Fri, 16 Jun 2017

Package OpenMx updated to version 2.7.12 with previous version 2.7.11 dated 2017-05-05

Title: Extended Structural Equation Modelling
Description: Facilitates treatment of statistical model specifications as things that can be generated and manipulated programmatically. Structural equation models may be specified with reticular action model matrices or paths, linear structural relations matrices or paths, or directly in matrix algebra. Fit functions include full information maximum likelihood, maximum likelihood, and weighted least squares. Example models include confirmatory factor, multiple group, mixture distribution, categorical threshold, modern test theory, differential equations, state space, and many others.
Author: Steven M. Boker [aut], Michael C. Neale [aut], Hermine H. Maes [aut], Michael J. Wilde [ctb], Michael Spiegel [aut], Timothy R. Brick [aut], Ryne Estabrook [aut], Timothy C. Bates [aut], Paras Mehta [ctb], Timo von Oertzen [ctb], Ross J. Gore [aut], Michael D. Hunter [aut], Daniel C. Hackett [ctb], Julian Karch [ctb], Andreas M. Brandmaier [ctb], Joshua N. Pritikin [aut, cre], Mahsa Zahery [aut], Robert M. Kirkpatrick [aut], Yang Wang [ctb], Charles Driver [ctb], Massachusetts Institute of Technology [cph], S. G. Johnson [cph], Association for Computing Machinery [cph], Dieter Kraft [cph], Stefan Wilhelm [cph], Manjunath B G [cph]
Maintainer: Joshua N. Pritikin <jpritikin@pobox.com>

Diff between OpenMx versions 2.7.11 dated 2017-05-05 and 2.7.12 dated 2017-06-16

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Package interp updated to version 1.0-28 with previous version 1.0-27 dated 2017-06-16

Title: Interpolation Methods
Description: Bivariate data interpolation on regular and irregular grids, either linear or using splines are the main part of this package. It is intended to provide FOSS replacement functions for the ACM licensed akima::interp and tripack::tri.mesh functions. Currently the piecewise linear interpolation part of akima::interp (and also akima::interpp) is implemented in interp::interp, this corresponds to the call akima::interp(..., linear=TRUE) which is the default setting and covers most of akima::interp use cases in depending packages. A re-implementation of Akimas spline interpolation (akima::interp(..., linear=FALSE)) is currently under development and will complete this package in a later version. Estimators for partial derivatives are already available, these are a prerequisite for the spline interpolation. The basic part is currently a GPLed triangulation algorithm (sweep hull algorithm by David Sinclair) providing the starting point for the piecewise linear interpolator. As side effect this algorithm is also used to provide replacements for the basic functions of the tripack package which also suffer from the ACM restrictions. All functions are designed to be backward compatible with their akima / tripack counterparts.
Author: Albrecht Gebhardt [aut, cre, cph] (...), Roger Bivand [aut], David Sinclair [aut, cph]
Maintainer: Albrecht Gebhardt <albrecht.gebhardt@aau.at>

Diff between interp versions 1.0-27 dated 2017-06-16 and 1.0-28 dated 2017-06-16

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Package dynr updated to version 0.1.11-2 with previous version 0.1.10-10 dated 2017-05-21

Title: Dynamic Modeling in R
Description: Intensive longitudinal data have become increasingly prevalent in various scientific disciplines. Many such data sets are noisy, multivariate, and multi-subject in nature. The change functions may also be continuous, or continuous but interspersed with periods of discontinuities (i.e., showing regime switches). The package 'dynr' (Dynamic Modeling in R) is an R package that implements a set of computationally efficient algorithms for handling a broad class of linear and nonlinear discrete- and continuous-time models with regime-switching properties under the constraint of linear Gaussian measurement functions. The discrete-time models can generally take on the form of a state- space or difference equation model. The continuous-time models are generally expressed as a set of ordinary or stochastic differential equations. All estimation and computations are performed in C, but users are provided with the option to specify the model of interest via a set of simple and easy-to-learn model specification functions in R. Model fitting can be performed using single- subject time series data or multiple-subject longitudinal data.
Author: Lu Ou [aut], Michael D. Hunter [aut, cre], Sy-Miin Chow [aut]
Maintainer: Michael D. Hunter <mhunter.ou@gmail.com>

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Package difNLR updated to version 1.0.3 with previous version 1.0.2 dated 2017-06-06

Title: Detection of Differential Item Functioning (DIF) and Differential Distractor Functioning (DDF) by Non-Linear Regression Models
Description: Detection of DIF among dichotomously scored items and DDF among unscored items with non-linear regression procedures based on generalized logistic regression models.
Author: Adela Drabinova [aut, cre], Patricia Martinkova [aut], Karel Zvara [aut]
Maintainer: Adela Drabinova <adela.drabinova@gmail.com>

Diff between difNLR versions 1.0.2 dated 2017-06-06 and 1.0.3 dated 2017-06-16

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Package wildcard updated to version 1.0.1 with previous version 1.0.0 dated 2017-05-21

Title: Templates for Data Frames
Description: Generate data frames from templates.
Author: William Michael Landau [aut, cre]
Maintainer: William Michael Landau <will.landau@gmail.com>

Diff between wildcard versions 1.0.0 dated 2017-05-21 and 1.0.1 dated 2017-06-16

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Package qrmtools updated to version 0.0-7 with previous version 0.0-6 dated 2016-05-29

Title: Tools for Quantitative Risk Management
Description: Functions and data sets for reproducing selected results from the book "Quantitative Risk Management: Concepts, Techniques and Tools". Furthermore, new developments and auxiliary functions for Quantitative Risk Management practice.
Author: Marius Hofert [aut, cre], Kurt Hornik [aut], Alexander J. McNeil [aut]
Maintainer: Marius Hofert <marius.hofert@uwaterloo.ca>

Diff between qrmtools versions 0.0-6 dated 2016-05-29 and 0.0-7 dated 2017-06-16

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Package tidyRSS updated to version 1.2.1 with previous version 1.2.0 dated 2017-06-07

Title: Tidy RSS for R
Description: With the objective of including data from RSS feeds into your analysis, 'tidyRSS' parses RSS and Atom XML feeds and returns a tidy data frame.
Author: Robert Myles McDonnell
Maintainer: Robert Myles McDonnell <robertmylesmcdonnell@gmail.com>

Diff between tidyRSS versions 1.2.0 dated 2017-06-07 and 1.2.1 dated 2017-06-16

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New package preference with initial version 0.1.0
Package: preference
Type: Package
Title: 2-Stage Clinical Trial Design and Analysis
Version: 0.1.0
Date: 2017-06-14
Authors@R: c(person(given="Briana", family="Cameron", email="briana.cameron@yale.edu", role=c("aut", "cph", "cre")), person(given="Denise", family="Esserman", email="denise.esserman@yale.edu", role="ctb"), person(given="Michael",family="Kane",email="michael.kane@yale.edu",role="ctb"))
URL: https://github.com/kaneplusplus/
BugReports: https://github.com/kaneplusplus/preference/issues
Description: Design and analyze two-stage randomized trials with a continuous outcome measure. The package contains functions to compute the required sample size needed to detect a given preference, treatment, and selection effect; alternatively, the package contains functions that can report the study power given a fixed sample size. Finally, analysis functions are provided to test each effect using either summary data (i.e. means, variances) or raw study data.
License: LGPL-2
Suggests: knitr, covr, testthat, ggplot2, devtools
VignetteBuilder: knitr
RoxygenNote: 6.0.1
LazyData: true
NeedsCompilation: no
Packaged: 2017-06-16 13:08:55 UTC; bricameron
Author: Briana Cameron [aut, cph, cre], Denise Esserman [ctb], Michael Kane [ctb]
Maintainer: Briana Cameron <briana.cameron@yale.edu>
Repository: CRAN
Date/Publication: 2017-06-16 19:43:21 UTC

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New package momentuHMM with initial version 1.0.0
Package: momentuHMM
Type: Package
Title: Maximum Likelihood Analysis of Animal Movement Behavior Using Multivariate Hidden Markov Models
Version: 1.0.0
Date: 2017-06-13
Depends: R (>= 2.10), splines, splines2
Author: Brett McClintock, Theo Michelot, Roland Langrock, Toby Patterson, Eric Rexstad
Maintainer: Brett McClintock <brett.mcclintock@noaa.gov>
Description: Extended tools for analyzing telemetry data using (multivariate) hidden Markov models. These include processing of tracking data, fitting HMMs to location and auxiliary biotelemetry or environmental data, multiple imputation for incorporating location measurement error and missing data, visualization of data and fitted model, decoding of the state process...
License: GPL-3
LazyData: TRUE
Imports: Rcpp, doParallel, foreach, numDeriv, CircStats, crawl, ggmap, ggplot2, mitools, moveHMM, raster, argosfilter, car, mvtnorm, boot, sp, MASS, Brobdingnag, gstat, conicfit, nleqslv, survival, qdapRegex
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, setRNG
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2017-06-16 08:08:05 UTC; theo
Repository: CRAN
Date/Publication: 2017-06-16 20:02:54 UTC

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New package MARX with initial version 0.1
Package: MARX
Title: Simulation, Estimation and Selection of MARX Models
Version: 0.1
Date: 2017-06-16
Authors@R: c(person("Sean", "Telg", email = "j.telg@maastrichtuniversity.nl", role = c("aut","cre","cph")), person("Alain", "Hecq", email = "a.hecq@maastrichtuniversity.nl", role = "ctb"), person("Lenard", "Lieb", email = "l.lieb@maastrichtuniversity.nl", role = "ctb"))
Author: Sean Telg [aut, cre, cph], Alain Hecq [ctb], Lenard Lieb [ctb]
Maintainer: Sean Telg <j.telg@maastrichtuniversity.nl>
Description: Simulate, estimate (by t-MLE) and select mixed causal-noncausal autoregressive models with possibly exogenous regressors, using methods proposed in Lanne and Saikkonen (2011) <doi:10.2202/1941-1928.1080> and Hecq et al. (2016) <doi:10.15609/annaeconstat2009.123-124.0307>.
Imports: matlab, fBasics, tseries, stabledist
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 5.0.1
Packaged: 2017-06-16 09:35:36 UTC; Sean
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2017-06-16 20:10:49 UTC

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New package CityWaterBalance with initial version 0.1.0
Package: CityWaterBalance
Title: Track Flows of Water Through an Urban System
Version: 0.1.0
Authors@R: person("Laura", "Erban", email = "erban.laura@epa.gov", role = c("aut", "cre"))
Description: Retrieves data and estimates unmeasured flows of water through the urban network. Any city may be modeled with preassembled data, but data for US cities can be gathered via web services using this package and dependencies 'geoknife' and 'dataRetrieval'.
Depends: R (>= 3.0.0)
Imports: dataRetrieval, dplyr, EcoHydRology, geoknife, graphics, grDevices, lubridate, reshape2, stats, tgp, utils, xts, zoo
License: CC0
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-06-16 12:35:07 UTC; lerban
Author: Laura Erban [aut, cre]
Maintainer: Laura Erban <erban.laura@epa.gov>
Repository: CRAN
Date/Publication: 2017-06-16 19:45:28 UTC

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New package charlatan with initial version 0.1.0
Package: charlatan
Type: Package
Title: Make Fake Data
Description: Make fake data, supporting addresses, person names, dates, times, colors, coordinates, currencies, digital object identifiers ('DOIs'), jobs, phone numbers, 'DNA' sequences, doubles and integers from distributions and within a range.
Version: 0.1.0
Authors@R: c( person("Scott", "Chamberlain", role = c("aut", "cre"), email = "myrmecocystus+r@gmail.com"), person("Brooke", "Anderson", role = "ctb", comment = "Brooke Anderson reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/94"), person("Tristan", "Mahr", role = "ctb", comment = "Tristan Mahr reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/94") )
License: MIT + file LICENSE
URL: https://github.com/ropensci/charlatan
BugReports: https://github.com/ropensci/charlatan/issues
LazyData: true
Encoding: UTF-8
VignetteBuilder: knitr
Imports: R6 (>= 2.2.0), tibble (>= 1.2), whisker
Suggests: roxygen2 (>= 6.0.1), testthat, knitr, rmarkdown
RoxygenNote: 6.0.1
Collate: 'base-provider.R' 'datetime-provider.R' 'address-provider.R' 'available_locales.R' 'charlatan-package.R' 'charlatan_settings.R' 'color-provider-en_US.R' 'color-provider-uk_UA.R' 'color-provider.R' 'color.R' 'company-provider-bg_BG.R' 'company-provider-cs_CZ.R' 'company-provider-de_DE.R' 'company-provider-en_US.R' 'company-provider-es_MX.R' 'company-provider-fa_IR.R' 'company-provider-fr_FR.R' 'company-provider-hr_HR.R' 'company-provider-it_IT.R' 'company-provider.R' 'company.R' 'coordinate-provider.R' 'coordinates.R' 'credit_card-provider.R' 'credit_card.R' 'currency-provider.R' 'currency.R' 'date_time.R' 'doi-provider.R' 'doi.R' 'fraudster.R' 'generate.R' 'job.R' 'jobs-provider-en_US.R' 'jobs-provider-fa_IR.R' 'jobs-provider-fr_CH.R' 'jobs-provider-fr_FR.R' 'jobs-provider-hr_HR.R' 'jobs-provider-pl_PL.R' 'jobs-provider-ru_RU.R' 'jobs-provider-uk_UA.R' 'jobs-provider-zh_TW.R' 'jobs-provider.R' 'missing-data-provider.R' 'missing.R' 'name.R' 'numerics-provider.R' 'numerics.R' 'onload.R' 'person-provider-bg_BG.R' 'person-provider-cs_CZ.R' 'person-provider-de_AT.R' 'person-provider-de_DE.R' 'person-provider-dk_DK.R' 'person-provider-en_US.R' 'person-provider-es_ES.R' 'person-provider-es_MX.R' 'person-provider-fa_IR.R' 'person-provider-fi_FI.R' 'person-provider-fr_CH.R' 'person-provider-fr_FR.R' 'person-provider-hr_HR.R' 'person-provider-it_IT.R' 'person-provider-ja_JP.R' 'person-provider-ko_KR.R' 'person-provider-lt_LT.R' 'person-provider-lv_lv.R' 'person-provider-ne_NP.R' 'person-provider-nl_NL.R' 'person-provider-no_NO.R' 'person-provider-pl_PL.R' 'person-provider.R' 'phone-number-provider-all.R' 'phone_number.R' 'phonenumbers-provider.R' 'sequence-provider.R' 'sequences.R' 'taxonomy-provider.R' 'taxonomy.R' 'zzz.R'
NeedsCompilation: no
Packaged: 2017-06-16 19:14:42 UTC; sacmac
Author: Scott Chamberlain [aut, cre], Brooke Anderson [ctb] (Brooke Anderson reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/94), Tristan Mahr [ctb] (Tristan Mahr reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/94)
Maintainer: Scott Chamberlain <myrmecocystus+r@gmail.com>
Repository: CRAN
Date/Publication: 2017-06-16 19:41:21 UTC

More information about charlatan at CRAN
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New package AWR.Athena with initial version 1.1.0
Package: AWR.Athena
Type: Package
Title: 'AWS' Athena DBI Wrapper
Version: 1.1.0
Author: Neal Fultz <nfultz@gmail.com>, Gergely Daróczi <gergely@system1.com>
Maintainer: Neal Fultz <nfultz@gmail.com>
Description: 'RJDBC' based DBI driver to Amazon Athena, which is an interactive query service to analyze data in Amazon S3 using standard SQL.
License: AGPL-3
Encoding: UTF-8
LazyData: true
Imports: methods, RJDBC, rJava
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-06-15 23:11:10.27 UTC; nfultz
Repository: CRAN
Date/Publication: 2017-06-16 20:00:51 UTC

More information about AWR.Athena at CRAN
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Package mosaicQA (with last version 1.2.0) was removed from CRAN

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

2017-02-07 1.2.0
2016-09-17 1.0.1

Permanent link
New package yearn with initial version 0.1.1
Package: yearn
Title: Use and if Needed Install Packages from CRAN, BioConductor, CRAN Archive, and GitHub
Version: 0.1.1
Authors@R: person("Brian", "O'Meara", email = "omeara.brian@gmail.com", role = c("aut", "cre"))
Description: This tries to attach a package if you have it; if not, it tries to install it from BioConductor or CRAN; if not available there, it tries to install it from the cran mirror on GitHub, which includes packages that have been removed from CRAN; if not available there, it looks for a matching other package on GitHub to install. Note this is sloppy practice and prone to all sorts of risks. However, there are use cases, such as quick scripting, or in a class where students already know best practices, where this can be useful. yearn was inspired by teaching in PhyloMeth, a course funded by an NSF CAREER award to the author (NSF DEB-1453424).
Depends: R (>= 3.3.0)
Imports: githubinstall, devtools, BiocInstaller
Suggests: testthat
License: GPL (>= 2)
URL: http://www.github.com/bomeara/yearn
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-06-15 23:36:45 UTC; bomeara
Author: Brian O'Meara [aut, cre]
Maintainer: Brian O'Meara <omeara.brian@gmail.com>
Repository: CRAN
Date/Publication: 2017-06-16 18:09:47 UTC

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Package qualtRics updated to version 2.0 with previous version 1.0 dated 2017-04-26

Title: Download Qualtrics Survey Data Directly into R
Description: Qualtrics <https://www.qualtrics.com/about/> allows users to collect online data through surveys. This package contains convenience functions to pull survey results straight into R using the Qualtrics API. See <https://api.qualtrics.com/> for more information about the Qualtrics API.
Author: Jasper Ginn
Maintainer: Jasper Ginn <jasperginn@gmail.com>

Diff between qualtRics versions 1.0 dated 2017-04-26 and 2.0 dated 2017-06-16

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Package ordinalCont updated to version 1.2 with previous version 1.0.2 dated 2016-12-15

Title: Ordinal Regression Analysis for Continuous Scales
Description: A regression framework for response variables which are continuous self-rating scales such as the Visual Analog Scale (VAS) used in pain assessment, or the Linear Analog Self-Assessment (LASA) scales in quality of life studies. These scales measure subjects' perception of an intangible quantity, and cannot be handled as ratio variables because of their inherent non-linearity. We treat them as ordinal variables, measured on a continuous scale. A function (the g function) connects the scale with an underlying continuous latent variable. The link function is the inverse of the CDF of the assumed underlying distribution of the latent variable. Currently the logit link, which corresponds to a standard logistic distribution, is implemented.
Author: Maurizio Manuguerra [aut, cre], Gillian Heller [aut]
Maintainer: Maurizio Manuguerra <maurizio.manuguerra@mq.edu.au>

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Package generalCorr updated to version 1.0.5 with previous version 1.0.4 dated 2017-06-08

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. 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 gradients (Cr1) and absolute residuals (Cr2), 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)|> |r*(y|x)| it suggests that y is more likely the "kernel cause" of x. The usual partial correlations are generalized for the asymmetric matrix of r*'s 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 and one for a heuristic t-test.
Author: Prof. H. D. Vinod, Fordham University, NY.
Maintainer: H. D. Vinod <vinod@fordham.edu>

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Package eiCompare updated to version 2.1 with previous version 1.9 dated 2017-03-07

Title: Compares EI, Goodman, RxC Estimates
Description: Compares estimates from three ecological inference routines, based on King (1997) <ISBN: 0691012407>, <http://gking.harvard.edu/eicamera/kinroot.html>; King et. al. (2004) <ISBN: 0521542804>, <http://gking.harvard.edu/files/abs/ecinf04-abs.shtml>.
Author: Loren Collingwood
Maintainer: Loren Collingwood <loren.collingwood@ucr.edu>

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Package crandatapkgs updated to version 0.1.8 with previous version 0.1.7 dated 2017-03-26

Title: Find Data-Only Packages on CRAN
Description: Provides a data frame listing of known data-only and data-heavy packages available on CRAN.
Author: Thomas J. Leeper [aut, cre]
Maintainer: Thomas J. Leeper <thosjleeper@gmail.com>

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Package catSurv updated to version 1.0.1 with previous version 1.0.0 dated 2017-06-15

Title: Computerized Adaptive Testing for Survey Research
Description: Provides methods of computerized adaptive testing for survey researchers. Includes functionality for data fit with the classic item response methods including the latent trait model, Birnbaum`s three parameter model, the graded response, and the generalized partial credit model. Additionally, includes several ability parameter estimation and item selection routines. During item selection, all calculations are done in compiled C++ code.
Author: Jacob Montgomery [aut], Erin Rossiter [aut, cre]
Maintainer: Erin Rossiter <erinrossiter@wustl.edu>

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Package pipe.design updated to version 0.5.1 with previous version 0.5 dated 2017-05-01

Title: Dual-Agent Dose Escalation for Phase I Trials using the PIPE Design
Description: Implements the Product of Independent beta Probabilities dose Escalation (PIPE) design for dual-agent Phase I trials as described in Mander AP, Sweeting MJ (2015) <DOI:10.1002/sim.6434>.
Author: Michael Sweeting
Maintainer: Michael Sweeting <mjs212@medschl.cam.ac.uk>

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Package phenopix updated to version 2.3.1 with previous version 2.3 dated 2017-06-15

Title: Process Digital Images of a Vegetation Cover
Description: A collection of functions to process digital images, depict greenness index trajectories and extract relevant phenological stages.
Author: Gianluca Filippa, Edoardo Cremonese, Mirco Migliavacca, Marta Galvagno, Matthias Folker, Andrew D. Richardson, Enrico Tomelleri
Maintainer: Gianluca Filippa <gian.filippa@gmail.com>

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Package frailtypack updated to version 2.12.1 with previous version 2.11.1 dated 2017-03-21

Title: General Frailty Models: Shared, Joint and Nested Frailty Models with Prediction
Description: The following several classes of frailty models using a penalized likelihood estimation on the hazard function but also a parametric estimation can be fit using this R package: 1) A shared frailty model (with gamma or log-normal frailty distribution) and Cox proportional hazard model. Clustered and recurrent survival times can be studied. 2) Additive frailty models for proportional hazard models with two correlated random effects (intercept random effect with random slope). 3) Nested frailty models for hierarchically clustered data (with 2 levels of clustering) by including two iid gamma random effects. 4) Joint frailty models in the context of the joint modelling for recurrent events with terminal event for clustered data or not. A joint frailty model for two semi-competing risks and clustered data is also proposed. 5) Joint general frailty models in the context of the joint modelling for recurrent events with terminal event data with two independent frailty terms. 6) Joint Nested frailty models in the context of the joint modelling for recurrent events with terminal event, for hierarchically clustered data (with two levels of clustering) by including two iid gamma random effects. 7) Multivariate joint frailty models for two types of recurrent events and a terminal event. 8) Joint models for longitudinal data and a terminal event. 9) Trivariate joint models for longitudinal data, recurrent events and a terminal event. Prediction values are available (for a terminal event or for a new recurrent event). Left-truncated (not for Joint model), right-censored data, interval-censored data (only for Cox proportional hazard and shared frailty model) and strata are allowed. In each model, the random effects have the gamma or normal distribution. Now, you can also consider time-varying covariates effects in Cox, shared and joint frailty models (1-5). The package includes concordance measures for Cox proportional hazards models and for shared frailty models.
Author: Virginie Rondeau, Juan R. Gonzalez, Yassin Mazroui, Audrey Mauguen, Agnieszka Krol, Amadou Diakite, Alexandre Laurent and Myriam Lopez
Maintainer: Virginie Rondeau <Virginie.Rondeau@isped.u-bordeaux2.fr>

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More information about frailtypack at CRAN
Permanent link

Package FinePop updated to version 1.4.0 with previous version 1.3.0 dated 2017-02-10

Title: Fine-Scale Population Analysis
Description: Statistical tool set for population genetics. The package provides following functions: 1) empirical Bayes estimator of Fst and other measures of genetic differentiation, 2) regression analysis of environmental effects on genetic differentiation using bootstrap method, 3) interfaces to read and manipulate 'GENEPOP' format data files and allele/haplotype frequency format files.
Author: Reiichiro Nakamichi, Hirohisa Kishino, Shuichi Kitada
Maintainer: Reiichiro Nakamichi <nakamichi@affrc.go.jp>

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More information about FinePop at CRAN
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Package ShinyItemAnalysis updated to version 1.2.0 with previous version 1.1.0 dated 2017-02-03

Title: Test and Item Analysis via Shiny
Description: Interactive shiny application for analysis of educational tests and their items.
Author: Patricia Martinkova [aut, cre], Adela Drabinova [aut], Ondrej Leder [aut], Jakub Houdek [aut], Lubomir Stepanek [ctb]
Maintainer: Patricia Martinkova <martinkova@cs.cas.cz>

Diff between ShinyItemAnalysis versions 1.1.0 dated 2017-02-03 and 1.2.0 dated 2017-06-16

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 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/DESCRIPTION                                                              |   25 
 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/MD5                                                                      |  103 
 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/NAMESPACE                                                                |    1 
 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/NEWS                                                                     |   75 
 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/R/DDplot.R                                                               |   24 
 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/R/DistractorAnalysis.R                                                   |   62 
 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/R/dataMedical.R                                                          |   24 
 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/R/dataMedicalkey.R                                                       |   11 
 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/R/dataMedicaltest.R                                                      |   23 
 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/R/plotDIFLogistic.R                                                      |   24 
 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/R/plotDIFirt.R                                                           |   17 
 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/R/plotDistractorAnalysis.R                                               |   31 
 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/R/startShinyItemAnalysis.R                                               |    2 
 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/README.md                                                                |   38 
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 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/man/DDplot.Rd                                                            |    8 
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 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/man/dataMedical.Rd                                                       |   33 
 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/man/dataMedicalkey.Rd                                                    |   21 
 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/man/dataMedicaltest.Rd                                                   |   32 
 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/man/plotDIFLogistic.Rd                                                   |    8 
 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/man/plotDIFirt.Rd                                                        |   19 
 ShinyItemAnalysis-1.2.0/ShinyItemAnalysis/man/plotDistractorAnalysis.Rd                                            |    9 
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More information about ShinyItemAnalysis at CRAN
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New package interp with initial version 1.0-27
Package: interp
Type: Package
Title: Interpolation Methods
Version: 1.0-27
Date: 2017-06-15
Authors@R: c(person("Albrecht", "Gebhardt", role = c("aut", "cre", "cph"), email = "albrecht.gebhardt@aau.at", comment = "..."), person("Roger", "Bivand", role = c("aut"), email = "Roger.Bivand@nhh.no"), person("David", "Sinclair", role = c("aut","cph"), email = "david@s-hull.org"))
Maintainer: Albrecht Gebhardt <albrecht.gebhardt@aau.at>
Description: Bivariate data interpolation on regular and irregular grids, either linear or using splines.
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.9), deldir
Suggests: sp, Deriv
LinkingTo: Rcpp, RcppEigen
NeedsCompilation: yes
Packaged: 2017-06-15 19:21:19 UTC; alge
Author: Albrecht Gebhardt [aut, cre, cph] (...), Roger Bivand [aut], David Sinclair [aut, cph]
Repository: CRAN
Date/Publication: 2017-06-15 23:19:45 UTC

More information about interp at CRAN
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