Author: Erin LeDell [aut, cre], Navdeep Gill [aut], Spencer Aiello [aut], Anqi Fu [aut], Arno Candel [aut], Cliff Click [aut], Tom Kraljevic [aut], Tomas Nykodym [aut], Patrick Aboyoun [aut], Michal Kurka [aut], Michal Malohlava [aut], Ludi Rehak [ctb], Eric Eckstrand [ctb], Brandon Hill [ctb], Sebastian Vidrio [ctb], Surekha Jadhawani [ctb], Amy Wang [ctb], Raymond Peck [ctb], Wendy Wong [ctb], Jan Gorecki [ctb], Matt Dowle [ctb], Yuan Tang [ctb], Lauren DiPerna [ctb], H2O.ai [cph, fnd]
Maintainer: Erin LeDell <erin@h2o.ai>

Diff between h2o versions 3.20.0.8 dated 2018-09-25 and 3.22.1.1 dated 2019-01-10

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More information about h2o at CRAN
Permanent link

Package dynamichazard updated to version 0.6.2 with previous version 0.6.1 dated 2018-10-22

Title: Dynamic Hazard Models using State Space Models
Description: Contains functions that lets you fit dynamic hazard models using state space models. The first implemented model is described in Fahrmeir (1992) <doi:10.1080/01621459.1992.10475232> and Fahrmeir (1994) <doi:10.1093/biomet/81.2.317>. Extensions hereof are available where the Extended Kalman filter is replaced by an unscented Kalman filter and other options including particle filters. The implemented particle filters support more general state space models.
Author: Benjamin Christoffersen [cre, aut], Alan Miller [cph], Anthony Williams [cph], Boost developers [cph], R-core [cph]
Maintainer: Benjamin Christoffersen <boennecd@gmail.com>

Diff between dynamichazard versions 0.6.1 dated 2018-10-22 and 0.6.2 dated 2019-01-10

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More information about dynamichazard at CRAN
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Package BiProbitPartial updated to version 1.0.3 with previous version 1.0.2 dated 2019-01-08

Title: Bivariate Probit with Partial Observability
Description: A suite of functions to estimate, summarize and perform predictions with the bivariate probit subject to partial observability. The frequentist and Bayesian probabilistic philosophies are both supported. The frequentist method is estimated with maximum likelihood and the Bayesian method is estimated with a Markov Chain Monte Carlo (MCMC) algorithm developed by Rajbanhdari, A (2014) <doi:10.1002/9781118771051.ch13>.
Author: Michael Guggisberg and Amrit Romana
Maintainer: Michael Guggisberg <mguggisb@ida.org>

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Package mlrCPO updated to version 0.3.4-2 with previous version 0.3.4-1 dated 2018-10-02

Title: Composable Preprocessing Operators and Pipelines for Machine Learning
Description: Toolset that enriches 'mlr' with a diverse set of preprocessing operators. Composable Preprocessing Operators ("CPO"s) are first-class R objects that can be applied to data.frames and 'mlr' "Task"s to modify data, can be attached to 'mlr' "Learner"s to add preprocessing to machine learning algorithms, and can be composed to form preprocessing pipelines.
Author: Martin Binder [aut, cre], Bernd Bischl [ctb], Michel Lang [ctb], Lars Kotthoff [ctb]
Maintainer: Martin Binder <developer.mb706@doublecaret.com>

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Package liquidSVM updated to version 1.2.2 with previous version 1.2.1 dated 2017-07-19

Title: A Fast and Versatile SVM Package
Description: Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.
Author: Ingo Steinwart, Philipp Thomann
Maintainer: Philipp Thomann <philipp.thomann@mathematik.uni-stuttgart.de>

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Package rsconnect updated to version 0.8.13 with previous version 0.8.12 dated 2018-12-05

Title: Deployment Interface for R Markdown Documents and Shiny Applications
Description: Programmatic deployment interface for 'RPubs', 'shinyapps.io', and 'RStudio Connect'. Supported content types include R Markdown documents, Shiny applications, Plumber APIs, plots, and static web content.
Author: JJ Allaire
Maintainer: Jonathan McPherson <jonathan@rstudio.com>

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Package baRcodeR updated to version 0.1.2 with previous version 0.1.1 dated 2018-11-29

Title: Labelling, Tracking, and Collecting Data from Biological Samples
Description: Tools to generate unique identifiers and printable barcoded labels for sample management. The creation of unique ID codes and printable PDF files can be initiated by standard commands, user prompts, or through a GUI addin for R Studio. Both single-level and hierarchical labels can be created in the command line interactively or non-interactively.
Author: Yihan Wu [aut], Robert Colautti [aut, cre]
Maintainer: Robert Colautti <robert.colautti@queensu.ca>

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Package spatsoc updated to version 0.1.6 with previous version 0.1.4 dated 2018-10-26

Title: Group Animal Relocation Data by Spatial and Temporal Relationship
Description: Detects spatial and temporal groups in GPS relocations. It can be used to convert GPS relocations to gambit-of-the-group format to build proximity-based social networks. In addition, the randomizations function provides data-stream randomization methods suitable for GPS data.
Author: Alec L. Robitaille [aut, cre] (<https://orcid.org/0000-0002-4706-1762>), Quinn Webber [aut] (<https://orcid.org/0000-0002-0434-9360>), Eric Vander Wal [aut] (<https://orcid.org/0000-0002-8534-4317>)
Maintainer: Alec L. Robitaille <robit.alec@gmail.com>

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Package showtext updated to version 0.6 with previous version 0.5-1 dated 2018-01-16

Title: Using Fonts More Easily in R Graphs
Description: Making it easy to use various types of fonts ('TrueType', 'OpenType', Type 1, web fonts, etc.) in R graphs, and supporting most output formats of R graphics including PNG, PDF and SVG. Text glyphs will be converted into polygons or raster images, hence after the plot has been created, it no longer relies on the font files. No external software such as 'Ghostscript' is needed to use this package.
Author: Yixuan Qiu and authors/contributors of the included software. See file AUTHORS for details.
Maintainer: Yixuan Qiu <yixuan.qiu@cos.name>

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Package crunch updated to version 1.25.0 with previous version 1.24.0 dated 2018-09-12

Title: Crunch.io Data Tools
Description: The Crunch.io service <http://crunch.io/> provides a cloud-based data store and analytic engine, as well as an intuitive web interface. Using this package, analysts can interact with and manipulate Crunch datasets from within R. Importantly, this allows technical researchers to collaborate naturally with team members, managers, and clients who prefer a point-and-click interface.
Author: Neal Richardson [aut, cre], Jonathan Keane [aut], Gordon Shotwell [aut]
Maintainer: Neal Richardson <neal@crunch.io>

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Package statGraph updated to version 0.2.0 with previous version 0.1.0 dated 2017-04-21

Title: Statistical Methods for Graphs
Description: Contains statistical methods to analyze graphs, such as graph parameter estimation, model selection based on the GIC (Graph Information Criterion), statistical tests to discriminate two or more populations of graphs (ANOGVA -Analysis of Graph Variability), correlation between graphs, and clustering of graphs.
Author: Suzana S. Santos [aut], Eduardo S. Lira [aut], Andre Fujita [aut, cre]
Maintainer: Andre Fujita <fujita@ime.usp.br>

Diff between statGraph versions 0.1.0 dated 2017-04-21 and 0.2.0 dated 2019-01-10

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New package qrandom with initial version 1.0
Package: qrandom
Type: Package
Title: True Random Numbers using the ANU Quantum Random Numbers Server
Version: 1.0
Date: 2019-01-08
Authors@R: c(person(given = "Siegfried", family = "Köstlmeier", role = c("aut", "cre"), email = "siegfried.koestlmeier@gmail.com"))
Maintainer: Siegfried Köstlmeier <siegfried.koestlmeier@gmail.com>
Description: The ANU Quantum Random Number Generator provided by the Australian National University generates true random numbers in real-time by measuring the quantum fluctuations of the vacuum. This package offers an interface using their API. The electromagnetic field of the vacuum exhibits random fluctuations in phase and amplitude at all frequencies. By carefully measuring these fluctuations, one is able to generate ultra-high bandwidth random numbers. The quantum Random Number Generator is based on the papers by Symul et al., (2011) <doi:10.1063/1.3597793> and Haw, et al. (2015) <doi:10.1103/PhysRevApplied.3.054004>. The package offers functions to retrieve a sequence of random integers or hexadecimals and true random samples from a normal or uniform distribution.
License: GPL-2 | file LICENSE
Imports: curl, jsonlite, methods, Rmpfr, utils
Suggests: testthat
Depends: R (>= 3.5)
Encoding: UTF-8
LazyData: true
URL: https://qrng.anu.edu.au/index.php
NeedsCompilation: no
Packaged: 2019-01-08 12:54:45 UTC; Siegfried
Author: Siegfried Köstlmeier [aut, cre]
Repository: CRAN
Date/Publication: 2019-01-10 17:00:03 UTC

More information about qrandom at CRAN
Permanent link

Package KeyboardSimulator updated to version 2.1.0 with previous version 2.0 dated 2019-01-02

Title: Keyboard and Mouse Input Simulation for Windows OS
Description: Control your keyboard and mouse with R code by simulating key presses and mouse clicks. The input simulation is implemented with the Windows API.
Author: Jim Chen [aut, cre], Jeff Keller [aut, ctb], Chieh Hsu [ctb]
Maintainer: Jim Chen <jim71183@gmail.com>

Diff between KeyboardSimulator versions 2.0 dated 2019-01-02 and 2.1.0 dated 2019-01-10

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Package tinytex updated to version 0.10 with previous version 0.9 dated 2018-10-23

Title: Helper Functions to Install and Maintain 'TeX Live', and Compile 'LaTeX' Documents
Description: Helper functions to install and maintain the 'LaTeX' distribution named 'TinyTeX' (<https://yihui.name/tinytex/>), a lightweight, cross-platform, portable, and easy-to-maintain version of 'TeX Live'. This package also contains helper functions to compile 'LaTeX' documents, and install missing 'LaTeX' packages automatically.
Author: Yihui Xie [aut, cre, cph] (<https://orcid.org/0000-0003-0645-5666>), RStudio, Inc. [cph], Fernando Cagua [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

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Package spatstat updated to version 1.58-2 with previous version 1.57-1 dated 2018-11-04

Title: Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests
Description: Comprehensive open-source toolbox for analysing Spatial Point Patterns. Focused mainly on two-dimensional point patterns, including multitype/marked points, in any spatial region. Also supports three-dimensional point patterns, space-time point patterns in any number of dimensions, point patterns on a linear network, and patterns of other geometrical objects. Supports spatial covariate data such as pixel images. Contains over 2000 functions for plotting spatial data, exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. Data types include point patterns, line segment patterns, spatial windows, pixel images, tessellations, and linear networks. Exploratory methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlation functions, segregation indices, mark dependence diagnostics, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported. Parametric models can be fitted to point pattern data using the functions ppm(), kppm(), slrm(), dppm() similar to glm(). Types of models include Poisson, Gibbs and Cox point processes, Neyman-Scott cluster processes, and determinantal point processes. Models may involve dependence on covariates, inter-point interaction, cluster formation and dependence on marks. Models are fitted by maximum likelihood, logistic regression, minimum contrast, and composite likelihood methods. A model can be fitted to a list of point patterns (replicated point pattern data) using the function mppm(). The model can include random effects and fixed effects depending on the experimental design, in addition to all the features listed above. Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise(), AIC()) and variable selection (sdr). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots.
Author: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>, Rolf Turner <r.turner@auckland.ac.nz> and Ege Rubak <rubak@math.aau.dk>, with substantial contributions of code by Kasper Klitgaard Berthelsen; Ottmar Cronie; Yongtao Guan; Ute Hahn; Abdollah Jalilian; Marie-Colette van Lieshout; Greg McSwiggan; Tuomas Rajala; Suman Rakshit; Dominic Schuhmacher; Rasmus Waagepetersen; and Hangsheng Wang. Additional contributions by M. Adepeju; C. Anderson; Q.W. Ang; R. Arellano; J. Astrom; M. Austenfeld; S. Azaele; M. Baddeley; C. Beale; M. Bell; R. Bernhardt; T. Bendtsen; A. Bevan; B. Biggerstaff; A. Bilgrau; L. Bischof; C. Biscio; R. Bivand; J.M. Blanco Moreno; F. Bonneu; J. Burgos; S. Byers; Y.M. Chang; J.B. Chen; I. Chernayavsky; Y.C. Chin; B. Christensen; J.-F. Coeurjolly; K. Colyvas; H. Commenges; R. Constantine; R. Corria Ainslie; R. Cotton; M. de la Cruz; P. Dalgaard; M. D'Antuono; S. Das; T. Davies; P.J. Diggle; P. Donnelly; I. Dryden; S. Eglen; A. El-Gabbas; B. Fandohan; O. Flores; E.D. Ford; P. Forbes; S. Frank; J. Franklin; N. Funwi-Gabga; O. Garcia; A. Gault; J. Geldmann; M. Genton; S. Ghalandarayeshi; J. Gilbey; J. Goldstick; P. Grabarnik; C. Graf; U. Hahn; A. Hardegen; M.B. Hansen; M. Hazelton; J. Heikkinen; M. Hering; M. Herrmann; M. Hesselbarth; P. Hewson; H. Heydarian; K. Hingee; K. Hornik; P. Hunziker; J. Hywood; R. Ihaka; C. Icos; A. Jammalamadaka; R. John-Chandran; D. Johnson; M. Khanmohammadi; R. Klaver; P. Kovesi; L. Kozmian-Ledward; M. Kuhn; J. Laake; R.A. Lamb; F. Lavancier; T. Lawrence; T. Lazauskas; J. Lee; G.P. Leser; A. Li; H.T. Li; G. Limitsios; A. Lister; B. Madin; M. Maechler; J. Marcus; K. Marchikanti; R. Mark; J. Mateu; P. McCullagh; U. Mehlig; F. Mestre; S. Meyer; X.C. Mi; L. De Middeleer; R.K. Milne; E. Miranda; J. Moller; I. Moncada; M. Moradi; V. Morera Pujol; E. Mudrak; G.M. Nair; N. Najari; N. Nava; L.S. Nielsen; F. Nunes; J.R. Nyengaard; J. Oehlschlaegel; T. Onkelinx; S. O'Riordan; E. Parilov; J. Picka; N. Picard; M. Porter; S. Protsiv; A. Raftery; S. Rakshit; B. Ramage; P. Ramon; X. Raynaud; N. Read; M. Reiter; I. Renner; T.O. Richardson; B.D. Ripley; E. Rosenbaum; B. Rowlingson; J. Rudokas; J. Rudge; C. Ryan; F. Safavimanesh; A. Sarkka; C. Schank; K. Schladitz; S. Schutte; B.T. Scott; O. Semboli; F. Semecurbe; V. Shcherbakov; G.C. Shen; P. Shi; H.-J. Ship; T.L. Silva; I.-M. Sintorn; Y. Song; M. Spiess; M. Stevenson; K. Stucki; M. Sumner; P. Surovy; B. Taylor; T. Thorarinsdottir; L. Torres; B. Turlach; T. Tvedebrink; K. Ummer; M. Uppala; A. van Burgel; T. Verbeke; M. Vihtakari; A. Villers; F. Vinatier; S. Voss; S. Wagner; H. Wang; H. Wendrock; J. Wild; C. Witthoft; S. Wong; M. Woringer; M.E. Zamboni and A. Zeileis.
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

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Package poweRlaw updated to version 0.70.2 with previous version 0.70.1 dated 2017-08-29

Title: Analysis of Heavy Tailed Distributions
Description: An implementation of maximum likelihood estimators for a variety of heavy tailed distributions, including both the discrete and continuous power law distributions. Additionally, a goodness-of-fit based approach is used to estimate the lower cut-off for the scaling region.
Author: Colin Gillespie [aut, cre]
Maintainer: Colin Gillespie <csgillespie@gmail.com>

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Package laeken updated to version 0.5.0 with previous version 0.4.6 dated 2014-08-19

Title: Estimation of Indicators on Social Exclusion and Poverty
Description: Estimation of indicators on social exclusion and poverty, as well as Pareto tail modeling for empirical income distributions.
Author: Andreas Alfons [aut, cre], Josef Holzer [aut], Matthias Templ [aut], Alexander Haider [ctb]
Maintainer: Andreas Alfons <alfons@ese.eur.nl>

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Package spaMM updated to version 2.6.0 with previous version 2.5.11 dated 2018-11-19

Title: Mixed-Effect Models, Particularly Spatial Models
Description: Inference based on mixed-effect models, including generalized linear mixed models with spatial correlations and models with non-Gaussian random effects (e.g., Beta). Variation in residual variance (heteroscedasticity) can itself be represented by a generalized linear mixed model. Various approximations of likelihood or restricted likelihood are implemented, in particular h-likelihood (Lee and Nelder 2001 <doi:10.1093/biomet/88.4.987>) and Laplace approximation.
Author: François Rousset [aut, cre, cph] (<https://orcid.org/0000-0003-4670-0371>), Jean-Baptiste Ferdy [aut, cph], Alexandre Courtiol [aut] (<https://orcid.org/0000-0003-0637-2959>), GSL authors [ctb] (src/gsl_bessel.*)
Maintainer: François Rousset <francois.rousset@umontpellier.fr>

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Package DtD updated to version 0.2.1 with previous version 0.2.0 dated 2018-09-10

Title: Distance to Default
Description: Provides fast methods to work with Merton's distance to default model introduced in Merton (1974) <doi:10.1111/j.1540-6261.1974.tb03058.x>. The methods includes simulation and estimation of the parameters.
Author: Benjamin Christoffersen [cre, aut], R-core [cph]
Maintainer: Benjamin Christoffersen <boennecd@gmail.com>

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Package vennLasso updated to version 0.1.4 with previous version 0.1.3 dated 2018-10-30

Title: Variable Selection for Heterogeneous Populations
Description: Provides variable selection and estimation routines for models with main effects stratified on multiple binary factors. The 'vennLasso' package is an implementation of the method introduced in Huling, et al. (2017) <doi:10.1111/biom.12769>.
Author: Jared Huling [aut, cre] (<https://orcid.org/0000-0003-0670-4845>), Muxuan Liang [ctb], Yixuan Qiu [cph], Gael Guennebaud [cph], Ray Gardner [cph], Jitse Niesen [cph]
Maintainer: Jared Huling <jaredhuling@gmail.com>

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Package soundgen updated to version 1.3.2 with previous version 1.3.1 dated 2018-10-04

Title: Parametric Voice Synthesis
Description: Tools for sound synthesis and acoustic analysis. Performs parametric synthesis of sounds with harmonic and noise components such as animal vocalizations or human voice. Also includes tools for spectral analysis, pitch tracking, audio segmentation, self-similarity matrices, morphing, etc.
Author: Andrey Anikin [aut, cre]
Maintainer: Andrey Anikin <rty.anik@rambler.ru>

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Package sjlabelled updated to version 1.0.16 with previous version 1.0.15 dated 2018-11-22

Title: Labelled Data Utility Functions
Description: Collection of functions dealing with labelled data, like reading and writing data between R and other statistical software packages like 'SPSS', 'SAS' or 'Stata', and working with labelled data. This includes easy ways to get, set or change value and variable label attributes, to convert labelled vectors into factors or numeric (and vice versa), or to deal with multiple declared missing values.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package jsonify updated to version 0.2.0 with previous version 0.1.2 dated 2018-12-07

Title: Converts 'R' Objects to Javascript Object Notation (JSON)
Description: Converts 'R' objects into Javascript Object Notation (JSON) using the 'rapidjsonr' library <https://CRAN.R-project.org/package=rapidjsonr>.
Author: David Cooley [aut, cre]
Maintainer: David Cooley <dcooley@symbolix.com.au>

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Package hexSticker updated to version 0.4.5 with previous version 0.4.4 dated 2018-06-22

Title: Create Hexagon Sticker in R
Description: Helper functions for creating reproducible hexagon sticker purely in R.
Author: Guangchuang Yu [aut, cre], Laurent Gatto [ctb], Johannes Rainer [ctb], Sebastian Gibb [ctb]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

Diff between hexSticker versions 0.4.4 dated 2018-06-22 and 0.4.5 dated 2019-01-10

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Package hetGP updated to version 1.1.1 with previous version 1.1.0 dated 2018-09-18

Title: Heteroskedastic Gaussian Process Modeling and Design under Replication
Description: Performs Gaussian process regression with heteroskedastic noise following Binois, M., Gramacy, R., Ludkovski, M. (2016) <arXiv:1611.05902>. The input dependent noise is modeled as another Gaussian process. Replicated observations are encouraged as they yield computational savings. Sequential design procedures based on the integrated mean square prediction error and lookahead heuristics are provided, and notably fast update functions when adding new observations.
Author: Mickael Binois, Robert B. Gramacy
Maintainer: Mickael Binois <mbinois@mcs.anl.gov>

Diff between hetGP versions 1.1.0 dated 2018-09-18 and 1.1.1 dated 2019-01-10

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Package dlsem updated to version 2.4.1 with previous version 2.4 dated 2018-08-08

Title: Distributed-Lag Linear Structural Equation Models
Description: Inference functionalities for distributed-lag linear structural equation models (DLSEMs). DLSEMs are Markovian structural causal models where each factor of the joint probability distribution is a distributed-lag linear regression model (Magrini, 2018) <doi:10.2478/bile-2018-0012>. DLSEMs account for temporal delays in the dependence relationships among the variables and allow to perform dynamic causal inference by assessing causal effects at different time lags. Endpoint-constrained quadratic, quadratic decreasing and gamma lag shapes are available.
Author: Alessandro Magrini
Maintainer: Alessandro Magrini <alessandro.magrini@unifi.it>

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Package NITPicker updated to version 1.0.1 with previous version 1.0.0 dated 2018-06-27

Title: Finds the Best Subset of Points to Sample
Description: Given a few examples of experiments over a time (or spatial) course, 'NITPicker' selects a subset of points to sample in follow-up experiments, which would (i) best distinguish between the experimental conditions and the control condition (ii) best distinguish between two models of how the experimental condition might differ from the control (iii) a combination of the two. Ezer and Keir (2018) <doi:10.1101/301796>.
Author: Daphne Ezer
Maintainer: Daphne Ezer <dezer@turing.ac.uk>

Diff between NITPicker versions 1.0.0 dated 2018-06-27 and 1.0.1 dated 2019-01-10

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Package lessR updated to version 3.8.1 with previous version 3.8.0 dated 2019-01-03

Title: Less Code, More Results
Description: Each function accomplishes the work of several or more standard R functions. For example, two function calls, Read() and CountAll(), read the data and generate summary statistics for all variables in the data frame, plus histograms and bar charts as appropriate. Other functions provide for descriptive statistics, a comprehensive regression analysis, analysis of variance and t-test, plotting including the introduced here Violin/Box/Scatter plot for a numerical variable, bar chart, histogram, box plot, density curves, calibrated power curve, reading multiple data formats with the same function call, variable labels, color themes, Trellis graphics and a built-in help system. Also includes a confirmatory factor analysis of multiple indicator measurement models, pedagogical routines for data simulation such as for the Central Limit Theorem, and generation of R markdown instructions for interpretative output.
Author: David W. Gerbing, The School of Business, Portland State University
Maintainer: David W. Gerbing <gerbing@pdx.edu>

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Package curl updated to version 3.3 with previous version 3.2 dated 2018-03-28

Title: A Modern and Flexible Web Client for R
Description: The curl() and curl_download() functions provide highly configurable drop-in replacements for base url() and download.file() with better performance, support for encryption (https, ftps), gzip compression, authentication, and other 'libcurl' goodies. The core of the package implements a framework for performing fully customized requests where data can be processed either in memory, on disk, or streaming via the callback or connection interfaces. Some knowledge of 'libcurl' is recommended; for a more-user-friendly web client see the 'httr' package which builds on this package with http specific tools and logic.
Author: Jeroen Ooms [aut, cre] (<https://orcid.org/0000-0002-4035-0289>), Hadley Wickham [ctb], RStudio [cph]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

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Package GA updated to version 3.2 with previous version 3.1.1 dated 2018-05-11

Title: Genetic Algorithms
Description: Flexible general-purpose toolbox implementing genetic algorithms (GAs) for stochastic optimisation. Binary, real-valued, and permutation representations are available to optimize a fitness function, i.e. a function provided by users depending on their objective function. Several genetic operators are available and can be combined to explore the best settings for the current task. Furthermore, users can define new genetic operators and easily evaluate their performances. Local search using general-purpose optimisation algorithms can be applied stochastically to exploit interesting regions. GAs can be run sequentially or in parallel, using an explicit master-slave parallelisation or a coarse-grain islands approach.
Author: Luca Scrucca [aut, cre] (<https://orcid.org/0000-0003-3826-0484>)
Maintainer: Luca Scrucca <luca.scrucca@unipg.it>

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Package rmdformats updated to version 0.3.4 with previous version 0.3.3 dated 2017-05-18

Title: HTML Output Formats and Templates for 'rmarkdown' Documents
Description: HTML formats and templates for 'rmarkdown' documents, with some extra features such as automatic table of contents, lightboxed figures, dynamic crosstab helper.
Author: Julien Barnier [aut, cre]
Maintainer: Julien Barnier <julien.barnier@ens-lyon.fr>

Diff between rmdformats versions 0.3.3 dated 2017-05-18 and 0.3.4 dated 2019-01-10

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Package hansard updated to version 0.6.3 with previous version 0.6.0 dated 2018-03-02

Title: Provides Easy Downloading Capabilities for the UK Parliament API
Description: Provides functions to download data from the <http://www.data.parliament.uk/> APIs. Because of the structure of the API, there is a named function for each type of available data for ease of use, as well as some functions designed to retrieve specific pieces of commonly used data. Functions for each new API will be added as and when they become available.
Author: Evan Odell [aut, cre] (<https://orcid.org/0000-0003-1845-808X>)
Maintainer: Evan Odell <evanodell91@gmail.com>

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Package rdbnomics updated to version 0.4.4 with previous version 0.4.3 dated 2018-11-30

Title: Download DBnomics Data
Description: R access to hundreds of millions data series from DBnomics API (<https://db.nomics.world/>).
Author: Thomas Brand [aut], Sebastien Galais [cre, ctb]
Maintainer: Sebastien Galais <Sebastien.GALAIS@banque-france.fr>

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Package QuantumOps updated to version 2.1 with previous version 2.0 dated 2018-12-15

Title: Performs Common Linear Algebra Operations Used in Quantum Computing
Description: Contains basic structures and operations used frequently in quantum computing. Intended to be a convenient tool to help in practicing the linear algebra involved in quantum operations. Has functionality for the creation of arbitrarily sized kets, bras, matrices and implements quantum gates, inner products, and tensor products. Contains all commonly used quantum gates and the Quantum Fourier Transform developed by Shor (1999). Implements modular arithmetic commonly found in quantum algorithms and can convert functions into equivalent quantum gates.
Author: Salonik Resch
Maintainer: Salonik Resch <resc0059@umn.edu>

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Package TableToLongForm updated to version 1.3.2 with previous version 1.3.1 dated 2014-08-21

Title: Automatically Convert Hierarchical for-Human Tables to Machine-Readable LongForm Dataframes
Description: A wrapper to a set of algorithms designed to recognise positional cues present in hierarchical for-human Tables (which would normally be interpreted visually by the human brain) to decompose, then reconstruct the data into machine-readable LongForm Dataframes.
Author: Jimmy Oh [aut, cre]
Maintainer: Jimmy Oh <joh024@aucklanduni.ac.nz>

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Package BoltzMM updated to version 0.1.3 with previous version 0.1.1 dated 2018-03-26

Title: Boltzmann Machines with MM Algorithms
Description: Provides probability computation, data generation, and model estimation for fully-visible Boltzmann machines. It follows the methods described in Nguyen and Wood (2016a) <doi:10.1162/NECO_a_00813> and Nguyen and Wood (2016b) <doi:10.1109/TNNLS.2015.2425898>.
Author: Andrew Thomas Jones, Hien Duy Nguyen, and Jessica Juanita Bagnall
Maintainer: Andrew Thomas Jones <andrewthomasjones@gmail.com>

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Package tidypredict updated to version 0.3.0 with previous version 0.2.1 dated 2018-12-20

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(), ranger() and earth() models.
Author: Edgar Ruiz [aut, cre]
Maintainer: Edgar Ruiz <edgar@rstudio.com>

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Package ClinicalTrialSummary (with last version 1.0.1) was removed from CRAN

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

2019-01-09 1.0.1
2019-01-02 1.0.0
2017-11-07 0.1.0

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