Thu, 12 Jul 2018

Package CorShrink updated to version 0.1-6 with previous version 0.1-5 dated 2018-04-10

Title: Adaptive Shrinkage of Correlation and Covariance Matrices
Description: Performs adaptive shrinkage of correlation and covariance matrices using a mixture model prior over the Fisher z-transformation of the correlations. It allows separate shrinkage intensity for each cell of the correlation matrix. Can also we flexibly extended to shrinking correlation like quantities such as cosine similarities in word2vec models and to partial correlations in conditional graph estimation. For details on methods, refer to Stephens (2017) "False discovery rates: a new deal", <DOI:10.1093/biostatistics/kxw041>.
Author: c(person("Kushal","Dey",role=c("aut","cre"), email="kkdey@uchicago.edu"), person("Matthew","Stephens",role="aut"), person("Peter","Carbonetto",role="ctb"))
Maintainer: Kushal Dey <kkdey@uchicago.edu>

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Package rdpower updated to version 0.2 with previous version 0.1 dated 2018-03-23

Title: Power Calculations for RD Designs
Description: The regression discontinuity (RD) design is a popular quasi-experimental design for causal inference and policy evaluation. The 'rdpower' package provides tools to perform power and sample size calculations in RD designs: rdpower() calculates the power of an RD design and rdsampsi() calculates the required sample size to achieve a desired power. See Cattaneo, Titiunik and Vazquez-Bare (2018) <https://sites.google.com/site/rdpackages/rdpower/Cattaneo-Titiunik-VazquezBare_2018_Stata.pdf> for further methodological details.
Author: Matias D. Cattaneo, Rocio Titiunik, Gonzalo Vazquez-Bare
Maintainer: Gonzalo Vazquez-Bare <gvazquez@umich.edu>

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Package Rlabkey updated to version 2.2.2 with previous version 2.2.1 dated 2018-03-13

Title: Data Exchange Between R and 'LabKey' Server
Description: The 'LabKey' client library for R makes it easy for R users to load live data from a 'LabKey' Server, <http://www.labkey.com/>, into the R environment for analysis, provided users have permissions to read the data. It also enables R users to insert, update, and delete records stored on a 'LabKey' Server, provided they have appropriate permissions to do so.
Author: Peter Hussey
Maintainer: Cory Nathe <cnathe@labkey.com>

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New package xdcclarge with initial version 0.1.0
Package: xdcclarge
Type: Package
Title: Estimating a (c)DCC-GARCH Model in Large Dimensions
Version: 0.1.0
Authors@R: c( person("Kei","Nakagawa",email="kei.nak.0315@gmail.com",role=c("aut","cre"),comment = c(ORCID = "0000-0001-5046-8128")), person("Mitsuyoshi","Imamura",email="ic140tg528@gmail.com",role=c("aut")) )
Description: Functions for Estimating a (c)DCC-GARCH Model in large dimensions based on a publication by Engle et,al (2017) <doi:10.1080/07350015.2017.1345683> and Nakagawa et,al (2018) <doi:10.3390/ijfs6020052>. This estimation method is consist of composite likelihood method by Pakel et al. (2014) <http://paneldataconference2015.ceu.hu/Program/Cavit-Pakel.pdf> and (Non-)linear shrinkage estimation of covariance matrices by Ledoit and Wolf (2004,2015,2016). (<doi:10.1016/S0047-259X(03)00096-4>, <doi:10.1214/12-AOS989>, <doi:10.1016/j.jmva.2015.04.006>).
License: GPL (>= 2)
Author: Kei Nakagawa [aut, cre] (<https://orcid.org/0000-0001-5046-8128>), Mitsuyoshi Imamura [aut]
Maintainer: Kei Nakagawa <kei.nak.0315@gmail.com>
LazyData: TRUE
Imports: stats, Rcpp(>= 0.10.6), nlshrink
Depends: R(>= 3.0.2)
LinkingTo: Rcpp(>= 0.10.6),RcppArmadillo(>= 0.2.34)
Suggests: rugarch(>= 1.0.0)
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-07-12 12:07:16 UTC; kei
Repository: CRAN
Date/Publication: 2018-07-12 18:50:03 UTC

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Package qGaussian updated to version 0.1.8 with previous version 0.1.6 dated 2017-09-28

Title: The q-Gaussian Distribution
Description: Density, distribution function, quantile function and random generation for the q-gaussian distribution with parameters mu and sig.
Author: Emerson Luis de Santa Helena <elsh@ufs.br> Wagner Santos de Lima <wagnersantos.ufs@hotmail.com>
Maintainer: Wagner Santos de Lima <wagnersantos.ufs@hotmail.com>

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Package rdrobust updated to version 0.99.3 with previous version 0.99.2 dated 2018-07-09

Title: Robust Data-Driven Statistical Inference in Regression-Discontinuity Designs
Description: Regression-discontinuity (RD) designs are quasi-experimental research designs popular in social, behavioral and natural sciences. The RD design is usually employed to study the (local) causal effect of a treatment, intervention or policy. This package provides tools for data-driven graphical and analytical statistical inference in RD designs: rdrobust() to construct local-polynomial point estimators and robust confidence intervals for average treatment effects at the cutoff in Sharp, Fuzzy and Kink RD settings, rdbwselect() to perform bandwidth selection for the different procedures implemented, and rdplot() to conduct exploratory data analysis (RD plots).
Author: Sebastian Calonico <scalonico@bus.miami.edu>, Matias D. Cattaneo <cattaneo@umich.edu>, Max H. Farrell <max.farrell@chicagobooth.edu>, Rocio Titiunik <titiunik@umich.edu>
Maintainer: Sebastian Calonico <scalonico@bus.miami.edu>

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Package washeR updated to version 0.1.2 with previous version 0.1.0 dated 2018-07-11

Title: Time Series Outlier Detection
Description: Time series outlier detection by mean of non parametric test. Outlier detection regarding two methodologies: single time series variability (a vector) and grouped similar time series (a data frame). Andrea Venturini(2011) Statistica-Universita' Bologna, Vol.71, pp.329-344.
Author: Andrea Venturini
Maintainer: Andrea Venturini <andrea.venturini@bancaditalia.it>

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Package irace updated to version 3.1 with previous version 3.0 dated 2018-07-05

Title: Iterated Racing for Automatic Algorithm Configuration
Description: Iterated race is an extension of the Iterated F-race method for the automatic configuration of optimization algorithms, that is, (offline) tuning their parameters by finding the most appropriate settings given a set of instances of an optimization problem.
Author: Manuel López-Ibáñez [aut, cre] (<https://orcid.org/0000-0001-9974-1295>), Jérémie Dubois-Lacoste [aut], Leslie Pérez Cáceres [aut], Thomas Stützle [aut], Mauro Birattari [aut], Eric Yuan [ctb], Prasanna Balaprakash [ctb]
Maintainer: Manuel López-Ibáñez <manuel.lopez-ibanez@manchester.ac.uk>

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Package gambin updated to version 2.4.0 with previous version 2.3.0 dated 2018-02-18

Title: Fit the Gambin Model to Species Abundance Distributions
Description: Fits unimodal and multimodal gambin distributions to species-abundance distributions from ecological data, as in in Matthews et al. (2014) <DOI:10.1111/ecog.00861>. 'gambin' is short for 'gamma-binomial'. The main function is fit_abundances(), which estimates the 'alpha' parameter(s) of the gambin distribution using maximum likelihood. Functions are also provided to generate the gambin distribution and for calculating likelihood statistics.
Author: Thomas Matthews [aut, cre], Michael Krabbe Borregaard [aut], Karl Ugland [aut], Colin Gillespie [aut]
Maintainer: Thomas Matthews <txm676@gmail.com>

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Package dkanr updated to version 0.1.2 with previous version 0.1.1 dated 2018-04-30

Title: Client for the 'DKAN' API
Description: Provides functions to facilitate access to the 'DKAN' API (<https://dkan.readthedocs.io/en/latest/apis/index.html>), including the 'DKAN' REST API (metadata), and the 'DKAN' datastore API (data). Includes functions to list, create, retrieve, update, and delete datasets and resources nodes. It also includes functions to search and retrieve data from the 'DKAN' datastore.
Author: Tony Fujs [aut, cre], Meera Desai [aut], Karthik Ramanathan [aut]
Maintainer: Tony Fujs <tonyfujs@gmail.com>

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Package spass updated to version 1.2 with previous version 1.1 dated 2017-11-02

Title: Study Planning and Adaptation of Sample Size
Description: Sample size estimation and blinded sample size reestimation in Adaptive Study Design.
Author: T. Asendorf, R. Gera, S. Islam, M. Harden and M. Placzek
Maintainer: Marius Placzek <marius.placzek@med.uni-goettingen.de>

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Package penalized updated to version 0.9-51 with previous version 0.9-50.1 dated 2018-06-30

Title: L1 (Lasso and Fused Lasso) and L2 (Ridge) Penalized Estimation in GLMs and in the Cox Model
Description: Fitting possibly high dimensional penalized regression models. The penalty structure can be any combination of an L1 penalty (lasso and fused lasso), an L2 penalty (ridge) and a positivity constraint on the regression coefficients. The supported regression models are linear, logistic and Poisson regression and the Cox Proportional Hazards model. Cross-validation routines allow optimization of the tuning parameters.
Author: Jelle Goeman, Rosa Meijer, Nimisha Chaturvedi, Matthew Lueder
Maintainer: ORPHANED

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Package sarima updated to version 0.7.3 with previous version 0.7.2 dated 2018-07-09

Title: Simulation and Prediction with Seasonal ARIMA Models
Description: Functions, classes and methods for time series modelling with ARIMA and related models. The aim of the package is to provide consistent interface for the user. For example, a single function autocorrelations() computes various kinds of theoretical and sample autocorrelations. This is work in progress, see the documentation and vignettes for the current functionality. Function sarima() fits extended multiplicative seasonal ARIMA models with trends, exogenous variables and arbitrary roots on the unit circle, which can be fixed or estimated.
Author: Georgi N. Boshnakov [aut, cre], Jamie Halliday [ctb]
Maintainer: Georgi N. Boshnakov <georgi.boshnakov@manchester.ac.uk>

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Package optmatch updated to version 0.9-10 with previous version 0.9-9 dated 2018-05-14

Title: Functions for Optimal Matching
Description: Distance based bipartite matching using the RELAX-IV minimum cost flow solver, oriented to matching of treatment and control groups in observational studies. Routines are provided to generate distances from generalised linear models (propensity score matching), formulas giving variables on which to limit matched distances, stratified or exact matching directives, or calipers, alone or in combination.
Author: Ben B. Hansen <ben.hansen@umich.edu>, Mark Fredrickson <mark.m.fredrickson@gmail.com>, Josh Buckner, Josh Errickson, and Peter Solenberger, with embedded Fortran code due to Dimitri P. Bertsekas <dimitrib@mit.edu> and Paul Tseng
Maintainer: Mark M. Fredrickson <mark.m.fredrickson@gmail.com>

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Package multifluo updated to version 1.1 with previous version 1.0 dated 2018-01-24

Title: Dealing with Several Images of a Same Object Constituted of Different Zones
Description: Deals with several images of a same object, constituted of different zones. Each image constitutes a variable for a given pixel. The user can interactively select different zones of an image. Then, multivariate analysis (PCA) can be run in order to characterize the different selected zones, according to the different images. Hotelling (Hotelling, 1931, <doi:10.1214/aoms/1177732979>) and Srivastava (Srivastava, 2009, <doi:10.1016/j.jmva.2006.11.002>) tests can be run to detect multivariate differences between the zones.
Author: Caroline Peltier
Maintainer: Caroline Peltier <caroline.peltier@agrosupdijon.fr>

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Package ggspatial updated to version 1.0.1 with previous version 0.2.1 dated 2017-04-02

Title: Spatial Data Framework for ggplot2
Description: Spatial data plus the power of the ggplot2 framework means easier mapping when input data are already in the form of spatial objects.
Author: Dewey Dunnington [aut, cre], Brent Thorne [ctb]
Maintainer: Dewey Dunnington <dewey@fishandwhistle.net>

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Package diseasemapping updated to version 1.4.6 with previous version 1.4.2 dated 2016-09-20

Title: Modelling Spatial Variation in Disease Risk for Areal Data
Description: Formatting of population and case data, calculation of Standardized Incidence Ratios, and fitting the BYM model using INLA.
Author: Patrick Brown <patrick.brown@utoronto.ca>, Lutong Zhou
Maintainer: Patrick Brown <patrick.brown@utoronto.ca>

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Package sjPlot updated to version 2.5.0 with previous version 2.4.1 dated 2018-02-05

Title: Data Visualization for Statistics in Social Science
Description: Collection of plotting and table output functions for data visualization. Results of various statistical analyses (that are commonly used in social sciences) can be visualized using this package, including simple and cross tabulated frequencies, histograms, box plots, (generalized) linear models, mixed effects models, principal component analysis and correlation matrices, cluster analyses, scatter plots, stacked scales, effects plots of regression models (including interaction terms) and much more. This package supports labelled data.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Carsten Schwemmer [ctb]
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package CAST updated to version 0.2.1 with previous version 0.2.0 dated 2018-05-06

Title: 'caret' Applications for Spatial-Temporal Models
Description: Supporting functionality to run 'caret' with spatial or spatial-temporal data. 'caret' is a frequently used package for model training and prediction using machine learning. This package includes functions to improve spatial-temporal modelling tasks using 'caret'. It prepares data for Leave-Location-Out and Leave-Time-Out cross-validation which are target-oriented validation strategies for spatial-temporal models. To decrease overfitting and improve model performances, the package implements a forward feature selection that selects suitable predictor variables in view to their contribution to the target-oriented performance.
Author: Hanna Meyer [cre, aut], Chris Reudenbach [ctb], Marvin Ludwig [ctb], Thomas Nauss [ctb]
Maintainer: Hanna Meyer <hanna.meyer@geo.uni-marburg.de>

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Package RSSL updated to version 0.7 with previous version 0.6.1 dated 2016-10-06

Title: Implementations of Semi-Supervised Learning Approaches for Classification
Description: A collection of implementations of semi-supervised classifiers and methods to evaluate their performance. The package includes implementations of, among others, Implicitly Constrained Learning, Moment Constrained Learning, the Transductive SVM, Manifold regularization, Maximum Contrastive Pessimistic Likelihood estimation, S4VM and WellSVM.
Author: Jesse Krijthe [aut, cre]
Maintainer: Jesse Krijthe <jkrijthe@gmail.com>

Diff between RSSL versions 0.6.1 dated 2016-10-06 and 0.7 dated 2018-07-12

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 NAMESPACE                                                     |    2 
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 R/LaplacianSVM.R                                              |    8 
 R/NormalBasedClassifier.R                                     |    6 
 R/RSSL.R                                                      |    2 
 R/RcppExports.R                                               |   24 
 R/svmd.R                                                      |   12 
 README.md                                                     |   12 
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 man/MCPLDA.Rd                                                 |    4 
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 man/RSSL.Rd                                                   |    1 
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 man/S4VM.Rd                                                   |    5 
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 man/SVM.Rd                                                    |    4 
 man/SelfLearning.Rd                                           |    4 
 man/TSVM.Rd                                                   |    6 
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 man/WellSVM.Rd                                                |    5 
 man/WellSVM_SSL.Rd                                            |    1 
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 man/clapply.Rd                                                |    1 
 man/cov_ml.Rd                                                 |    1 
 man/decisionvalues-methods.Rd                                 |    7 
 man/df_to_matrices.Rd                                         |    1 
 man/diabetes.Rd                                               |    1 
 man/evaluation-measures.Rd                                    |    4 
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 man/minimaxlda.Rd                                             |    1 
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More information about RSSL at CRAN
Permanent link

New package LipidMS with initial version 0.1.0
Package: LipidMS
Type: Package
Title: Lipid Annotation for LC-MS/MS using Data Independent Acquisition
Version: 0.1.0
Author: M Isabel Alcoriza-Balaguer, J Carlos Garcia-Canaveras
Maintainer: M Isabel Alcoriza-Balaguer <maialba@alumni.uv.es>
Description: Lipid annotation in untargeted liquid chromatography-data independent acquisition-mass spectrometry lipidomics based on fragmentation rules.
Depends: R (>= 2.10), enviPick, methods, CAMERA
License: GPL (>= 2)
LazyData: TRUE
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-07-10 11:59:40 UTC; 73581298C
Repository: CRAN
Date/Publication: 2018-07-12 10:40:03 UTC

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New package gDefrag with initial version 0.1
Package: gDefrag
Type: Package
Title: Graph-Based Landscape De-Fragmentation
Version: 0.1
Date: 2018-05-17
Depends: sp, R (>= 3.0)
Imports: maptools, rgeos, rgdal, igraph, methods
Author: Frederico Mestre, Fernando Ascensao, A. Marcia Barbosa
Maintainer: Frederico Mestre <mestre.frederico@gmail.com>
Description: Provides a set of tools to help the de-fragmentation process. It works by prioritizing the different sections of linear infrastructures (e.g. roads, power-lines) to increase the available amount of a given resource.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2018-07-11 20:09:25 UTC; FMest
Repository: CRAN
Date/Publication: 2018-07-12 10:30:03 UTC

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Package poliscidata updated to version 2.2.0 with previous version 1.2.0 dated 2016-10-24

Title: Datasets and Functions Featured in Pollock and Edwards, An R Companion to Essentials of Political Analysis, Second Edition
Description: Bundles the datasets and functions used in the book by Philip Pollock and Barry Edwards, An R Companion to Essentials of Political Analysis, Second Edition.
Author: Barry Edwards and Philip Pollock
Maintainer: Barry Edwards <barry.edwards@ucf.edu>

Diff between poliscidata versions 1.2.0 dated 2016-10-24 and 2.2.0 dated 2018-07-12

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New package MAGNAMWAR with initial version 2.0.4
Package: MAGNAMWAR
Title: A Pipeline for Meta-Genome Wide Association
Version: 2.0.4
Date: 2018-06-15
Authors@R: c( person("Corinne", "Sexton", role = c("aut"), email="corinsexton@gmail.com"), person("John", "Chaston", role = c("aut", "cre"), email = "john_chaston@byu.edu"), person("Hayden", "Smith", role = "ctb") )
Description: Correlates variation within the meta-genome to target species phenotype variations in meta-genome with association studies. Follows the pipeline described in Chaston, J.M. et al. (2014) <doi:10.1128/mBio.01631-14>.
License: MIT + file LICENSE
LazyData: true
Imports: ape, coxme, doParallel, dplyr, foreach, iterators, lme4, multcomp, parallel, plyr, qqman, survival, seqinr
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Depends: R (>= 3.0)
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-06-16 03:47:53 UTC; coripenrod
Author: Corinne Sexton [aut], John Chaston [aut, cre], Hayden Smith [ctb]
Maintainer: John Chaston <john_chaston@byu.edu>
Repository: CRAN
Date/Publication: 2018-07-12 07:20:17 UTC

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Package generalCorr updated to version 1.1.2 with previous version 1.1.1 dated 2018-01-24

Title: Generalized Correlations and Initial Causal Path
Description: Since causal paths from data are important for all sciences, the package provides sophisticated functions. The idea is simply that if X causes Y (path: X to Y) then non-deterministic variation in X is more "original or independent" than similar variation in Y. Since causal variables are also exogenous in a model, we provide new exogeneity tests. We compare two flipped kernel regressions: X=f(Y, Z) and Y=g(X,Z), where Z are control variables. Our first two criteria compare absolute cross products of regressor values and residuals (Cr1) and absolute residuals (Cr2), are both quantified by stochastic dominance of four orders (SD1 to SD4). Our third criterion (Cr3) expects X to be better able to predict Y than the other way around using generalized partial correlation If |r*(x|y,z)|> |r*(y|x,z)| it suggests that y is more likely the "kernel cause" of x. The usual partial correlations are generalized with a new non-symmetric matrix developed here. Partial correlations help asses effect of x on y after removing the effect of a set of variables. The package provides additional tools for causal assessment, for printing the causal directions in a clear, comprehensive compact summary form, for matrix algebra, for "outlier detection", and for numerical integration by the trapezoidal rule, stochastic dominance, etc. The package has functions for bootstrap-based statistical inference.
Author: Prof. H. D. Vinod, Fordham University, NY.
Maintainer: H. D. Vinod <vinod@fordham.edu>

Diff between generalCorr versions 1.1.1 dated 2018-01-24 and 1.1.2 dated 2018-07-12

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Package estimatr updated to version 0.10.0 with previous version 0.8.0 dated 2018-06-02

Title: Fast Estimators for Design-Based Inference
Description: Fast procedures for small set of commonly-used, design-appropriate estimators with robust standard errors and confidence intervals. Includes estimators for linear regression, instrumental variables regression, difference-in-means, Horvitz-Thompson estimation, and regression improving precision of experimental estimates by interacting treatment with centered pre-treatment covariates introduced by Lin (2013) <doi:10.1214/12-AOAS583>.
Author: Graeme Blair [aut, cre], Jasper Cooper [aut], Alexander Coppock [aut], Macartan Humphreys [aut], Luke Sonnet [aut], Neal Fultz [ctb]
Maintainer: Graeme Blair <graeme.blair@ucla.edu>

Diff between estimatr versions 0.8.0 dated 2018-06-02 and 0.10.0 dated 2018-07-12

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Package descomponer updated to version 1.5 with previous version 1.4 dated 2017-08-21

Title: Seasonal Adjustment by Frequency Analysis
Description: Decompose a time series into seasonal, trend and irregular components using transformations to amplitude-frequency domain.
Author: Francisco Parra <parra_fj@cantabria.es>
Maintainer: Francisco Parra <parra_fj@cantabria.es>

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Package xwf updated to version 0.2-2 with previous version 0.2-1 dated 2018-01-31

Title: Extrema-Weighted Feature Extraction
Description: Extrema-weighted feature extraction for varying length functional data. Functional data analysis method that performs dimensionality reduction based on predefined features and allows for quantile weighting. Method implemented as presented in Van den Boom et al. (2018) <doi:10.1093/bioinformatics/bty120>.
Author: Willem van den Boom [aut, cre]
Maintainer: Willem van den Boom <willem@wvdboom.nl>

Diff between xwf versions 0.2-1 dated 2018-01-31 and 0.2-2 dated 2018-07-12

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Package JGR updated to version 1.8-6 with previous version 1.8-4 dated 2017-09-24

Title: Java GUI for R
Description: Java GUI for R - cross-platform, universal and unified Graphical User Interface for R. For full functionality on Windows and Mac OS X JGR requires a start application which depends on your OS.
Author: Markus Helbig <info@markushelbig.de>, Simon Urbanek, Ian Fellows
Maintainer: Markus Helbig <info@markushelbig.de>

Diff between JGR versions 1.8-4 dated 2017-09-24 and 1.8-6 dated 2018-07-12

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Package rpart.plot updated to version 3.0.0 with previous version 2.2.0 dated 2018-05-19

Title: Plot 'rpart' Models: An Enhanced Version of 'plot.rpart'
Description: Plot 'rpart' models. Extends plot.rpart() and text.rpart() in the 'rpart' package.
Author: Stephen Milborrow
Maintainer: Stephen Milborrow <milbo@sonic.net>

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Package gemlog updated to version 0.30 with previous version 0.26 dated 2017-10-05

Title: File Conversion for 'Gem Infrasound Logger'
Description: Reads data files from the 'Gem infrasound logger' for analysis and converts to segy format (which is convenient for reading with traditional seismic analysis software). The Gem infrasound logger is an in-development low-cost, lightweight, low-power instrument for recording infrasound in field campaigns; email the maintainer for more information.
Author: Jake Anderson
Maintainer: Jake Anderson <ajakef@gmail.com>

Diff between gemlog versions 0.26 dated 2017-10-05 and 0.30 dated 2018-07-12

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More information about gemlog at CRAN
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Package compound.Cox updated to version 3.13 with previous version 3.12 dated 2018-07-02

Title: Univariate Feature Selection and Compound Covariate for Predicting Survival
Description: Univariate feature selection and compound covariate methods under the Cox model with high-dimensional features (e.g., gene expressions). Available are survival data for non-small-cell lung cancer patients with gene expressions (Chen et al 2007 New Engl J Med) <DOI:10.1056/NEJMoa060096>, statistical methods in Emura et al (2012 PLoS ONE) <DOI:10.1371/journal.pone.0047627>, Emura & Chen (2016 Stat Methods Med Res) <DOI:10.1177/0962280214533378>, and Emura et al. (2018-)<submitted>. Algorithms for generating correlated gene expressions are also available.
Author: Takeshi Emura, Hsuan-Yu Chen, Shigeyuki Matsui, Yi-Hau Chen
Maintainer: Takeshi Emura <takeshiemura@gmail.com>

Diff between compound.Cox versions 3.12 dated 2018-07-02 and 3.13 dated 2018-07-12

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More information about compound.Cox at CRAN
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