Sat, 06 May 2017

Package RWeka updated to version 0.4-34 with previous version 0.4-33 dated 2017-04-06

Title: R/Weka Interface
Description: An R interface to Weka (Version 3.9.1). Weka is a collection of machine learning algorithms for data mining tasks written in Java, containing tools for data pre-processing, classification, regression, clustering, association rules, and visualization. Package 'RWeka' contains the interface code, the Weka jar is in a separate package 'RWekajars'. For more information on Weka see <http://www.cs.waikato.ac.nz/ml/weka/>.
Author: Kurt Hornik [aut, cre], Christian Buchta [ctb], Torsten Hothorn [ctb], Alexandros Karatzoglou [ctb], David Meyer [ctb], Achim Zeileis [ctb]
Maintainer: Kurt Hornik <Kurt.Hornik@R-project.org>

Diff between RWeka versions 0.4-33 dated 2017-04-06 and 0.4-34 dated 2017-05-06

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Package OpenImageR updated to version 1.0.6 with previous version 1.0.5 dated 2017-04-17

Title: An Image Processing Toolkit
Description: Incorporates functions for image preprocessing, filtering and image recognition. The package takes advantage of 'RcppArmadillo' to speed up computationally intensive functions. The histogram of oriented gradients descriptor is a modification of the 'findHOGFeatures' function of the 'SimpleCV' computer vision platform and the average_hash(), dhash() and phash() functions are based on the 'ImageHash' python library.
Author: Lampros Mouselimis [aut, cre], Sight Machine [cph] (findHOGFeatures function of the SimpleCV computer vision platform), Johannes Buchner [cph] (average_hash, dhash and phash functions of the ImageHash python library)
Maintainer: Lampros Mouselimis <mouselimislampros@gmail.com>

Diff between OpenImageR versions 1.0.5 dated 2017-04-17 and 1.0.6 dated 2017-05-06

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Package icesSAG (with last version 1.3-1) was removed from CRAN

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

2017-05-04 1.3-1
2017-04-30 1.3-0
2017-03-24 1.2-1
2016-12-07 1.2-0
2016-08-09 1.0

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Package spbabel updated to version 0.4.7 with previous version 0.4.6 dated 2017-04-30

Title: Convert Spatial Data Using Tidy Tables
Description: Tools to convert from specific formats to more general forms of spatial data. Using tables to store the actual entities present in spatial data provides flexibility, and the functions here deliberately minimize the level of interpretation applied, leaving that for specific applications. Includes support for simple features, round-trip for 'Spatial' classes and long-form tables, analogous to 'ggplot2::fortify'. There is also a more 'normal form' representation that decomposes simple features and their kin to tables of objects, parts, and unique coordinates.
Author: Michael D. Sumner [aut, cre]
Maintainer: Michael D. Sumner <mdsumner@gmail.com>

Diff between spbabel versions 0.4.6 dated 2017-04-30 and 0.4.7 dated 2017-05-06

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New package PROreg with initial version 1.0
Package: PROreg
Title: Patient Reported Outcomes Regression Analysis
Version: 1.0
Author: Josu Najera <jnajera@bcamath.org>, Dae-Jin Lee <dlee@bcamath.org>, Inmaculada Arostegui <inmaculada.arostegui@ehu.es>
Maintainer: Josu Najera <jnajera@bcamath.org>
Description: Offers a variety of tools, such as specific plots and regression model approaches, for analyzing different patient reported questionnaires. Specially, mixed-effects models based on the beta-binomial distribution are implemented to deal with binomial data with over-dispersion (see Najera-Zuloaga J., Lee D.-J. and Arostegui I. (2017) <doi:10.1177/0962280217690413>).
License: GPL
Imports: fmsb, car, RColorBrewer, matrixcalc, rootSolve, numDeriv, Matrix
NeedsCompilation: no
Packaged: 2017-05-06 08:08:05 UTC; jnajera
Repository: CRAN
Date/Publication: 2017-05-06 09:06:26 UTC

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Package mixlm updated to version 1.2.1 with previous version 1.1.5 dated 2016-10-08

Title: Mixed Model ANOVA and Statistics for Education
Description: The main functions perform mixed models analysis by least squares or REML by adding the function r() to formulas of lm() and glm(). A collection of text-book statistics for higher education is also included, e.g. modifications of the functions lm(), glm() and associated summaries from the package 'stats'.
Author: Kristian Hovde Liland [aut, cre], Solve Sæbø [ctb], R-Core [ctb]
Maintainer: Kristian Hovde Liland <kristian.liland@nmbu.no>

Diff between mixlm versions 1.1.5 dated 2016-10-08 and 1.2.1 dated 2017-05-06

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Package janitor updated to version 0.3.0 with previous version 0.2.1 dated 2016-10-31

Title: Simple Tools for Examining and Cleaning Dirty Data
Description: The main janitor functions can: perfectly format data.frame column names; provide quick one- and two-variable tabulations (i.e., frequency tables and crosstabs); and isolate duplicate records. Other janitor functions nicely format the tabulation results. These tabulate-and-report functions approximate popular features of SPSS and Microsoft Excel. This package follows the principles of the "tidyverse" and works well with the pipe function %>%. janitor was built with beginning-to-intermediate R users in mind and is optimized for user-friendliness. Advanced R users can already do everything covered here, but with janitor they can do it faster and save their thinking for the fun stuff.
Author: Sam Firke [aut, cre], Chris Haid [ctb], Ryan Knight [ctb]
Maintainer: Sam Firke <samuel.firke@gmail.com>

Diff between janitor versions 0.2.1 dated 2016-10-31 and 0.3.0 dated 2017-05-06

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Package glmmLasso updated to version 1.5.1 with previous version 1.5.0 dated 2017-04-28

Title: Variable Selection for Generalized Linear Mixed Models by L1-Penalized Estimation
Description: A variable selection approach for generalized linear mixed models by L1-penalized estimation is provided.
Author: Andreas Groll
Maintainer: Andreas Groll <groll@mathematik.uni-muenchen.de>

Diff between glmmLasso versions 1.5.0 dated 2017-04-28 and 1.5.1 dated 2017-05-06

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Package glmnet updated to version 2.0-10 with previous version 2.0-9 dated 2017-05-02

Title: Lasso and Elastic-Net Regularized Generalized Linear Models
Description: Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression and the Cox model. Two recent additions are the multiple-response Gaussian, and the grouped multinomial regression. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the paper linked to via the URL below.
Author: Jerome Friedman, Trevor Hastie, Noah Simon, Rob Tibshirani
Maintainer: Trevor Hastie <hastie@stanford.edu>

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Package VarfromPDB updated to version 2.2.7 with previous version 2.2.6 dated 2017-04-26

Title: Disease-Gene-Variant Relations Mining from the Public Databases and Literature
Description: Captures and compiles the genes and variants related to a disease, a phenotype or a clinical feature from the public databases including HPO (Human Phenotype Ontology, <http://human-phenotype-ontology.github.io/about.html>), Orphanet <http://www.orpha.net/consor/cgi-bin/index.php>, OMIM (Online Mendelian Inheritance in Man, <http://www.omim.org>), ClinVar <http://www.ncbi.nlm.nih.gov/clinvar>, and UniProt (Universal Protein Resource, <http://www.uniprot.org>) and PubMed abstracts. HPO provides a standardized vocabulary of phenotypic abnormalities encountered in human disease. HPO currently contains approximately 11,000 terms and over 115,000 annotations to hereditary diseases. Orphanet is the reference portal for information on rare diseases and orphan drugs, whose aim is to help improve the diagnosis, care and treatment of patients with rare diseases. OMIM is a continuously updated catalog of human genes and genetic disorders and traits, with particular focus on the molecular relationship between genetic variation and phenotypic expression. ClinVar is a freely accessible, public archive of reports of the relationships among human variations and phenotypes, with supporting evidence. UniProt focuses on amino acid altering variants imported from Ensembl Variation databases. For Homo sapiens, the variants including human polymorphisms and disease mutations in the UniProt are manually curated from UniProtKB/Swiss-Prot. Additionally, PubMed provides the primary and latest source of the information. Text mining was employed to capture the information from PubMed abstracts.
Author: Zongfu Cao <caozongfu@gmail.com>; Lei Wang <isan.wong@gmail.com>
Maintainer: Zongfu Cao <caozongfu@gmail.com>

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Package SuperExactTest updated to version 0.99.3 with previous version 0.99.2 dated 2015-11-10

Title: Exact Test and Visualization of Multi-Set Intersections
Description: Identification of sets of objects with shared features is a common operation in all disciplines. Analysis of intersections among multiple sets is fundamental for in-depth understanding of their complex relationships. This package implements a theoretical framework for efficient computation of statistical distributions of multi-set intersections based upon combinatorial theory, and provides multiple scalable techniques for visualizing the intersection statistics. The statistical algorithm behind this package was published in Wang et al (2015), doi:10.1038/srep16923.
Author: Minghui Wang, Yongzhong Zhao and Bin Zhang
Maintainer: Minghui Wang <minghui.wang@mssm.edu>

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Package spatstat.utils updated to version 1.6-0 with previous version 1.4-1 dated 2017-03-21

Title: Utility Functions for 'spatstat'
Description: Contains utility functions for the 'spatstat' package which may also be useful for other purposes.
Author: Adrian Baddeley [aut, cre], Rolf Turner [aut], Ege Rubak [aut]
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

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Package rnoaa updated to version 0.7.0 with previous version 0.6.6 dated 2016-11-17

Title: 'NOAA' Weather Data from R
Description: Client for many 'NOAA' data sources including the 'NCDC' climate 'API' at <https://www.ncdc.noaa.gov/cdo-web/webservices/v2>, with functions for each of the 'API' 'endpoints': data, data categories, data sets, data types, locations, location categories, and stations. In addition, we have an interface for 'NOAA' sea ice data, the 'NOAA' severe weather inventory, 'NOAA' Historical Observing 'Metadata' Repository ('HOMR') data, 'NOAA' storm data via 'IBTrACS', tornado data via the 'NOAA' storm prediction center, and more.
Author: Scott Chamberlain [aut, cre], Brooke Anderson [ctb], Maëlle Salmon [ctb], Adam Erickson [ctb], Nicholas Potter [ctb], Joseph Stachelek [ctb], Alex Simmons [ctb], Karthik Ram [ctb], Hart Edmund [ctb]
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

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 inst/vign/myfile.zip                   |binary
 inst/vign/ncdc_attributes.Rmd          |  122 ++++++-------
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 inst/vign/rnoaa_ropenaq.Rmd            |   18 -
 inst/vign/rnoaa_ropenaq.md             |   68 +++----
 inst/vign/seaice_vignette.Rmd          |   13 -
 inst/vign/seaice_vignette.md           |   26 --
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 man/deg2rad.Rd                         |    1 
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 man/erddap_table-defunct.Rd            |    1 
 man/ersst.Rd                           |    8 
 man/fipscodes.Rd                       |    1 
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 man/ghcnd.Rd                           |   14 -
 man/ghcnd_search.Rd                    |    7 
 man/ghcnd_splitvars.Rd                 |    1 
 man/ghcnd_states.Rd                    |    3 
 man/ghcnd_stations.Rd                  |    1 
 man/homr.Rd                            |    1 
 man/homr_definitions.Rd                |    1 
 man/is.ncdc_data.Rd                    |    3 
 man/isd.Rd                             |   31 ++-
 man/isd_read.Rd                        |   10 -
 man/isd_stations.Rd                    |    2 
 man/isd_stations_search.Rd             |    1 
 man/meteo_clear_cache.Rd               |    1 
 man/meteo_coverage.Rd                  |    1 
 man/meteo_distance.Rd                  |    1 
 man/meteo_nearby_stations.Rd           |    9 
 man/meteo_process_geographic_data.Rd   |    1 
 man/meteo_pull_monitors.Rd             |    7 
 man/meteo_show_cache.Rd                |    1 
 man/meteo_spherical_distance.Rd        |    1 
 man/meteo_tidy_ghcnd.Rd                |    7 
 man/meteo_tidy_ghcnd_element.Rd        |    1 
 man/ncdc.Rd                            |  204 ++++++++++++---------
 man/ncdc_combine.Rd                    |    1 
 man/ncdc_datacats.Rd                   |    4 
 man/ncdc_datasets.Rd                   |   25 +-
 man/ncdc_datatypes.Rd                  |   27 +-
 man/ncdc_leg_data-defunct.Rd           |    1 
 man/ncdc_leg_site_info-defunct.Rd      |    1 
 man/ncdc_leg_sites-defunct.Rd          |    1 
 man/ncdc_leg_variables-defunct.Rd      |    1 
 man/ncdc_locs.Rd                       |    8 
 man/ncdc_locs_cats.Rd                  |    9 
 man/ncdc_plot.Rd                       |    1 
 man/ncdc_stations.Rd                   |   29 +--
 man/ncdc_theme.Rd                      |    1 
 man/noaa-defunct.Rd                    |    1 
 man/noaa_combine-defunct.Rd            |    1 
 man/noaa_datacats-defunct.Rd           |    1 
 man/noaa_datasets-defunct.Rd           |    1 
 man/noaa_datatypes-defunct.Rd          |    1 
 man/noaa_locs-defunct.Rd               |    1 
 man/noaa_locs_cats-defunct.Rd          |    1 
 man/noaa_plot-defunct.Rd               |    1 
 man/noaa_seaice-defunct.Rd             |    1 
 man/noaa_stations-defunct.Rd           |    1 
 man/readshpfile.Rd                     |    1 
 man/rnoaa-package.Rd                   |    8 
 man/seaice.Rd                          |    4 
 man/seaiceeurls.Rd                     |    9 
 man/storm_columns.Rd                   |    1 
 man/storm_names.Rd                     |    1 
 man/storms.Rd                          |    6 
 man/swdi.Rd                            |    1 
 man/theme_ice.Rd                       |    1 
 man/tornadoes.Rd                       |    5 
 man/type_summ.Rd                       |    9 
 man/vis_miss.Rd                        |    1 
 tests/testthat/test-coops.R            |   39 +++-
 tests/testthat/test-cpc_prcp.R         |only
 tests/testthat/test-ghcnd.R            |    8 
 tests/testthat/test-ghcnd_splitvars.R  |    1 
 tests/testthat/test-isd_read.R         |    6 
 tools                                  |only
 vignettes/homr_vignette.Rmd            |  132 ++++++++------
 vignettes/ncdc_attributes.Rmd          |  122 ++++++-------
 vignettes/ncdc_vignette.Rmd            |   42 +++-
 vignettes/ncdc_workflow.Rmd            |    8 
 vignettes/rnoaa_ropenaq.Rmd            |   68 +++----
 vignettes/seaice_vignette.Rmd          |   26 --
 vignettes/storms_vignette.Rmd          |    4 
 vignettes/swdi_vignette.Rmd            |   18 -
 160 files changed, 2127 insertions(+), 1662 deletions(-)

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New package rlang with initial version 0.1
Package: rlang
Version: 0.1
Title: Functions for Base Types and Core R and 'Tidyverse' Features
Description: A toolbox for working with base types, core R features like the condition system, and core 'Tidyverse' features like tidy evaluation.
Authors@R: c( person("Lionel", "Henry", ,"lionel@rstudio.com", c("aut", "cre")), person("Hadley", "Wickham", ,"hadley@rstudio.com", "aut"), person("RStudio", role = "cph") )
License: GPL-3
LazyData: true
Depends: R (>= 3.1.0)
Suggests: knitr, rmarkdown (>= 0.2.65), testthat, covr
VignetteBuilder: knitr
RoxygenNote: 6.0.1
URL: https://github.com/tidyverse/rlang
BugReports: https://github.com/tidyverse/rlang/issues
NeedsCompilation: yes
Packaged: 2017-05-06 00:11:09 UTC; lionel
Author: Lionel Henry [aut, cre], Hadley Wickham [aut], RStudio [cph]
Maintainer: Lionel Henry <lionel@rstudio.com>
Repository: CRAN
Date/Publication: 2017-05-06 05:23:04 UTC

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New package pwr2 with initial version 1.0
Package: pwr2
Type: Package
Title: Power and Sample Size Analysis for One-way and Two-way ANOVA Models
Version: 1.0
Date: 2017-05-01
Author: Pengcheng Lu, Junhao Liu, Devin Koestler
Maintainer: Pengcheng Lu <plu2@kumc.edu>
Description: User friendly functions for power and sample size analysis at one-way and two-way ANOVA settings take either effect size or delta and sigma as arguments. They are designed for both one-way and two-way ANOVA settings. In addition, a function for plotting power curves is available for power comparison, which can be easily visualized by statisticians and clinical researchers.
License: GPL-2
NeedsCompilation: no
Packaged: 2017-05-02 02:51:50 UTC; Junhao
Repository: CRAN
Date/Publication: 2017-05-06 05:22:35 UTC

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Package MNP updated to version 3.0-1 with previous version 2.6-4 dated 2013-06-09

Title: R Package for Fitting the Multinomial Probit Model
Description: Fits the Bayesian multinomial probit model via Markov chain Monte Carlo. The multinomial probit model is often used to analyze the discrete choices made by individuals recorded in survey data. Examples where the multinomial probit model may be useful include the analysis of product choice by consumers in market research and the analysis of candidate or party choice by voters in electoral studies. The MNP package can also fit the model with different choice sets for each individual, and complete or partial individual choice orderings of the available alternatives from the choice set. The estimation is based on the efficient marginal data augmentation algorithm that is developed by Imai and van Dyk (2005). ``A Bayesian Analysis of the Multinomial Probit Model Using the Data Augmentation,'' Journal of Econometrics, Vol. 124, No. 2 (February), pp. 311-334. <DOI:10.1016/j.jeconom.2004.02.002> Detailed examples are given in Imai and van Dyk (2005). ``MNP: R Package for Fitting the Multinomial Probit Model.'' Journal of Statistical Software, Vol. 14, No. 3 (May), pp. 1-32. <DOI:10.18637/jss.v014.i03>.
Author: Kosuke Imai [aut, cre], David van Dyk [aut], Jin Hubert [ctb]
Maintainer: Kosuke Imai <kimai@princeton.edu>

Diff between MNP versions 2.6-4 dated 2013-06-09 and 3.0-1 dated 2017-05-06

 MNP-2.6-4/MNP/MNP.pdf                      |only
 MNP-3.0-1/MNP/ChangeLog                    |only
 MNP-3.0-1/MNP/DESCRIPTION                  |   56 ++--
 MNP-3.0-1/MNP/MD5                          |   54 ++--
 MNP-3.0-1/MNP/NAMESPACE                    |    4 
 MNP-3.0-1/MNP/R/coef.mnp.R                 |   23 +
 MNP-3.0-1/MNP/R/cov.mnp.R                  |   21 +
 MNP-3.0-1/MNP/R/detergent.R                |only
 MNP-3.0-1/MNP/R/japan.R                    |only
 MNP-3.0-1/MNP/R/mnp.R                      |  182 ++++++++++++++
 MNP-3.0-1/MNP/R/predict.mnp.R              |   73 +++++
 MNP-3.0-1/MNP/R/print.summary.mnp.R        |   13 +
 MNP-3.0-1/MNP/R/summary.mnp.R              |   25 +
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 MNP-3.0-1/MNP/man/cov.mnp.Rd               |   54 +---
 MNP-3.0-1/MNP/man/detergent.Rd             |   43 +--
 MNP-3.0-1/MNP/man/japan.Rd                 |   42 +--
 MNP-3.0-1/MNP/man/mnp.Rd                   |  367 +++++++++++++----------------
 MNP-3.0-1/MNP/man/predict.mnp.Rd           |  186 ++++++--------
 MNP-3.0-1/MNP/man/print.summary.mnp.Rd     |only
 MNP-3.0-1/MNP/man/summary.mnp.Rd           |   68 ++---
 MNP-3.0-1/MNP/src/MNP.c                    |    1 
 MNP-3.0-1/MNP/src/rand.c                   |    3 
 MNP-3.0-1/MNP/src/registerDynamicSymbols.c |only
 MNP-3.0-1/MNP/src/subroutines.c            |    1 
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 30 files changed, 779 insertions(+), 495 deletions(-)

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New package miRNAss with initial version 1.0
Package: miRNAss
Type: Package
Title: Genome-Wide Discovery of Pre-miRNAs with few Labeled Examples
Version: 1.0
Author: Cristian Yones
Maintainer: Cristian Yones <cyones@sinc.unl.edu.ar>
Description: Machine learning method specifically designed for pre-miRNA prediction. It takes advantage of unlabeled sequences to improve the prediction rates even when there are just a few positive examples, when the negative examples are unreliable or are not good representatives of its class. Furthermore, the method can automatically search for negative examples if the user is unable to provide them. MiRNAss can find a good boundary to divide the pre-miRNAs from other groups of sequences; it automatically optimizes the threshold that defines the classes boundaries, and thus, it is robust to high class imbalance. Each step of the method is scalable and can handle large volumes of data.
License: Apache License 2.0
Encoding: UTF-8
LazyData: true
Imports: Matrix, stats, Rcpp, CORElearn, RSpectra,
LinkingTo: Rcpp
NeedsCompilation: yes
RoxygenNote: 6.0.1
Packaged: 2017-05-05 22:35:54 UTC; cyones
Repository: CRAN
Date/Publication: 2017-05-06 05:24:05 UTC

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Package efreadr updated to version 0.2.2 with previous version 0.1.1 dated 2016-03-08

Title: Read European Eddy Fluxes CSV Files
Description: The European Eddy Fluxes Database Cluster distributes fluxes of different Green House Gases measured mainly using the eddy covariance technique acquired in sites involved in EU projects but also single sites in Europe, Africa and others continents that decided to share their measurements in the database <http://gaia.agraria.unitus.it>. The package provides two functions to load and row-wise bind CSV files distributed by the database. Currently only L2, L3, and L4 (L=Level), half-hourly and daily (aggregation) files are supported.
Author: Marco Bascietto [aut, cre]
Maintainer: Marco Bascietto <marco.bascietto@crea.gov.it>

Diff between efreadr versions 0.1.1 dated 2016-03-08 and 0.2.2 dated 2017-05-06

 efreadr-0.1.1/efreadr/inst/extdata           |only
 efreadr-0.2.2/efreadr/DESCRIPTION            |   16 +-
 efreadr-0.2.2/efreadr/MD5                    |   30 ++---
 efreadr-0.2.2/efreadr/NAMESPACE              |   12 +-
 efreadr-0.2.2/efreadr/NEWS                   |   11 +
 efreadr-0.2.2/efreadr/R/efreadr.R            |  125 ++++++++++++++++++++
 efreadr-0.2.2/efreadr/R/read_ef_file.R       |   84 +++++++++-----
 efreadr-0.2.2/efreadr/R/read_ef_files.R      |  161 ++++++++++++++++-----------
 efreadr-0.2.2/efreadr/R/utils.R              |only
 efreadr-0.2.2/efreadr/README.md              |    3 
 efreadr-0.2.2/efreadr/inst/examples          |only
 efreadr-0.2.2/efreadr/man/efreadr-package.Rd |    7 -
 efreadr-0.2.2/efreadr/man/read_ef_file.Rd    |   27 +++-
 efreadr-0.2.2/efreadr/man/read_ef_files.Rd   |   35 ++---
 14 files changed, 363 insertions(+), 148 deletions(-)

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New package crochet with initial version 1.0.0
Package: crochet
Version: 1.0.0
License: MIT + file LICENSE
Title: Implementation Helper for [ and [<- Of Custom Matrix-Like Types
Description: Functions to help implement the extraction / subsetting / indexing function [ and replacement function [<- of custom matrix-like types (based on S3, S4, etc.), modeled as closely to the base matrix class as possible (with tests to prove it).
Authors@R: person("Alexander", "Grueneberg", email = "alexander.grueneberg@googlemail.com", role = c("aut", "cre"))
URL: https://github.com/agrueneberg/crochet
BugReports: https://github.com/agrueneberg/crochet/issues
Imports: methods
Suggests: testthat
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-05-05 22:44:52 UTC; agrueneberg
Author: Alexander Grueneberg [aut, cre]
Maintainer: Alexander Grueneberg <alexander.grueneberg@googlemail.com>
Repository: CRAN
Date/Publication: 2017-05-06 05:20:30 UTC

More information about crochet at CRAN
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