Title: Command Line Option Parser
Description: A command line parser inspired by Python's 'optparse' library to
be used with Rscript to write "#!" shebang scripts that accept short and
long flag/options.
Author: Trevor L Davis [aut, cre],
Allen Day [ctb] (Some documentation and examples ported from the getopt
package.),
Python Software Foundation [ctb] (Some documentation from the optparse
Python module.),
Steve Lianoglou [ctb],
Jim Nikelski [ctb],
Kirill Müller [ctb],
Peter Humburg [ctb],
Rich FitzJohn [ctb],
Gyu Jin Choi [ctb]
Maintainer: Trevor L Davis <trevor.l.davis@gmail.com>
Diff between optparse versions 1.6.2 dated 2019-04-02 and 1.6.4 dated 2019-09-16
DESCRIPTION | 6 +-- MD5 | 12 +++--- NEWS.md | 14 +++++-- R/optparse.R | 28 ++++++++++----- README.md | 76 ++++++++++++++++++----------------------- inst/doc/optparse.html | 50 +++++++++++++------------- tests/testthat/test-optparse.R | 9 +++- 7 files changed, 105 insertions(+), 90 deletions(-)
Title: Parameter-Free Domain-Agnostic Season Length Detection in Time
Series
Description: Spectral and Average Autocorrelation Zero Distance Density
('sazed') is a method for estimating the season length of a
seasonal time series. 'sazed' is aimed at practitioners, as it employs only
domain-agnostic preprocessing and does not depend on parameter tuning or
empirical constants. The computation of 'sazed' relies on the efficient
autocorrelation computation methods suggested by Thibauld Nion (2012, URL:
<http://www.tibonihoo.net/literate_musing/autocorrelations.html>) and by
Bob Carpenter (2012, URL:
<https://lingpipe-blog.com/2012/06/08/autocorrelation-fft-kiss-eigen/>).
Author: Maximilian Toller [aut],
Tiago Santos [aut, cre],
Roman Kern [aut]
Maintainer: Tiago Santos <teixeiradossantos@tugraz.at>
Diff between sazedR versions 2.0.0 dated 2019-04-26 and 2.0.1 dated 2019-09-16
DESCRIPTION | 7 ++++--- MD5 | 7 ++++--- NEWS.md | 7 ++++++- README.md | 6 +++--- inst |only 5 files changed, 17 insertions(+), 10 deletions(-)
Title: Text Analysis of the US Code of Federal Regulations
Description: The Code of Federal Regulations (CFR) annual edition is the codification
of the general and permanent rules published in the Federal Register by the departments
and agencies of the Federal Government of the United States of America. Simply, the
'fedregs' package facilitates word processing and sentiment analysis of the CFR using tidy
principles. Note: According to the Code of Federal Regulations XML Rendition User Guide Document:
"In general, there are no restrictions on re-use of information in Code of Federal Regulations
material because U.S. Government works are not subject to copyright. OFR and GPO do not
restrict downstream uses of Code of Federal Regulations data, except that independent providers
should be aware that only the OFR and GPO are entitled to represent that they are the providers
of the official versions of the Code of Federal Regulations and related Federal Register
publications."
Author: Scott Large [cre, aut]
Maintainer: Scott Large <scott.large@noaa.gov>
Diff between fedregs versions 0.1.1 dated 2019-02-04 and 1.0.0 dated 2019-09-16
fedregs-0.1.1/fedregs/man/cfr_urls.Rd |only fedregs-1.0.0/fedregs/DESCRIPTION | 12 fedregs-1.0.0/fedregs/MD5 | 19 - fedregs-1.0.0/fedregs/NAMESPACE | 7 fedregs-1.0.0/fedregs/NEWS.md | 7 fedregs-1.0.0/fedregs/R/fedregs.r | 8 fedregs-1.0.0/fedregs/R/functions.R | 255 ++++++-------------- fedregs-1.0.0/fedregs/man/cfr_part.Rd | 19 - fedregs-1.0.0/fedregs/man/cfr_text.Rd | 4 fedregs-1.0.0/fedregs/man/numextract.Rd | 6 fedregs-1.0.0/fedregs/tests/testthat/test-fedregs.R | 156 ++++++------ 11 files changed, 207 insertions(+), 286 deletions(-)
Title: Calculate Power and Sample Size with Beta Regression
Description: Power calculations are a critical component of any research study to determine the
minimum sample size necessary to detect differences between multiple groups.
Researchers often work with data taking the form of proportions that can be modeled with
a beta distribution. Here we present an R package, 'BetaPASS', that perform power and
sample size calculations for data following a beta distribution with comparative
nonparametric output. This package allows flexibility with multiple options for link
functions to fit the data and graphing functionality for visual comparisons.
Author: Jinpu Li [aut, cre],
Ryan Knigge [aut],
Emily Leary [aut]
Maintainer: Jinpu Li <lijinp@health.missouri.edu>
Diff between BetaPASS versions 1.0-1 dated 2019-07-23 and 1.1-1 dated 2019-09-16
BetaPASS-1.0-1/BetaPASS/R/plot_betapower.R |only BetaPASS-1.0-1/BetaPASS/R/plot_samplesize.R |only BetaPASS-1.0-1/BetaPASS/man/plot_betapower.Rd |only BetaPASS-1.0-1/BetaPASS/man/plot_samplesize.Rd |only BetaPASS-1.1-1/BetaPASS/DESCRIPTION | 14 BetaPASS-1.1-1/BetaPASS/MD5 | 26 - BetaPASS-1.1-1/BetaPASS/NAMESPACE | 9 BetaPASS-1.1-1/BetaPASS/R/betapower.R | 448 ++++++++++++------------- BetaPASS-1.1-1/BetaPASS/R/samplesize.R | 444 ++++++++++++++---------- BetaPASS-1.1-1/BetaPASS/build/vignette.rds |binary BetaPASS-1.1-1/BetaPASS/inst/doc/BetaPASS.R | 12 BetaPASS-1.1-1/BetaPASS/inst/doc/BetaPASS.Rmd | 12 BetaPASS-1.1-1/BetaPASS/inst/doc/BetaPASS.html | 143 ++----- BetaPASS-1.1-1/BetaPASS/man/betapower.Rd | 62 ++- BetaPASS-1.1-1/BetaPASS/man/samplesize.Rd | 49 +- BetaPASS-1.1-1/BetaPASS/vignettes/BetaPASS.Rmd | 12 16 files changed, 644 insertions(+), 587 deletions(-)
Title: Flights that Departed NYC in 2013
Description: Airline on-time data for all flights departing NYC
in 2013. Also includes useful 'metadata' on airlines, airports,
weather, and planes.
Author: Hadley Wickham [aut, cre],
RStudio [cph]
Maintainer: Hadley Wickham <hadley@rstudio.com>
Diff between nycflights13 versions 1.0.0 dated 2018-06-26 and 1.0.1 dated 2019-09-16
DESCRIPTION | 27 ++++++++++++++++----------- MD5 | 30 +++++++++++++++--------------- NEWS.md | 7 +++++++ R/airlines.R | 6 +++--- R/airport.R | 21 +++++++++++---------- R/flights.R | 26 +++++++++++++------------- R/planes.R | 17 +++++++++-------- R/weather.R | 24 ++++++++++++------------ README.md | 9 ++++++--- data/airports.rda |binary data/weather.rda |binary man/airlines.Rd | 6 +++--- man/airports.Rd | 21 +++++++++++---------- man/flights.Rd | 26 +++++++++++++------------- man/planes.Rd | 17 +++++++++-------- man/weather.Rd | 24 ++++++++++++------------ 16 files changed, 140 insertions(+), 121 deletions(-)
Title: Data Visualisation Using an HTML Page and 'D3.js'
Description: Gives access to data visualisation methods that are relevant from the statistician's point of view. Using 'D3''s existing data visualisation tools to empower R language and environment. The throw chart method is a line chart used to illustrate paired data sets (such as before-after, male-female).
Author: Timothy Bell [aut, cre],
Christophe Genolini [aut, ths]
Maintainer: Timothy Bell <horia.yeb@gmail.com>
Diff between DataViz versions 0.2.7 dated 2019-07-05 and 0.2.8 dated 2019-09-16
DESCRIPTION | 8 ++++---- MD5 | 31 ++++++++++++++++++++++++------- R/RcppExports.R | 4 ++++ R/forcelayout.R |only R/r_forcelayout.R |only R/r_throwchart.R | 8 +++++++- R/throwchart.R | 15 +++++++++++---- data/Workweek.RData |only data/weekschedule.RData |only inst/extdata/DataForceLayout.js |only inst/extdata/img |only inst/extdata/indexForceLayout.html |only inst/extdata/js |only man/DataViz-package.Rd | 1 + man/forcelayout.Rd |only man/r_forcelayout.Rd |only man/rcpp_forcelayout.Rd |only man/weekschedule.Rd |only man/workweek.Rd |only src/RcppExports.cpp | 12 ++++++++++++ src/rcpp_forcelayout.cpp |only src/rcpp_throwchart.cpp | 15 +++++++++++++-- 22 files changed, 76 insertions(+), 18 deletions(-)
Title: API Wrapper for 'US Energy Information Administration' Open Data
Description: Provides API access to data from the 'US Energy Information Administration' ('EIA') <https://www.eia.gov/>.
Use of the API requires a free API key obtainable at <https://www.eia.gov/opendata/register.php>.
The package includes functions for searching 'EIA' data categories and importing time series and geoset time series datasets.
Datasets returned by these functions are provided in a tidy format or alternatively in more raw form.
It also offers helper functions for working with 'EIA' date strings and time formats and for inspecting different summaries of series metadata.
The package also provides control over API key storage and caching of API request results.
Author: Matthew Leonawicz [aut, cre] (<https://orcid.org/0000-0001-9452-2771>),
E Source [cph, fnd]
Maintainer: Matthew Leonawicz <matt_leonawicz@esource.com>
Diff between eia versions 0.3.2 dated 2019-07-25 and 0.3.3 dated 2019-09-16
DESCRIPTION | 8 ++++---- MD5 | 28 ++++++++++++++-------------- NAMESPACE | 1 + NEWS.md | 5 +++++ R/eia.R | 11 +++++++++-- R/key.R | 2 +- R/series.R | 42 ++++++++++++++++++++++++++++++++++++++++++ README.md | 37 ++++++++++++++++++++++++------------- inst/WORDLIST | 2 ++ inst/doc/eia-nokey.Rmd | 2 +- inst/doc/eia-nokey.html | 8 ++++++-- man/eia_key.Rd | 2 +- man/eia_series_metadata.Rd | 12 ++++++++++++ tests/testthat/test-series.R | 14 +++++++++++++- vignettes/eia-nokey.Rmd | 2 +- 15 files changed, 136 insertions(+), 40 deletions(-)
Title: Distances on Directed Graphs
Description: Distances on dual-weighted directed graphs using priority-queue
shortest paths (Padgham (2019) <doi:10.32866/6945>). Weighted directed
graphs have weights from A to B which may differ from those from B to A.
Dual-weighted directed graphs have two sets of such weights. A canonical
example is a street network to be used for routing in which routes are
calculated by weighting distances according to the type of way and mode of
transport, yet lengths of routes must be calculated from direct distances.
Author: Mark Padgham [aut, cre],
Andreas Petutschnig [aut],
Robin Lovelace [ctb],
Andrew Smith [ctb],
Malcolm Morgan [ctb],
Shane Saunders [cph] (Original author of included code for priority
heaps)
Maintainer: Mark Padgham <mark.padgham@email.com>
Diff between dodgr versions 0.2.0 dated 2019-06-05 and 0.2.1 dated 2019-09-16
DESCRIPTION | 6 MD5 | 96 ++++---- NAMESPACE | 4 NEWS.md | 16 + R/RcppExports.R | 123 ++++++----- R/dists.R | 4 R/dodgr-package.r | 20 - R/flows.R | 62 ++++- R/fund-cycles.R | 36 +-- R/graph-contraction.R | 52 ++-- R/graph-conversion.R | 8 R/graph-functions-misc.R | 16 - R/graph-functions.R | 10 R/iso.R |only R/utils.R | 19 + R/weight-streetnet-times.R | 32 +- R/weight-streetnet.R | 51 ++-- R/weighting_profiles.R | 3 build/vignette.rds |binary data/weighting_profiles.rda |binary inst/doc/benchmark.html | 88 ++++---- inst/doc/dodgr.R | 68 ++---- inst/doc/dodgr.Rmd | 346 +++++++++++++++++--------------- inst/doc/dodgr.html | 305 ++++++++++++++-------------- inst/doc/times.html | 145 +++++++------ man/dodgr_cache_off.Rd | 5 man/dodgr_cache_on.Rd |only man/dodgr_contract_graph.Rd | 12 - man/dodgr_flows_aggregate.Rd | 8 man/dodgr_flows_disperse.Rd | 18 + man/dodgr_full_cycles.Rd | 2 man/dodgr_isochrones.Rd |only man/dodgr_isodists.Rd |only man/dodgr_isoverts.Rd |only man/match_points_to_graph.Rd | 2 man/match_pts_to_graph.Rd | 2 man/os_roads_bristol.Rd | 20 - man/weight_streetnet.Rd | 7 src/Makevars | 4 src/Makevars.win | 4 src/RcppExports.cpp | 110 +++++----- src/flows.cpp |only src/flows.h |only src/fund-cycles.h | 6 src/pathfinders.cpp | 43 ++++ src/pathfinders.h | 6 src/run_sp.cpp | 460 ++++++++++++------------------------------- src/run_sp.h | 20 - tests/testthat/test-cache.R |only tests/testthat/test-flows.R | 26 +- tests/testthat/test-iso.R |only tests/testthat/test-sc.R | 10 vignettes/dodgr.Rmd | 346 +++++++++++++++++--------------- vignettes/hampi-flowmap.png |only 54 files changed, 1352 insertions(+), 1269 deletions(-)
Title: Operationalizing Social Determinants of Health Data for
Researchers
Description: Accesses raw data via API and calculates social
determinants of health measures for user-specified locations in the
US, returning them in tidyverse- and sf-compatible data frames.
Author: Nik Krieger [aut, cre],
Jarrod Dalton [aut],
Cindy Wang [aut],
Adam Perzynski [aut],
National Institutes of Health/National Institute on Aging [fnd] (The
development of this software package was supported by a research
grant from the National Institutes of Health/National Institute on
Aging, (Principal Investigators: Jarrod E. Dalton, PhD and Adam T.
Perzynski, PhD; Grant Number: 5R01AG055480-02). All of its contents
are solely the responsibility of the authors and do not necessarily
represent the official views of the NIH.)
Maintainer: Nik Krieger <nk@case.edu>
Diff between sociome versions 1.0.0 dated 2019-08-02 and 1.2.0 dated 2019-09-16
DESCRIPTION | 19 - MD5 | 40 +-- NEWS.md | 29 ++ R/calculate_adi.R | 272 +++++++++++++--------- R/data_documentation.R | 4 R/get_adi.R | 177 +++++++++----- R/get_geoids.R | 2 R/sysdata.rda |binary R/validation.R | 8 data/acs_vars.rda |binary data/decennial_vars.rda |binary inst/extdata/census_variables_dataset_creator.Rmd | 59 ++++ man/acs_vars.Rd | 2 man/calculate_adi.Rd | 28 +- man/decennial_vars.Rd | 2 man/get_adi.Rd | 143 ++++++++--- man/get_geoids.Rd | 2 tests/testthat/test_arg_tibble_acs.R | 65 +++-- tests/testthat/test_arg_tibble_decennial1990.R |only tests/testthat/test_arg_tibble_decennial2000.R | 48 ++- tests/testthat/test_arg_tibble_decennial2010.R | 60 +++- tests/testthat/test_calculate_adi.R |only 22 files changed, 651 insertions(+), 309 deletions(-)
Title: Mixture Models with Heterogeneous and (Partially) Missing Data
Description: Mixture Composer <https://github.com/modal-inria/MixtComp> is a project to build mixture models with
heterogeneous data sets and partially missing data management.
It includes 8 models for real, categorical, counting, functional and ranking data.
Author: Vincent Kubicki [aut],
Christophe Biernacki [aut],
Quentin Grimonprez [aut, cre],
Matthieu Marbac-Lourdelle [ctb],
Étienne Goffinet [ctb],
Serge Iovleff [ctb]
Maintainer: Quentin Grimonprez <quentin.grimonprez@inria.fr>
Diff between RMixtComp versions 4.0.1 dated 2019-09-04 and 4.0.2 dated 2019-09-16
DESCRIPTION | 8 ++++---- MD5 | 14 +++++++------- NEWS | 4 ++++ R/MIXTCOMP_methods.R | 2 +- R/PLOT_plotCrit.R | 7 ++++--- man/plot.MixtCompLearn.Rd | 2 +- man/plotCrit.Rd | 7 ++++--- tests/testthat/test.runWrapper.R | 11 +++++++---- 8 files changed, 32 insertions(+), 23 deletions(-)
Title: Plackett-Luce Models for Rankings
Description: Functions to prepare rankings data and fit the Plackett-Luce model
jointly attributed to Plackett (1975) <doi:10.2307/2346567> and Luce
(1959, ISBN:0486441369). The standard Plackett-Luce model is generalized
to accommodate ties of any order in the ranking. Partial rankings, in which
only a subset of items are ranked in each ranking, are also accommodated in
the implementation. Disconnected/weakly connected networks implied by the
rankings may be handled by adding pseudo-rankings with a hypothetical item.
Optionally, a multivariate normal prior may be set on the log-worth
parameters and ranker reliabilities may be incorporated as proposed by
Raman and Joachims (2014) <doi:10.1145/2623330.2623654>. Maximum a
posteriori estimation is used when priors are set. Methods are provided to
estimate standard errors or quasi-standard errors for inference as well as
to fit Plackett-Luce trees. See the package website or vignette for further
details.
Author: Heather Turner [aut, cre] (<https://orcid.org/0000-0002-1256-3375>),
Ioannis Kosmidis [aut] (<https://orcid.org/0000-0003-1556-0302>),
David Firth [aut] (<https://orcid.org/0000-0003-0302-2312>),
Jacob van Etten [ctb] (<https://orcid.org/0000-0001-7554-2558>)
Maintainer: Heather Turner <ht@heatherturner.net>
Diff between PlackettLuce versions 0.2-8 dated 2019-09-05 and 0.2-9 dated 2019-09-16
DESCRIPTION | 12 +-- MD5 | 73 ++++++++++++-------- NAMESPACE | 1 NEWS.md | 12 +++ R/PlackettLuce.R | 19 ++++- R/aggregate.rankings.R | 4 - R/beans.R | 4 - R/nascar.R | 2 R/pltree-summaries.R | 2 R/preflib.R | 108 ++++++++++++++++++++++-------- R/pudding.R | 14 +++ R/rankings.R | 22 +++++- R/vcov.R | 4 - README.md | 15 +++- TODO | 16 ++++ inst/WORDLIST | 10 ++ inst/doc/Overview.R | 15 +++- inst/doc/Overview.Rmd | 32 ++++---- inst/doc/Overview.html | 54 ++++++++------- inst/extdata |only man/PlackettLuce.Rd | 15 +++- man/beans.Rd | 4 - man/figures/always-loses-1.png |binary man/nascar.Rd | 2 man/pltree-summaries.Rd | 2 man/preflib.Rd | 19 +++++ man/pudding.Rd | 14 +++ tests/testthat/Rplots.pdf |binary tests/testthat/outputs/soc.rds |only tests/testthat/outputs/soc_rankings.rds |only tests/testthat/outputs/soi.rds |only tests/testthat/outputs/soi_rankings.rds |only tests/testthat/outputs/toc.rds |only tests/testthat/outputs/toc_rankings.rds |only tests/testthat/outputs/toi.rds |only tests/testthat/outputs/toi_rankings.rds |only tests/testthat/test-aggregated_rankings.R |only tests/testthat/test-preflib.R |only tests/testthat/test-vcov.R | 52 +++++++++++++- vignettes/Overview.Rmd | 32 ++++---- vignettes/plackettluce.bib | 13 +++ 41 files changed, 423 insertions(+), 149 deletions(-)
Title: Methods for Graphical Models and Causal Inference
Description: Functions for causal structure
learning and causal inference using graphical models. The main algorithms
for causal structure learning are PC (for observational data without hidden
variables), FCI and RFCI (for observational data with hidden variables),
and GIES (for a mix of data from observational studies
(i.e. observational data) and data from experiments
involving interventions (i.e. interventional data) without hidden
variables). For causal inference the IDA algorithm, the Generalized
Backdoor Criterion (GBC), the Generalized Adjustment Criterion (GAC)
and some related functions are implemented. Functions for incorporating
background knowledge are provided.
Author: Markus Kalisch [aut, cre],
Alain Hauser [aut],
Martin Maechler [aut],
Diego Colombo [ctb],
Doris Entner [ctb],
Patrik Hoyer [ctb],
Antti Hyttinen [ctb],
Jonas Peters [ctb],
Nicoletta Andri [ctb],
Emilija Perkovic [ctb],
Preetam Nandy [ctb],
Philipp Ruetimann [ctb],
Daniel Stekhoven [ctb],
Manuel Schuerch [ctb],
Marco Eigenmann [ctb]
Maintainer: Markus Kalisch <kalisch@stat.math.ethz.ch>
Diff between pcalg versions 2.6-5 dated 2019-08-27 and 2.6-6 dated 2019-09-16
DESCRIPTION | 8 ++++---- MD5 | 8 ++++---- inst/doc/pcalgDoc.pdf |binary inst/doc/vignette2018.pdf |binary man/optAdjSet.Rd | 31 +++++++++++++++++++------------ 5 files changed, 27 insertions(+), 20 deletions(-)
Title: Targeted Stable Balancing Weights Using Optimization
Description: Use optimization to estimate weights that balance covariates for binary, multinomial, and continuous treatments in the spirit of Zubizarreta (2015) <doi:10.1080/01621459.2015.1023805>. The degree of balance can be specified for each covariate. In addition, sampling weights can be estimated that allow a sample to generalize to a population specified with given target moments of covariates.
Author: Noah Greifer [aut, cre]
Maintainer: Noah Greifer <noah.greifer@gmail.com>
Diff between optweight versions 0.2.4 dated 2019-09-03 and 0.2.5 dated 2019-09-16
DESCRIPTION | 10 +- MD5 | 26 +++--- NAMESPACE | 2 NEWS.md | 4 + README.md | 184 ++++++++++++++++++++++++++++++++++++++++------- build/partial.rdb |binary man/check.targets.Rd | 15 --- man/check.tols.Rd | 22 ----- man/optweight.Rd | 17 +--- man/optweight.fit.Rd | 13 --- man/optweight.svy.Rd | 27 ------ man/optweight.svy.fit.Rd | 21 ----- man/plot.optweight.Rd | 9 -- man/summary.optweight.Rd | 11 -- 14 files changed, 194 insertions(+), 167 deletions(-)
Title: Bayesian Model Averaging for Random and Fixed Effects
Meta-Analysis
Description: Computes the posterior model probabilities for standard meta-analysis models
(null model vs. alternative model assuming either fixed- or random-effects, respectively).
These posterior probabilities are used to estimate the overall mean effect size
as the weighted average of the mean effect size estimates of the random- and
fixed-effect model as proposed by Gronau, Van Erp, Heck, Cesario, Jonas, &
Wagenmakers (2017, <doi:10.1080/23743603.2017.1326760>). The user can define
a wide range of non-informative or informative priors for the mean effect size
and the heterogeneity coefficient. Moreover, using pre-compiled Stan models,
meta-analysis with continuous and discrete moderators with Jeffreys-Zellner-Siow (JZS)
priors can be fitted and tested. This allows to compute Bayes factors and
perform Bayesian model averaging across random- and fixed-effects meta-analysis
with and without moderators.
Author: Daniel W. Heck [aut, cre] (<https://orcid.org/0000-0002-6302-9252>),
Quentin F. Gronau [ctb]
Maintainer: Daniel W. Heck <heck@uni-mannheim.de>
Diff between metaBMA versions 0.6.1 dated 2019-07-10 and 0.6.2 dated 2019-09-16
DESCRIPTION | 13 ++--- MD5 | 61 ++++++++++++------------ NEWS | 8 +++ R/bma.R | 41 ++++++++++------ R/check_input.R | 2 R/data_list.R | 4 + R/meta_bma.R | 47 ++++++++++++------ R/meta_fixed.R | 2 R/meta_ordered.R | 70 +++++++++++++++------------- R/meta_random.R | 4 - R/plot_forest.R | 30 +++++++----- R/posterior.R | 32 +++++++++--- R/print.R | 4 - R/summary_parameters.R | 4 - inst/doc/metaBMA.html | 36 ++++++++------ man/meta_bma.Rd | 49 ++++++++++++------- man/meta_fixed.Rd | 13 +++-- man/meta_ordered.Rd | 56 +++++++++++++++------- man/meta_random.Rd | 26 ++++++---- man/plot_forest.Rd | 4 + src/stan_files/fixed_jzs.stan | 2 src/stan_files/jzs/data.stan | 2 src/stan_files/jzs/param.stan | 2 src/stan_files/jzs/target.stan | 2 src/stan_files/random_jzs.stan | 2 src/stan_files/random_jzs_dstudy.stan | 2 src/stan_files/random_ordered.stan | 6 +- tests/testthat.R | 1 tests/testthat/test_bma.R | 26 +++++----- tests/testthat/test_data_frame_evaluation.R | 6 +- tests/testthat/test_jzs.R | 18 +++---- tests/testthat/test_scheibehenne2017.R |only 32 files changed, 349 insertions(+), 226 deletions(-)
Title: Statistical Framework to Define Subgroups in Complex Datasets
Description: High-dimensional datasets that do not exhibit a clear intrinsic clustered structure pose a challenge to conventional clustering algorithms. For this reason, we developed an unsupervised framework that helps scientists to better subgroup their datasets based on visual cues, please see Gao S, Mutter S, Casey A, Makinen V-P (2019) Numero: a statistical framework to define multivariable subgroups in complex population-based datasets, Int J Epidemiology, 48:369-37, <doi:10.1093/ije/dyy113>. The framework includes the necessary functions to construct a self-organizing map of the data, to evaluate the statistical significance of the observed data patterns, and to visualize the results.
Author: Song Gao [aut],
Stefan Mutter [aut],
Aaron E. Casey [aut],
Ville-Petteri Makinen [aut, cre]
Maintainer: Ville-Petteri Makinen <vpmakine@gmail.com>
Diff between Numero versions 1.2.0 dated 2019-06-12 and 1.3.1 dated 2019-09-16
Numero-1.2.0/Numero/R/nroPrune.R |only Numero-1.2.0/Numero/README.md |only Numero-1.2.0/Numero/man/nroPrune.Rd |only Numero-1.2.0/Numero/src/nro.scriptumartistclose.cpp |only Numero-1.2.0/Numero/src/nro_circus.cpp |only Numero-1.3.1/Numero/DESCRIPTION | 10 Numero-1.3.1/Numero/MD5 | 199 +++--- Numero-1.3.1/Numero/NAMESPACE | 2 Numero-1.3.1/Numero/R/nroColorize.R | 55 - Numero-1.3.1/Numero/R/nroImpute.R | 63 + Numero-1.3.1/Numero/R/nroKmeans.R | 48 + Numero-1.3.1/Numero/R/nroLabel.R | 15 Numero-1.3.1/Numero/R/nroMatch.R | 8 Numero-1.3.1/Numero/R/nroPair.R | 5 Numero-1.3.1/Numero/R/nroPermute.R | 33 - Numero-1.3.1/Numero/R/nroPlot.R | 148 ---- Numero-1.3.1/Numero/R/nroPlot.save.R |only Numero-1.3.1/Numero/R/nroPostprocess.R | 34 - Numero-1.3.1/Numero/R/nroPreprocess.R | 11 Numero-1.3.1/Numero/R/nroSummary.R | 103 ++- Numero-1.3.1/Numero/R/nroTrain.R | 15 Numero-1.3.1/Numero/R/numero.clean.R | 1 Numero-1.3.1/Numero/R/numero.create.R | 4 Numero-1.3.1/Numero/R/numero.evaluate.R | 20 Numero-1.3.1/Numero/R/numero.plot.R | 113 ++- Numero-1.3.1/Numero/R/numero.prepare.R | 84 +- Numero-1.3.1/Numero/R/numero.quality.R | 4 Numero-1.3.1/Numero/R/numero.subgroup.R | 22 Numero-1.3.1/Numero/R/numero.summary.R | 25 Numero-1.3.1/Numero/build/vignette.rds |binary Numero-1.3.1/Numero/inst/CITATION | 10 Numero-1.3.1/Numero/inst/doc/intro.R | 112 ++- Numero-1.3.1/Numero/inst/doc/intro.html | 488 +++++++++------ Numero-1.3.1/Numero/inst/doc/intro.rmd | 178 ++++- Numero-1.3.1/Numero/inst/extcode |only Numero-1.3.1/Numero/man/nroColorize.Rd | 8 Numero-1.3.1/Numero/man/nroImpute.Rd | 7 Numero-1.3.1/Numero/man/nroKmeans.Rd | 7 Numero-1.3.1/Numero/man/nroLabel.Rd | 13 Numero-1.3.1/Numero/man/nroPair.Rd | 8 Numero-1.3.1/Numero/man/nroPermute.Rd | 4 Numero-1.3.1/Numero/man/nroPlot.Rd | 79 +- Numero-1.3.1/Numero/man/nroPostprocess.Rd | 15 Numero-1.3.1/Numero/man/nroSummary.Rd | 22 Numero-1.3.1/Numero/man/nroTrain.Rd | 6 Numero-1.3.1/Numero/man/numero.evaluate.Rd | 6 Numero-1.3.1/Numero/man/numero.plot.Rd | 18 Numero-1.3.1/Numero/man/numero.prepare.Rd | 6 Numero-1.3.1/Numero/man/numero.quality.Rd | 4 Numero-1.3.1/Numero/man/numero.subrgoup.Rd | 9 Numero-1.3.1/Numero/man/numero.summary.Rd | 13 Numero-1.3.1/Numero/src/Numero_init.c | 30 Numero-1.3.1/Numero/src/abacus.h | 2 Numero-1.3.1/Numero/src/abacus.local.h | 2 Numero-1.3.1/Numero/src/akkad.h | 2 Numero-1.3.1/Numero/src/akkad.local.h | 2 Numero-1.3.1/Numero/src/koho.engine.insert.cpp | 6 Numero-1.3.1/Numero/src/koho.engine.shuffle.cpp | 2 Numero-1.3.1/Numero/src/koho.h | 12 Numero-1.3.1/Numero/src/koho.local.h | 15 Numero-1.3.1/Numero/src/koho.model.configure.cpp | 3 Numero-1.3.1/Numero/src/koho.model.insert.cpp | 3 Numero-1.3.1/Numero/src/koho.model.train.cpp | 83 +- Numero-1.3.1/Numero/src/medusa.h | 2 Numero-1.3.1/Numero/src/medusa.local.h | 2 Numero-1.3.1/Numero/src/medusa.time2text.cpp | 10 Numero-1.3.1/Numero/src/nro.h | 9 Numero-1.3.1/Numero/src/nro.reals2topology.cpp | 26 Numero-1.3.1/Numero/src/nro_circus_paint.cpp |only Numero-1.3.1/Numero/src/nro_circus_show.cpp |only Numero-1.3.1/Numero/src/nro_circus_write.cpp |only Numero-1.3.1/Numero/src/nro_colorize.cpp | 37 - Numero-1.3.1/Numero/src/nro_diffuse.cpp | 4 Numero-1.3.1/Numero/src/nro_figure.cpp | 26 Numero-1.3.1/Numero/src/nro_impute.cpp | 108 +-- Numero-1.3.1/Numero/src/nro_kohonen.cpp | 12 Numero-1.3.1/Numero/src/nro_label.cpp | 55 - Numero-1.3.1/Numero/src/nro_pair.cpp | 87 ++ Numero-1.3.1/Numero/src/nro_permute.cpp | 19 Numero-1.3.1/Numero/src/nro_train.cpp | 29 Numero-1.3.1/Numero/src/nro_webpage.cpp |only Numero-1.3.1/Numero/src/punos.h | 65 - Numero-1.3.1/Numero/src/punos.local.h | 4 Numero-1.3.1/Numero/src/punos.topology.cpp | 61 - Numero-1.3.1/Numero/src/punos.topology.distance.cpp | 8 Numero-1.3.1/Numero/src/punos.topology.highlight.cpp | 48 - Numero-1.3.1/Numero/src/punos.topology.import.cpp | 24 Numero-1.3.1/Numero/src/punos.topology.interpolate.cpp | 32 Numero-1.3.1/Numero/src/punos.topology.operator[].cpp | 4 Numero-1.3.1/Numero/src/punos.topology.paint.cpp | 144 +--- Numero-1.3.1/Numero/src/punos.topology.rewire.cpp | 99 ++- Numero-1.3.1/Numero/src/punos.topology.save.cpp | 18 Numero-1.3.1/Numero/src/punos.topology.write.cpp | 37 - Numero-1.3.1/Numero/src/scriptum.artist.close.cpp |only Numero-1.3.1/Numero/src/scriptum.artist.cpp | 2 Numero-1.3.1/Numero/src/scriptum.artistbuffer.prolog.cpp | 30 Numero-1.3.1/Numero/src/scriptum.colormap.cpp | 6 Numero-1.3.1/Numero/src/scriptum.frame.flush.cpp | 2 Numero-1.3.1/Numero/src/scriptum.frame.group.cpp | 22 Numero-1.3.1/Numero/src/scriptum.frame.stylize.cpp | 12 Numero-1.3.1/Numero/src/scriptum.h | 32 Numero-1.3.1/Numero/src/scriptum.local.h | 2 Numero-1.3.1/Numero/src/scriptum.style.cpp | 7 Numero-1.3.1/Numero/src/scriptum.style2code.cpp | 24 Numero-1.3.1/Numero/vignettes/intro.rmd | 178 ++++- 105 files changed, 2140 insertions(+), 1344 deletions(-)
Title: Discretization and Grouping for Logistic Regression
Description: A Stochastic-Expectation-Maximization (SEM) algorithm (Celeux et al. (1995) <https://hal.inria.fr/inria-00074164>) associated with a Gibbs sampler which purpose is to learn a constrained representation for logistic regression that is called quantization (Ehrhardt et al. (2019) <arXiv:1903.08920>). Continuous features are discretized and categorical features' values are grouped to produce a better logistic regression model. Pairwise interactions between quantized features are dynamically added to the model through a Metropolis-Hastings algorithm (Hastings, W. K. (1970) <doi:10.1093/biomet/57.1.97>).
Author: Adrien Ehrhardt [aut, cre],
Vincent Vandewalle [aut],
Christophe Biernacki [ctb],
Philippe Heinrich [ctb]
Maintainer: Adrien Ehrhardt <adrien.ehrhardt@inria.fr>
Diff between glmdisc versions 0.1 dated 2019-04-04 and 0.2 dated 2019-09-16
DESCRIPTION | 10 +++--- MD5 | 36 ++++++++++++++----------- R/discretize.link.R | 2 - R/method_plot.R | 2 - R/method_predict.R | 9 ++---- R/normalizedGini.R | 2 - R/semDiscretization.R | 2 - build/vignette.rds |binary inst/doc/glmdisc.R | 2 - inst/doc/glmdisc.Rmd | 4 +- inst/doc/glmdisc.html | 72 +++++++++++++++++++++++++------------------------- man/glmdisc.Rd | 4 -- man/normalizedGini.Rd | 3 -- man/plot.Rd | 4 -- man/predict.Rd | 5 --- tests |only vignettes/glmdisc.Rmd | 4 +- 17 files changed, 78 insertions(+), 83 deletions(-)
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2019-08-20 2.0.2
2019-05-05 2.0.1
2019-04-12 2.0.0
2019-03-08 1.0.0
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2016-04-23 0.1-4
2016-04-22 0.1-3
2016-03-09 0.1-2
2016-01-15 0.1-1
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2019-02-12 1.0.6
2019-02-02 1.0.5
2019-01-11 1.0.4
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2018-11-18 0.1
Title: Create Ternary Plots
Description: Plots ternary diagrams using the standard graphics functions.
An alternative to 'ggtern', which uses the 'ggplot2' family of plotting functions.
Author: Martin R. Smith [aut, cre, cph]
(<https://orcid.org/0000-0001-5660-1727>)
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>
Diff between Ternary versions 1.1.1 dated 2019-06-14 and 1.1.2 dated 2019-09-16
Ternary-1.1.1/Ternary/inst/doc/Using-Ternary.R |only Ternary-1.1.1/Ternary/inst/doc/Using-Ternary.Rmd |only Ternary-1.1.1/Ternary/inst/doc/Using-Ternary.html |only Ternary-1.1.1/Ternary/vignettes/Using-Ternary.Rmd |only Ternary-1.1.2/Ternary/DESCRIPTION | 13 - Ternary-1.1.2/Ternary/MD5 | 84 +++++--- Ternary-1.1.2/Ternary/NEWS.md | 5 Ternary-1.1.2/Ternary/R/Contours.R | 9 Ternary-1.1.2/Ternary/R/Coordinates.R | 37 +-- Ternary-1.1.2/Ternary/R/ReleaseQuestions.R | 14 + Ternary-1.1.2/Ternary/R/Ternary-package.R |only Ternary-1.1.2/Ternary/R/TernaryPlot.R | 143 ++++++++------ Ternary-1.1.2/Ternary/R/data.R | 20 +- Ternary-1.1.2/Ternary/README.md | 19 + Ternary-1.1.2/Ternary/build/partial.rdb |binary Ternary-1.1.2/Ternary/build/vignette.rds |binary Ternary-1.1.2/Ternary/data/cbPalette15.rda |binary Ternary-1.1.2/Ternary/data/cbPalette8.rda |binary Ternary-1.1.2/Ternary/inst/doc/Ternary.R |only Ternary-1.1.2/Ternary/inst/doc/Ternary.Rmd |only Ternary-1.1.2/Ternary/inst/doc/Ternary.html |only Ternary-1.1.2/Ternary/man/ColourTernary.Rd | 7 Ternary-1.1.2/Ternary/man/Ternary-package.Rd |only Ternary-1.1.2/Ternary/man/TernaryContour.Rd | 7 Ternary-1.1.2/Ternary/man/TernaryCoords.Rd | 27 +- Ternary-1.1.2/Ternary/man/TernaryDensityContour.Rd | 7 Ternary-1.1.2/Ternary/man/TernaryPlot.Rd | 8 Ternary-1.1.2/Ternary/man/TernaryPointValues.Rd | 7 Ternary-1.1.2/Ternary/man/TriangleCentres.Rd | 5 Ternary-1.1.2/Ternary/man/XYToTernary.Rd | 6 Ternary-1.1.2/Ternary/man/cbPalette15.Rd | 13 + Ternary-1.1.2/Ternary/man/cbPalette8.Rd | 11 + Ternary-1.1.2/Ternary/tests/figs |only Ternary-1.1.2/Ternary/tests/testthat.R | 5 Ternary-1.1.2/Ternary/tests/testthat/Rplots.pdf |binary Ternary-1.1.2/Ternary/tests/testthat/test-Contours.R | 126 +++++++++++++ Ternary-1.1.2/Ternary/tests/testthat/test-Coordinates.R | 30 +++ Ternary-1.1.2/Ternary/tests/testthat/test-ternary.R | 154 ++++++++++++++-- Ternary-1.1.2/Ternary/vignettes/Ternary.Rmd |only 39 files changed, 596 insertions(+), 161 deletions(-)
Title: Handling Missing Data in Stochastic Block Models
Description: When a network is partially observed (here, NAs in the adjacency matrix rather than 1 or 0
due to missing information between node pairs), it is possible to account for the underlying process
that generates those NAs. 'missSBM' adjusts the popular stochastic block model from network data
sampled under various missing data conditions, as described in Tabouy, Barbillon and Chiquet (2019) <doi:10.1080/01621459.2018.1562934>.
Author: Julien Chiquet [aut, cre] (<https://orcid.org/0000-0002-3629-3429>),
Pierre Barbillon [aut] (<https://orcid.org/0000-0002-7766-7693>),
Timothée Tabouy [aut]
Maintainer: Julien Chiquet <julien.chiquet@inra.fr>
Diff between missSBM versions 0.2.0 dated 2019-06-08 and 0.2.1 dated 2019-09-16
DESCRIPTION | 10 ++--- MD5 | 34 ++++++++++---------- NAMESPACE | 11 ++++++ NEWS.md | 9 +++++ R/SBM-Class.R | 32 +++++++++++++++++-- R/SBM_fit-Class.R | 2 - R/SBM_sampler-Class.R | 5 ++ R/estimate.R | 8 ++++ R/missSBM_fit-Class.R | 57 ++++++++++++++++++++++++++++++++-- R/sampledNetwork-Class.R | 24 +++++++++++--- R/simulate.R | 2 + README.md | 22 +++++++++---- build/vignette.rds |binary inst/doc/case_study_war_networks.html | 12 ++++--- man/SBM_sampler.Rd | 3 + man/estimate.Rd | 8 ++++ man/sampledNetwork.Rd | 3 + man/simulate.Rd | 2 + 18 files changed, 200 insertions(+), 44 deletions(-)
Title: Generalized Linear Mixed Model Analysis via Expectation
Propagation
Description: Approximate frequentist inference for generalized linear mixed model analysis with expectation propagation used to circumvent the need for multivariate integration. In this version, the random effects can be any reasonable dimension. However, only probit mixed models with one level of nesting are supported. The methodology is described in Hall, Johnstone, Ormerod, Wand and Yu (2018) <arXiv:1805.08423v1>.
Author: Matt P. Wand [aut, cre],
James C.F. Yu [aut]
Maintainer: Matt P. Wand <matt.wand@uts.edu.au>
Diff between glmmEP versions 1.0-1 dated 2018-05-29 and 1.0-2 dated 2019-09-16
DESCRIPTION | 12 ++++++------ MD5 | 36 ++++++++++++++++++------------------ NAMESPACE | 2 ++ R/EPlogLik.r | 9 ++++----- R/glmmEP.r | 21 ++++++++++++++++----- R/glmmSimData.r | 2 +- R/zzz.r | 2 +- build/vignette.rds |binary inst/doc/manual.pdf |binary man/glmmEP.control.Rd | 4 +++- man/glmmEPvignette.Rd | 2 +- src/cpbt.f | 17 ++++++++--------- src/dgedi.f | 4 ++-- src/dgefa.f | 4 ++-- src/dgesl.f | 4 ++-- src/epllk.f | 29 ++++++++++++++--------------- src/init.c | 24 +++++++++++------------- src/kpbt.f | 6 +++--- src/zetad.f | 4 ++-- 19 files changed, 96 insertions(+), 86 deletions(-)
Title: Core Tools for Packages in the 'fable' Framework
Description: Provides tools, helpers and data structures for developing models and time series functions for 'fable' and extension packages. These tools support a consistent and tidy interface for time series modelling and analysis.
Author: Mitchell O'Hara-Wild [aut, cre],
Rob Hyndman [aut],
Earo Wang [aut],
Di Cook [ctb],
George Athanasopoulos [ctb]
Maintainer: Mitchell O'Hara-Wild <mail@mitchelloharawild.com>
Diff between fabletools versions 0.1.0 dated 2019-08-08 and 0.1.1 dated 2019-09-16
DESCRIPTION | 23 ++++++----- MD5 | 56 ++++++++++++++-------------- NAMESPACE | 3 + NEWS.md | 19 +++++++++ R/accuracy.R | 32 ++++++++++++++-- R/aggregate.R | 45 ++++++---------------- R/broom.R | 8 +++- R/estimate.R | 2 - R/fable.R | 68 ++++++++++++++++++++-------------- R/features.R | 51 +++++++++++++++++++++---- R/forecast.R | 38 +++++++++++++------ R/model.R | 4 +- R/parse.R | 6 +-- R/plot.R | 2 - R/quantile.R | 6 ++- R/reconciliation.R | 31 ++++++++++----- R/transform.R | 7 ++- R/utils.R | 51 +++++++++++++++++++------ README.md | 9 ++++ build/fabletools.pdf |binary inst/WORDLIST | 3 + man/distribution_accuracy_measures.Rd | 7 +++ man/fabletools-package.Rd | 3 + man/features.Rd | 2 - man/min_trace.Rd | 8 ++-- man/tidy.Rd | 3 + tests/testthat/test-accuracy.R | 2 - tests/testthat/test-parser.R | 5 ++ tests/testthat/test-reconciliation.R | 4 +- 29 files changed, 329 insertions(+), 169 deletions(-)
Title: Dose Response for Omics
Description: Several functions are provided for dose-response (or concentration-response) characterization from omics data. 'DRomics' is especially dedicated to omics data obtained using a typical dose-response design, favoring a great number of tested doses (or concentrations, at least 5, and the more the better) rather than a great number of replicates (no need of three replicates). 'DRomics' provides functions 1) to check, normalize and or transform data, 2) to select monotonic or biphasic significantly responding items (e.g. probes, metabolites), 3) to choose the best-fit model among a predefined family of monotonic and biphasic models to describe each selected item 4) to derive a benchmark dose or concentration and a typology of response from each fitted curve. In the available version data are supposed to be single-channel microarray data in log2, RNAseq data in raw counts or already pretreated metabolomic data in log scale. For further details see Larras et al (2018) <DOI:10.1021/acs.est.8b04752>.
Author: Marie-Laure Delignette-Muller [aut],
Elise Billoir [aut],
Floriane Larras [ctb],
Aurelie Siberchicot [aut, cre]
Maintainer: Aurelie Siberchicot <aurelie.siberchicot@univ-lyon1.fr>
Diff between DRomics versions 1.0-2 dated 2019-01-16 and 2.0-1 dated 2019-09-16
DRomics-1.0-2/DRomics/man/omicdata.Rd |only DRomics-1.0-2/DRomics/tests/example4shinyap.R |only DRomics-2.0-1/DRomics/DESCRIPTION | 11 DRomics-2.0-1/DRomics/MD5 | 67 +- DRomics-2.0-1/DRomics/NAMESPACE | 29 + DRomics-2.0-1/DRomics/R/RNAseqdata.R |only DRomics-2.0-1/DRomics/R/bmdboot.R |only DRomics-2.0-1/DRomics/R/bmdcalc.R | 92 ++- DRomics-2.0-1/DRomics/R/curvesplot.R |only DRomics-2.0-1/DRomics/R/drcfit.R | 11 DRomics-2.0-1/DRomics/R/ecdfplotwithCI.R |only DRomics-2.0-1/DRomics/R/itemselect.R | 118 +++- DRomics-2.0-1/DRomics/R/metabolomicdata.R |only DRomics-2.0-1/DRomics/R/microarraydata.R |only DRomics-2.0-1/DRomics/R/omicdata.R | 113 ---- DRomics-2.0-1/DRomics/R/util-basicandfitfunc.R | 16 DRomics-2.0-1/DRomics/R/util-plotfunc.R | 89 ++- DRomics-2.0-1/DRomics/inst/DRomics-shiny/global.R | 1 DRomics-2.0-1/DRomics/inst/DRomics-shiny/rinstall.txt | 5 DRomics-2.0-1/DRomics/inst/DRomics-shiny/server.R | 238 +++++++--- DRomics-2.0-1/DRomics/inst/DRomics-shiny/ui.R | 205 ++++++-- DRomics-2.0-1/DRomics/inst/DRomics-shiny/www/Dromics_tutorial.pdf |binary DRomics-2.0-1/DRomics/inst/DRomics-shiny/www/informations_datafile_input.txt | 4 DRomics-2.0-1/DRomics/inst/DRomics-shiny/www/informations_metabolo_pretreatment.txt |only DRomics-2.0-1/DRomics/inst/DRomics-shiny/www/informations_transfo_methods.txt |only DRomics-2.0-1/DRomics/inst/NEWS | 39 + DRomics-2.0-1/DRomics/inst/extdata/RNAseq_sample.txt |only DRomics-2.0-1/DRomics/inst/extdata/Zhou_kidney_pce.txt |only DRomics-2.0-1/DRomics/inst/extdata/metabolo_sample.txt |only DRomics-2.0-1/DRomics/man/DRomics.Rd | 51 +- DRomics-2.0-1/DRomics/man/RNAseqdata.Rd |only DRomics-2.0-1/DRomics/man/bmdboot.Rd |only DRomics-2.0-1/DRomics/man/bmdcalc.Rd | 35 - DRomics-2.0-1/DRomics/man/curvesplot.Rd |only DRomics-2.0-1/DRomics/man/drcfit.Rd | 34 + DRomics-2.0-1/DRomics/man/ecdfplotwithCI.Rd |only DRomics-2.0-1/DRomics/man/itemselect.Rd | 47 + DRomics-2.0-1/DRomics/man/metabolomicdata.Rd |only DRomics-2.0-1/DRomics/man/microarraydata.Rd |only DRomics-2.0-1/DRomics/tests/examplewithLprobit.R |only DRomics-2.0-1/DRomics/tests/examplewithRNAseq.R |only DRomics-2.0-1/DRomics/tests/examplewithmetabolomic.R |only DRomics-2.0-1/DRomics/tests/examplewithmicroarray.R |only DRomics-2.0-1/DRomics/tests/testthat/test_bmdcalc.R | 4 DRomics-2.0-1/DRomics/tests/testthat/test_drcfit.R | 4 DRomics-2.0-1/DRomics/tests/testthat/test_itemselect.R | 16 46 files changed, 814 insertions(+), 415 deletions(-)
Title: A Modern and Flexible Web Client for R
Description: The curl() and curl_download() functions provide highly
configurable drop-in replacements for base url() and download.file() with
better performance, support for encryption (https, ftps), gzip compression,
authentication, and other 'libcurl' goodies. The core of the package implements a
framework for performing fully customized requests where data can be processed
either in memory, on disk, or streaming via the callback or connection
interfaces. Some knowledge of 'libcurl' is recommended; for a more-user-friendly
web client see the 'httr' package which builds on this package with http
specific tools and logic.
Author: Jeroen Ooms [aut, cre] (<https://orcid.org/0000-0002-4035-0289>),
Hadley Wickham [ctb],
RStudio [cph]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>
Diff between curl versions 4.0 dated 2019-07-22 and 4.1 dated 2019-09-16
DESCRIPTION | 9 ++-- MD5 | 50 +++++++++++++----------- NEWS | 11 +++++ R/download.R | 9 +++- R/echo.R | 6 +- R/email.R | 8 ++- R/nslookup.R | 52 ++++++++++++++++++++++--- R/sysdata.rda |binary build/vignette.rds |binary inst/WORDLIST | 11 +++++ inst/doc/intro.html | 60 ++++++++++++++--------------- inst/doc/windows.R |only inst/doc/windows.Rmd |only inst/doc/windows.html |only man/curl_download.Rd | 3 - man/nslookup.Rd | 8 ++- man/send_mail.Rd | 4 + src/Makevars.win | 2 src/handle.c | 24 ++++++----- src/init.c | 7 ++- src/ssl.c | 57 +++++++++++++++++---------- src/typechecking.c | 88 +++++++++++++++++++++++++++++++------------ src/utils.c | 5 +- tests/testthat/test-handle.R | 6 ++ tests/testthat/test-path.R | 14 ++++++ tools/symbols-in-versions | 8 +++ tools/typecheck.R |only tools/typechecking.c.in |only vignettes/windows.Rmd |only 29 files changed, 308 insertions(+), 134 deletions(-)
Title: Jack, Zonal, and Schur Polynomials
Description: Symbolic calculation and evaluation of the Jack polynomials, zonal polynomials, and Schur polynomials. Mainly based on Demmel & Koev's paper (2006) <doi:10.1090/S0025-5718-05-01780-1>. Zonal polynomials and Schur polynomials are particular cases of Jack polynomials. Zonal polynomials appear in random matrix theory. Schur polynomials appear in the field of combinatorics.
Author: Stéphane Laurent
Maintainer: Stéphane Laurent <laurent_step@outlook.fr>
Diff between jack versions 1.1.0 dated 2019-09-09 and 1.1.1 dated 2019-09-16
DESCRIPTION | 8 ++++---- MD5 | 24 ++++++++++++------------ NEWS.md | 15 ++++++++++++++- R/Jack.R | 8 +++++++- R/Polynomials.R | 4 ++++ R/Schur.R | 4 ++++ R/Zonal.R | 4 ++++ R/ZonalQ.R | 4 ++++ R/internal.R | 2 +- tests/testthat/test-jack.R | 14 ++++++++++++++ tests/testthat/test-schur.R | 23 +++++++++++++++++++++++ tests/testthat/test-zonal.R | 24 ++++++++++++++++++++++++ tests/testthat/test-zonalQ.R | 11 +++++++++++ 13 files changed, 126 insertions(+), 19 deletions(-)
Title: Common Code for the 'AMPED' and 'PIMPLE' 'shiny' Apps for
Stakeholder Engagement and Harvest Strategies
Description: A collection of common code for the 'AMPED' and 'PIMPLE' 'shiny' applications for stakeholder engagement in developing fisheries harvest strategies. The package is not that useful on its own but provides common functionality including plots, stochasticity options, life history options and a simple surplus production model.
Author: Finlay Scott [aut, cre]
Maintainer: Finlay Scott <finlays@spc.int>
Diff between AMPLE versions 0.0.1 dated 2019-07-07 and 0.0.2 dated 2019-09-16
DESCRIPTION | 8 - MD5 | 16 +-- NAMESPACE | 2 R/funcs.R | 190 ++++++++++++++++++++++++++++++++++++------ R/plots.R | 117 +++++++++++-------------- man/comparison_plots.Rd | 32 +++---- man/front_page_plots.Rd | 4 man/maintainer_and_licence.Rd | 7 + man/performance_indicators.Rd | 26 ++++- 9 files changed, 280 insertions(+), 122 deletions(-)