Tue, 30 May 2017

Package VarReg updated to version 1.0.1 with previous version 1.0 dated 2017-03-21

Title: Semi-Parametric Variance Regression
Description: Methods for fitting semi-parametric mean and variance models, with normal or censored data. Also extended to allow a regression in the location, scale and shape parameters.
Author: Kristy Robledo [aut, cre], Ian Marschner [ths]
Maintainer: Kristy Robledo <robledo.kristy@gmail.com>

Diff between VarReg versions 1.0 dated 2017-03-21 and 1.0.1 dated 2017-05-30

 DESCRIPTION           |    6 +++---
 MD5                   |   33 ++++++++++++++++++---------------
 R/VarReg_control.R    |    2 +-
 R/censloop_em.R       |    2 +-
 R/criterion.R         |    2 +-
 R/lss_calc.R          |    5 ++---
 R/plotVarReg.R        |    2 +-
 R/plotlssVarReg.R     |    9 ++++-----
 R/seVarReg.R          |   12 ++++++------
 R/vcf.R               |only
 data/vcf.rdata        |only
 man/VarReg.control.Rd |    2 +-
 man/censloop_em.Rd    |    2 +-
 man/criterion.Rd      |    2 +-
 man/lss_calc.Rd       |    1 -
 man/plotVarReg.Rd     |    2 +-
 man/plotlssVarReg.Rd  |    9 ++++-----
 man/seVarReg.Rd       |   12 ++++++------
 man/vcf.Rd            |only
 19 files changed, 51 insertions(+), 52 deletions(-)

More information about VarReg at CRAN
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Package HIBPwned updated to version 0.1.6 with previous version 0.1.4 dated 2017-05-04

Title: Bindings for the 'HaveIBeenPwned.com' Data Breach API
Description: Utilising the 'Have I been pwned?' API (see <https://haveibeenpwned.com/API/v2> for more information), check whether email addresses and/or user names have been present in a publicly disclosed data breach.
Author: Steph Locke [aut, cre], Troy Hunt [aut] (HaveIBeenPwned.com)
Maintainer: Steph Locke <stephanie.g.locke@gmail.com>

Diff between HIBPwned versions 0.1.4 dated 2017-05-04 and 0.1.6 dated 2017-05-30

 DESCRIPTION        |   10 -
 MD5                |   10 -
 NEWS.md            |    7 -
 R/utils.R          |    2 
 README.md          |  296 ++++++++++++++++++++++++++++-------------------------
 inst/doc/HIBP.html |   27 ++--
 6 files changed, 193 insertions(+), 159 deletions(-)

More information about HIBPwned at CRAN
Permanent link

Package edpclient updated to version 0.1.0 with previous version 0.0.1 dated 2017-05-28

Title: Empirical Data Platform Client
Description: R client for Empirical Data Platform. More information is at <https://empirical.com>. For support, contact support@empirical.com.
Author: Empirical Engineering
Maintainer: Madeleine Thompson <madeleine@empirical.com>

Diff between edpclient versions 0.0.1 dated 2017-05-28 and 0.1.0 dated 2017-05-30

 edpclient-0.0.1/edpclient/tests/lint.R                   |only
 edpclient-0.0.1/edpclient/tests/test_create_population.R |only
 edpclient-0.0.1/edpclient/tests/test_dataframes.R        |only
 edpclient-0.0.1/edpclient/tests/test_population.R        |only
 edpclient-0.0.1/edpclient/tests/test_session.R           |only
 edpclient-0.1.0/edpclient/DESCRIPTION                    |   10 ++--
 edpclient-0.1.0/edpclient/MD5                            |   30 ++++++++------
 edpclient-0.1.0/edpclient/NAMESPACE                      |    7 +++
 edpclient-0.1.0/edpclient/R/create_population.R          |    7 ++-
 edpclient-0.1.0/edpclient/R/popmod.R                     |   31 ++++++---------
 edpclient-0.1.0/edpclient/R/population.R                 |    5 ++
 edpclient-0.1.0/edpclient/R/session.R                    |   31 ++++++++++-----
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 edpclient-0.1.0/edpclient/build/partial.rdb              |binary
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 19 files changed, 76 insertions(+), 49 deletions(-)

More information about edpclient at CRAN
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Package CpGassoc updated to version 2.60 with previous version 2.55 dated 2016-01-29

Title: Association Between Methylation and a Phenotype of Interest
Description: Is designed to test for association between methylation at CpG sites across the genome and a phenotype of interest, adjusting for any relevant covariates. The package can perform standard analyses of large datasets very quickly with no need to impute the data. It can also handle mixed effects models with chip or batch entering the model as a random intercept. Also includes tools to apply quality control filters, perform permutation tests, and create QQ plots, manhattan plots, and scatterplots for individual CpG sites.
Author: Barfield, R., Conneely, K., Kilaru,V
Maintainer: R Barfield <barfieldrichard8@gmail.com>

Diff between CpGassoc versions 2.55 dated 2016-01-29 and 2.60 dated 2017-05-30

 DESCRIPTION             |   10 
 MD5                     |   20 
 R/cpg.work.R            |    4 
 build/vignette.rds      |binary
 data/annotation.rda     |binary
 data/samplecpg.rda      |binary
 data/samplepheno.rda    |binary
 inst/doc/CpGassoc.Rnw   | 1900 ++++++++++++++++++++++++------------------------
 inst/doc/CpGassoc.pdf   |binary
 man/CpGassoc-package.Rd |    6 
 vignettes/CpGassoc.Rnw  | 1900 ++++++++++++++++++++++++------------------------
 11 files changed, 1920 insertions(+), 1920 deletions(-)

More information about CpGassoc at CRAN
Permanent link

Package sisVIVE updated to version 1.4 with previous version 1.3 dated 2016-06-05

Title: Some Invalid Some Valid Instrumental Variables Estimator
Description: Selects invalid instruments amongst a candidate of potentially bad instruments. The algorithm selects potentially invalid instruments and provides an estimate of the causal effect between exposure and outcome.
Author: Hyunseung Kang <hyunseung@stat.wisc.edu>
Maintainer: Hyunseung Kang <hyunseung@stat.wisc.edu>

Diff between sisVIVE versions 1.3 dated 2016-06-05 and 1.4 dated 2017-05-30

 DESCRIPTION |   12 ++++++------
 MD5         |    2 +-
 2 files changed, 7 insertions(+), 7 deletions(-)

More information about sisVIVE at CRAN
Permanent link

Package RSDA updated to version 1.4 with previous version 1.3 dated 2015-11-03

Title: R to Symbolic Data Analysis
Description: Symbolic Data Analysis (SDA) was proposed by professor Edwin Diday in 1987, the main purpose of SDA is to substitute the set of rows (cases) in the data table for a concept (second order statistical unit). This package implements, to the symbolic case, certain techniques of automatic classification, as well as some linear models.
Author: Oldemar Rodriguez R. with contributions from Carlos Aguero, Olger Calderon, Roberto Zuniga and Jorge Arce
Maintainer: Oldemar Rodriguez <oldemar.rodriguez@ucr.ac.cr>

Diff between RSDA versions 1.3 dated 2015-11-03 and 1.4 dated 2017-05-30

 RSDA-1.3/RSDA/man/RSDA-package.Rd                        |only
 RSDA-1.3/RSDA/man/sym.kmeans.Rd                          |only
 RSDA-1.4/RSDA/DESCRIPTION                                |   18 
 RSDA-1.4/RSDA/MD5                                        |  381 +++++++------
 RSDA-1.4/RSDA/NAMESPACE                                  |   23 
 RSDA-1.4/RSDA/R/R2.L.R                                   |   44 +
 RSDA-1.4/RSDA/R/R2.U.R                                   |   44 +
 RSDA-1.4/RSDA/R/RMSE.L.R                                 |   50 +
 RSDA-1.4/RSDA/R/RMSE.U.R                                 |   50 +
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 RSDA-1.4/RSDA/R/SDS.to.RSDA.R                            |  430 ++++++++-------
 RSDA-1.4/RSDA/R/SODAS.to.RSDA.R                          |  144 +++--
 RSDA-1.4/RSDA/R/calculate.probs.R                        |only
 RSDA-1.4/RSDA/R/centers.interval.R                       |   64 +-
 RSDA-1.4/RSDA/R/cfa.CVPRealz.R                           |   51 -
 RSDA-1.4/RSDA/R/cfa.Czz.R                                |   84 +-
 RSDA-1.4/RSDA/R/cfa.MatrixZ.R                            |   88 +--
 RSDA-1.4/RSDA/R/cfa.minmax.R                             |  292 +++++-----
 RSDA-1.4/RSDA/R/cfa.scatterplot.R                        |  124 ++--
 RSDA-1.4/RSDA/R/cfa.totals.R                             |  109 +--
 RSDA-1.4/RSDA/R/classic.to.sym.R                         |  279 ++++++++-
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 RSDA-1.4/RSDA/R/display.sym.table.R                      |   26 
 RSDA-1.4/RSDA/R/dist.vect.R                              |   44 +
 RSDA-1.4/RSDA/R/dist.vect.matrix.R                       |   55 +
 RSDA-1.4/RSDA/R/downarrow.matrix.R                       |  165 ++---
 RSDA-1.4/RSDA/R/generate.sym.table.R                     |  113 ++-
 RSDA-1.4/RSDA/R/interscal.B.R                            |   58 +-
 RSDA-1.4/RSDA/R/interscal.R                              |  134 ++--
 RSDA-1.4/RSDA/R/interscal.delta.R                        |   74 +-
 RSDA-1.4/RSDA/R/interval.dist.R                          |  114 ++-
 RSDA-1.4/RSDA/R/interval.dist.tobj.R                     |  141 ++--
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 RSDA-1.4/RSDA/R/neighbors.vertex.R                       |   44 +
 RSDA-1.4/RSDA/R/newSobject.R                             |   65 +-
 RSDA-1.4/RSDA/R/norm.vect.R                              |   36 +
 RSDA-1.4/RSDA/R/plotX.slice.R                            |  116 +---
 RSDA-1.4/RSDA/R/predictsym.glm.R                         |  127 ++--
 RSDA-1.4/RSDA/R/predictsym.lm.R                          |  135 ++--
 RSDA-1.4/RSDA/R/process.continue.variable.R              |   36 -
 RSDA-1.4/RSDA/R/process.continuum.variable.R             |   11 
 RSDA-1.4/RSDA/R/process.histogram.variable.R             |   64 +-
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 RSDA-1.4/RSDA/R/process.set.variable.R                   |   46 -
 RSDA-1.4/RSDA/R/read.sym.table.R                         |  247 ++++++--
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 RSDA-1.4/RSDA/R/sym.circle.plot.R                        |  108 ++-
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 RSDA-1.4/RSDA/R/sym.hclust.R                             |   46 +
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 RSDA-1.4/RSDA/R/sym.interval.pc.R                        |  250 +++++---
 RSDA-1.4/RSDA/R/sym.interval.pc.limits.R                 |  105 ++-
 RSDA-1.4/RSDA/R/sym.interval.pca.R                       |  333 +++++++----
 RSDA-1.4/RSDA/R/sym.kmeans.R                             |   94 ++-
 RSDA-1.4/RSDA/R/sym.lm.R                                 |  121 ++--
 RSDA-1.4/RSDA/R/sym.lm.bi.R                              |  176 ++++--
 RSDA-1.4/RSDA/R/sym.mds.R                                |   44 +
 RSDA-1.4/RSDA/R/sym.mean.R                               |   75 +-
 RSDA-1.4/RSDA/R/sym.median.R                             |   71 +-
 RSDA-1.4/RSDA/R/sym.normalize.R                          |   40 -
 RSDA-1.4/RSDA/R/sym.obj.R                                |   62 +-
 RSDA-1.4/RSDA/R/sym.scatterplot.R                        |  133 +++-
 RSDA-1.4/RSDA/R/sym.scatterplot.ggplot.R                 |  105 ++-
 RSDA-1.4/RSDA/R/sym.scatterplot3d.R                      |  157 +++--
 RSDA-1.4/RSDA/R/sym.sd.R                                 |   91 ++-
 RSDA-1.4/RSDA/R/sym.var.R                                |   84 ++
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 RSDA-1.4/RSDA/R/var.sym.data.table.R                     |only
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 RSDA-1.4/RSDA/R/vertex.interval.R                        |   97 ++-
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Package NetworkChange updated to version 0.2 with previous version 0.1 dated 2017-03-29

Title: Bayesian Package for Network Changepoint Analysis
Description: Network changepoint analysis for undirected network data. The package implements a hidden Markov multilinear tenstor regression model (Park and Sohn, 2017, <http://jhp.snu.ac.kr/NetworkChange.pdf>). Functions for break number detection using the approximate marginal likelihood and WAIC are also provided.
Author: Jong Hee Park and Yunkyu Sohn
Maintainer: Jong Hee Park <jongheepark@snu.ac.kr>

Diff between NetworkChange versions 0.1 dated 2017-03-29 and 0.2 dated 2017-05-30

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Package vardpoor updated to version 0.9.4 with previous version 0.9.2 dated 2017-05-15

Title: Variance Estimation for Sample Surveys by the Ultimate Cluster Method
Description: Generation of domain variables, linearization of several nonlinear population statistics (the ratio of two totals, weighted income percentile, relative median income ratio, at-risk-of-poverty rate, at-risk-of-poverty threshold, Gini coefficient, gender pay gap, the aggregate replacement ratio, the relative median income ratio, median income below at-risk-of-poverty gap, income quintile share ratio, relative median at-risk-of-poverty gap), computation of regression residuals in case of weight calibration, variance estimation of sample surveys by the ultimate cluster method (Hansen, Hurwitz and Madow,Theory, vol. I: Methods and Applications; vol. II: Theory. 1953, New York: John Wiley and Sons), variance estimation for longitudinal, cross-sectional measures and measures of change for single and multistage stage cluster sampling designs (Berger, Y. G., 2015, <doi:10.1111/rssa.12116>). Several other precision measures are derived - standard error, the coefficient of variation, the margin of error, confidence interval, design effect.
Author: Juris Breidaks [aut, cre], Martins Liberts [aut], Santa Ivanova [aut]
Maintainer: Juris Breidaks <Juris.Breidaks@csb.gov.lv>

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New package dtangle with initial version 0.1.0
Package: dtangle
Title: Cell Type Deconvolution from Gene Expressions
Version: 0.1.0
Description: Deconvolving cell types from high-throughput gene profiling data.
Date: 2017-05-24
Author: Gregory Hunt
Maintainer: Gregory Hunt <gjhunt@umich.edu>
LazyData: true
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
License: GPL-3
Depends: R(>= 2.10.0)
NeedsCompilation: no
Packaged: 2017-05-30 13:50:52 UTC; greg
Repository: CRAN
Date/Publication: 2017-05-30 16:09:58 UTC

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New package RTaxometrics with initial version 2.0
Package: RTaxometrics
Type: Package
Title: Taxometric Analysis
Version: 2.0
Date: 2017-05-30
Author: John Ruscio <ruscio@tcnj.edu> and Shirley Wang <wangs7@tcnj.edu>
Maintainer: John Ruscio <ruscio@tcnj.edu>
Description: We provide functions to perform taxometric analyses. This package contains 52 functions, but only 5 should be called directly by users. CheckData() should be run prior to any taxometric analysis to ensure that the data are appropriate for taxometric analysis. RunTaxometrics() performs taxometric analyses for a sample of data. RunCCFIProfile() performs a series of taxometric analyses to generate a CCFI profile. CreateData() generates a sample of categorical or dimensional data. ClassifyCases() assigns cases to groups using the base-rate classification method.
License: MIT + file LICENSE
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-05-30 14:16:50 UTC; Shirley
Repository: CRAN
Date/Publication: 2017-05-30 15:36:34 UTC

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Package loder updated to version 0.1.2 with previous version 0.1.0 dated 2017-05-05

Title: Dependency-Free Access to PNG Image Files
Description: Read and write access to PNG image files using the LodePNG library. The package has no external dependencies.
Author: Jon Clayden [aut, cre], Lode Vandevenne [aut]
Maintainer: Jon Clayden <code@clayden.org>

Diff between loder versions 0.1.0 dated 2017-05-05 and 0.1.2 dated 2017-05-30

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Package forestFloor updated to version 1.11.1 with previous version 1.9.5 dated 2016-06-01

Title: Visualizes Random Forests with Feature Contributions
Description: Form visualizations of high dimensional mapping structures of random forests and feature contributions.
Author: Soeren Havelund Welling
Maintainer: Soeren Havelund Welling <SORHAWELL@GMAIL.COM>

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Package dgo updated to version 0.2.10 with previous version 0.2.9 dated 2017-05-22

Title: Dynamic Estimation of Group-Level Opinion
Description: Fit dynamic group-level IRT and MRP models from individual or aggregated item response data. This package handles common preprocessing tasks and extends functions for inspecting results, poststratification, and quick iteration over alternative models.
Author: James Dunham [aut, cre], Devin Caughey [aut], Christopher Warshaw [aut]
Maintainer: James Dunham <james@jdunham.io>

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Package antaresRead updated to version 1.1.3 with previous version 1.1.2 dated 2017-04-20

Title: Import, Manipulate and Explore the Results of an Antares Simulation
Description: Import, manipulate and explore results generated by Antares, a powerful software developed by RTE to simulate and study electric power systems (more information about Antares here: <https://antares.rte-france.com>).
Author: Francois Guillem [aut, cre], Jalal-Edine ZAWAM [ctb], RTE [cph]
Maintainer: Francois Guillem <francois.guillem@rte-france.com>

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Package vfcp updated to version 1.1.0 with previous version 0.1.0 dated 2017-05-15

Title: Computation of v Values for U and Copula C(U, v)
Description: Computation the value of one of two uniformly distributed marginals if the copula probability value is known and the value of the second marginal is also known. Computation and plotting corresponding cumulative distribution function or survival function.
Author: Josef Brejcha
Maintainer: Josef Brejcha <brchjo@gmail.com>

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Package simmer updated to version 3.6.2 with previous version 3.6.1 dated 2017-03-31

Title: Discrete-Event Simulation for R
Description: A process-oriented and trajectory-based Discrete-Event Simulation (DES) package for R. It is designed as a generic yet powerful framework. The architecture encloses a robust and fast simulation core written in C++ with automatic monitoring capabilities. It provides a rich and flexible R API that revolves around the concept of trajectory, a common path in the simulation model for entities of the same type.
Author: Iñaki Ucar [aut, cph, cre], Bart Smeets [aut, cph]
Maintainer: Iñaki Ucar <i.ucar86@gmail.com>

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Package cocoreg updated to version 0.1.1 with previous version 0.1.0 dated 2016-05-04

Title: Extract Shared Variation in Collections of Data Sets Using Regression Models
Description: The algorithm extracts shared variation from a collection of data sets using regression models.
Author: Jussi Korpela [aut, cre], Andreas Henelius [aut], Finnish Institute of Occupational Health [cph]
Maintainer: Jussi Korpela <jussi.korpela@iki.fi>

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Package SIDES updated to version 1.11 with previous version 1.10 dated 2017-01-20

Title: Subgroup Identification Based on Differential Effect Search
Description: Provides function to apply "Subgroup Identification based on Differential Effect Search" (SIDES) method proposed by Lipkovich et al. (2011) <doi:10.1002/sim.4289>.
Author: Marie-Karelle Riviere
Maintainer: Marie-Karelle Riviere <eldamjh@gmail.com>

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New package processx with initial version 2.0.0
Package: processx
Title: Execute and Control System Processes
Version: 2.0.0
Author: Gábor Csárdi
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>
Description: Portable tools to run system processes in the background. It can check if a background process is running; wait on a background process to finish; get the exit status of finished processes; kill background processes and their children; restart processes. It can read the standard output and error of the processes, using non-blocking connections. 'processx' can poll a process for standard output or error, with a timeout. It can also poll several processes at once.
License: MIT + file LICENSE
LazyData: true
URL: https://github.com/r-pkgs/processx#readme
BugReports: https://github.com/r-pkgs/processx/issues
RoxygenNote: 6.0.1.9000
Suggests: covr, testthat, withr
Imports: assertthat, crayon, debugme, R6, utils
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2017-05-30 08:46:07 UTC; gaborcsardi
Repository: CRAN
Date/Publication: 2017-05-30 09:44:28 UTC

More information about processx at CRAN
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Package leaflet.minicharts updated to version 0.3.1 with previous version 0.3.0 dated 2017-05-22

Title: Mini Charts for Interactive Maps
Description: Add and modify small charts on an interactive map created with package 'leaflet'. These charts can be used to represent at same time multiple variables on a single map.
Author: Francois Guillem [aut, cre], Jalal-Edine ZAWAM [ctb], RTE [cph]
Maintainer: Francois Guillem <francois.guillem@rte-france.com>

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Package Epi updated to version 2.15 with previous version 2.12 dated 2017-04-16

Title: A Package for Statistical Analysis in Epidemiology
Description: Functions for demographic and epidemiological analysis in the Lexis diagram, i.e. register and cohort follow-up data, in particular representation, manipulation and simulation of multi state data - the Lexis suite of functions, which includes interfaces to 'mstate', 'etm' and 'cmprsk' packages. Also contains functions for Age-Period-Cohort and Lee-Carter modeling and a function for interval censored data and some useful functions for tabulation and plotting, as well as a number of epidemiological data sets.
Author: Bendix Carstensen [aut, cre], Martyn Plummer [aut], Esa Laara [ctb], Michael Hills [ctb]
Maintainer: Bendix Carstensen <b@bxc.dk>

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Package comtradr (with last version 0.0.1) was removed from CRAN

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

2017-04-05 0.0.1

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New package quadprogXT with initial version 0.0.1
Package: quadprogXT
Title: Quadratic Programming with Absolute Value Constraints
Version: 0.0.1
Authors@R: person("Bob", "Harlow", email = "rharlow86@gmail.com",role = c("aut", "cre"))
Description: Extends the quadprog package to solve quadratic programs with absolute value constraints and absolute values in the objective function.
Depends: R (>= 3.3.2)
Imports: quadprog
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Suggests: testthat
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-05-29 18:24:40 UTC; bob
Author: Bob Harlow [aut, cre]
Maintainer: Bob Harlow <rharlow86@gmail.com>
Repository: CRAN
Date/Publication: 2017-05-30 04:56:39 UTC

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Package pbmcapply updated to version 1.2.2 with previous version 1.2.1 dated 2017-02-05

Title: Tracking the Progress of Mc*pply with Progress Bar
Description: A light-weight package helps you track and visualize the progress of parallel version of vectorized R functions (mc*apply). Parallelization (mc.core > 1) works only on *nix (Linux, Unix such as macOS) system due to the lack of fork() functionality, which is essential for mc*apply, on Windows.
Author: Kevin Kuang (aut), Francesco Napolitano (ctb)
Maintainer: Kevin kuang <kvn.kuang@mail.utoronto.ca>

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Package Ckmeans.1d.dp updated to version 4.2.0 with previous version 4.0.1 dated 2017-02-16

Title: Optimal and Fast Univariate Clustering
Description: A fast dynamic programming algorithmic framework to achieve optimal univariate k-means, k-median, and k-segments clustering. Minimizing the sum of respective within-cluster distances, the algorithms guarantee optimality and reproducibility. Their advantage over heuristic clustering algorithms in efficiency and accuracy is increasingly pronounced as the number of clusters k increases. Weighted k-means and unweighted k-segments algorithms can also optimally segment time series and perform peak calling. An auxiliary function generates histograms that are adaptive to patterns in data. This package provides a powerful alternative to heuristic methods for univariate data analysis.
Author: Joe Song [aut, cre], Haizhou Wang [aut]
Maintainer: Joe Song <joemsong@cs.nmsu.edu>

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Package burnr updated to version 0.2.0 with previous version 0.1.2 dated 2017-02-08

Title: Advanced Fire History Analysis in R
Description: Basic tools to analyze forest fire history data (e.g. FHX2) in R.
Author: Steven Malevich [aut, cre], Christopher Guiterman [ctb], Ellis Margolis [ctb]
Maintainer: Steven Malevich <malevich@email.arizona.edu>

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Package mdpeer updated to version 1.0.1 with previous version 0.1.0 dated 2016-11-25

Title: Graph-Constrained Regression with Enhanced Regularization Parameters Selection
Description: Provides graph-constrained regression methods in which regularization parameters are selected automatically via estimation of equivalent Linear Mixed Model formulation. 'riPEER' (ridgified Partially Empirical Eigenvectors for Regression) method employs a penalty term being a linear combination of graph-originated and ridge-originated penalty terms, whose two regularization parameters are ML estimators from corresponding Linear Mixed Model solution; a graph-originated penalty term allows imposing similarity between coefficients based on graph information given whereas additional ridge-originated penalty term facilitates parameters estimation: it reduces computational issues arising from singularity in a graph-originated penalty matrix and yields plausible results in situations when graph information is not informative. 'riPEERc' (ridgified Partially Empirical Eigenvectors for Regression with constant) method utilizes addition of a diagonal matrix multiplied by a predefined (small) scalar to handle the non-invertibility of a graph Laplacian matrix. 'vrPEER' (variable reducted PEER) method performs variable-reduction procedure to handle the non-invertibility of a graph Laplacian matrix.
Author: Marta Karas [aut, cre], Damian Brzyski [ctb], Jaroslaw Harezlak [ctb]
Maintainer: Marta Karas <marta.karass@gmail.com>

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Package gamlss.spatial updated to version 1.3.2 with previous version 1.3.1 dated 2016-06-19

Title: Spatial Terms in Generalized Additive Models for Location Scale and Shape Models
Description: It allows us to fit Gaussian Markov Random Field within the Generalized Additive Models for Location Scale and Shape algorithms.
Author: Fernanda De Bastiani [aut, cre, cph], Mikis Stasinopoulos [aut], Bob Rigby [aut]
Maintainer: Fernanda De Bastiani <fernandadebastiani@gmail.com>

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