Title: Polynomial Spline Routines
Description: Routines for the polynomial spline fitting routines
hazard regression, hazard estimation with flexible tails, logspline,
lspec, polyclass, and polymars, by C. Kooperberg and co-authors.
Author: Charles Kooperberg [aut, cre],
Cleve Moler [ctb] ,
Jack Dongarra [ctb]
Maintainer: Charles Kooperberg <clk@fredhutch.org>
Diff between polspline versions 1.1.20 dated 2022-04-25 and 1.1.22 dated 2022-11-22
DESCRIPTION | 8 MD5 | 92 NAMESPACE | 78 R/polspline.R |10036 +++++++++++++++++++-------------------- man/beta.polyclass.Rd | 94 man/clspec.Rd | 120 man/cpolyclass.Rd | 110 man/design.polymars.Rd | 86 man/dhare.Rd | 130 man/dheft.Rd | 104 man/dlogspline.Rd | 136 man/doldlogspline.Rd | 142 man/hare.Rd | 240 man/heft.Rd | 270 - man/logspline.Rd | 288 - man/lspec.Rd | 300 - man/oldlogspline.Rd | 282 - man/oldlogspline.to.logspline.Rd | 98 man/persp.polymars.Rd | 58 man/plot.hare.Rd | 120 man/plot.heft.Rd | 114 man/plot.logspline.Rd | 112 man/plot.lspec.Rd | 90 man/plot.oldlogspline.Rd | 110 man/plot.polyclass.Rd | 138 man/plot.polymars.Rd | 174 man/polyclass.Rd | 454 - man/polymars.Rd | 432 - man/predict.polymars.Rd | 108 man/summary.hare.Rd | 140 man/summary.heft.Rd | 136 man/summary.logspline.Rd | 112 man/summary.lspec.Rd | 60 man/summary.oldlogspline.Rd | 126 man/summary.polyclass.Rd | 80 man/summary.polymars.Rd | 114 man/testhare.Rd | 54 man/unstrip.Rd | 46 man/xhare.Rd | 52 src/hareall.c | 379 - src/heftall.c | 307 - src/lsdall.c | 293 - src/lspecall.c | 120 src/nlsd.c | 433 - src/polyall.c | 331 - src/polymars.c | 12 src/x2c.h | 22 47 files changed, 8456 insertions(+), 8885 deletions(-)
Title: Spatial Entropy Measures
Description: The heterogeneity of spatial data presenting a finite number of categories can be measured via computation of spatial entropy. Functions are available for the computation of the main entropy and spatial entropy measures in the literature. They include the traditional version of Shannon's entropy (Shannon, 1948 <doi:10.1002/j.1538-7305.1948.tb01338.x>), Batty's spatial entropy (Batty, 1974 <doi:10.1111/j.1538-4632.1974.tb01014.x>), O'Neill's entropy (O'Neill et al., 1998 <doi:10.1007/BF00162741>), Li and Reynolds' contagion index (Li and Reynolds, 1993 <doi:10.1007/BF00125347>), Karlstrom and Ceccato's entropy (Karlstrom and Ceccato, 2002 <urn:nbn:se:kth:diva-61351>), Leibovici's entropy (Leibovici, 2009 <doi:10.1007/978-3-642-03832-7_24>), Parresol and Edwards' entropy (Parresol and Edwards, 2014 <doi:10.3390/e16041842>) and Altieri's entropy (Altieri et al., 2018, <doi:10.1007/s10651-017-0383-1>). Full references for all measures can be [...truncated...]
Author: L. Altieri, D. Cocchi, G. Roli
Maintainer: Altieri Linda <linda.altieri@unibo.it>
Diff between SpatEntropy versions 2.1-1 dated 2022-02-19 and 2.2-0 dated 2022-11-22
DESCRIPTION | 14 +++++++------- MD5 | 8 ++++---- R/altieri_entropy.R | 12 ++++++------ R/oneill_leibovici_entropy.R | 12 ++++++------ R/shannon.R | 19 ++++++++++--------- 5 files changed, 33 insertions(+), 32 deletions(-)
Title: Extinction Simulation in Ecological Networks
Description: Simulates the extinction of species in ecological networks and it analyzes
its cascading effects, described in Dunne et al. (2002) <doi:10.1073/pnas.192407699>.
Author: Derek Corcoran [aut, cre] ,
M. Isidora Ávila-Thieme [aut] ,
Fernanda S. Valdovinos [aut],
Sergio A. Navarrete [aut],
Pablo A. Marquet [aut] ,
Erik Kusch [aut]
Maintainer: Derek Corcoran <derek.corcoran.barrios@gmail.com>
Diff between NetworkExtinction versions 1.0.0 dated 2022-10-07 and 1.0.1 dated 2022-11-22
DESCRIPTION | 10 +++++----- MD5 | 14 +++++++------- R/Extintions.R | 12 ++++++++---- build/vignette.rds |binary inst/doc/NetworkExtinction.html | 26 +++++++++++++------------- man/ExtinctionOrder.Rd | 2 +- man/RandomExtinctions.Rd | 2 +- man/SimulateExtinctions.Rd | 2 +- 8 files changed, 36 insertions(+), 32 deletions(-)
More information about NetworkExtinction at CRAN
Permanent link
Title: Routines for Logspline Density Estimation
Description: Contains routines for logspline density estimation.
The function oldlogspline() uses the same algorithm as the logspline package
version 1.0.x; i.e. the Kooperberg and Stone (1992)
algorithm (with an improved interface). The recommended routine logspline()
uses an algorithm from Stone et al (1997) <DOI:10.1214/aos/1031594728>.
Author: Charles Kooperberg [aut, cre],
Cleve Moler [ctb] ,
Jack Dongarra [ctb]
Maintainer: Charles Kooperberg <clk@fredhutch.org>
Diff between logspline versions 2.1.17 dated 2022-04-25 and 2.1.19 dated 2022-11-22
DESCRIPTION | 8 - MD5 | 8 - R/logspline.R | 20 +- src/lsdall.c | 293 ++++++++++++++++++++++----------------- src/nlsd.c | 433 +++++++++++++++++++--------------------------------------- 5 files changed, 328 insertions(+), 434 deletions(-)
Title: Tools for Clinical Research
Description: Every research team have their own script for data management, statistics and
most importantly hemodynamic indices. The purpose is to standardize scripts
utilized in clinical research. The hemodynamic indices can be used in a long-format dataframe,
and add both periods of interest (trigger-periods), and delete artifacts with deleter-files.
Transfer function analysis (Claassen et al. (2016) <doi:10.1177/0271678X15626425>) and
Mx (Czosnyka et al. (1996) <doi:10.1161/01.str.27.10.1829>) can be calculated using this package.
Author: Markus Harboe Olsen [cre, aut],
Christian Riberholt [ctb],
Ronan Berg [ctb],
Kirsten Moeller [ctb],
Janus Christian Jakobsen [ctb],
Aksel Karl Georg Jensen [ctb]
Maintainer: Markus Harboe Olsen <oel@oelfam.com>
Diff between clintools versions 0.9.6 dated 2022-07-12 and 0.9.7 dated 2022-11-22
DESCRIPTION | 8 ++++---- MD5 | 12 ++++++------ NEWS.md | 6 ++++++ R/PLR3000.R | 32 +++++++++++++++++++------------- R/sRCT.R | 1 + man/TFA.Rd | 12 ++++++++---- man/clinmon.Rd | 12 ++++++++---- 7 files changed, 52 insertions(+), 31 deletions(-)
Title: Expiry Estimation Procedures
Description: The Australian Regulatory Guidelines for Prescription
Medicines (ARGPM), guidance on "Stability testing for prescription
medicines", recommends to predict the shelf life of chemically derived
medicines from stability data by taking the worst case situation at batch
release into account. Consequently, if a change over time is observed,
a release limit needs to be specified. Finding a release limit and the
associated shelf life is supported, as well as the standard approach
that is recommended by guidance Q1E "Evaluation of stability data"
from the International Council for Harmonisation (ICH).
Author: Pius Dahinden [aut, cre],
Tillotts Pharma AG [cph, fnd]
Maintainer: Pius Dahinden <pius.dahinden@tillotts.com>
Diff between expirest versions 0.1.3 dated 2022-06-01 and 0.1.5 dated 2022-11-22
DESCRIPTION | 19 ++--- MD5 | 42 +++++------ NAMESPACE | 3 NEWS.md | 22 +++++ R/data.R | 14 +-- R/expirest_osle.R | 102 ++++++++++++++------------ R/expirest_wisle.R | 140 ++++++++++++++++--------------------- R/generic.R | 65 ++++++++++------- R/utility.R | 128 ++++++++++++++++++--------------- README.md | 25 +++--- man/exp1.Rd | 3 man/exp2.Rd | 3 man/exp3.Rd | 3 man/exp4.Rd | 2 man/expirest_osle.Rd | 3 man/expirest_wisle.Rd | 6 - man/figures/README-example_2-1.png |binary man/find_poi.Rd | 6 - man/get_distance.Rd | 6 - man/get_wcs_limit.Rd | 3 tests/testthat/test-extract_wc_x.R | 42 +++++++---- tests/testthat/test-generic.R | 25 ++++-- 22 files changed, 354 insertions(+), 308 deletions(-)
Title: Spatial Analysis of Vectra Immunoflourescent Data
Description: Visualization and analysis of Vectra Immunoflourescent
data. Options for calculating both the univariate and bivariate Ripley's K
are included. Calculations are performed using a permutation-based
approach presented by Wilson et al. <doi:10.1101/2021.04.27.21256104>.
Author: Jordan Creed [aut],
Ram Thapa [aut],
Christopher Wilson [aut],
Alex Soupir [aut],
Oscar Ospina [aut],
Brooke Fridley [cph],
Fridley Lab [cre]
Maintainer: Fridley Lab <fridley.lab@moffitt.org>
Diff between spatialTIME versions 1.2.1 dated 2022-06-23 and 1.2.2 dated 2022-11-22
DESCRIPTION | 12 +- MD5 | 16 +-- R/ripleys_k.R | 8 - R/utils-helpers.R | 10 +- build/vignette.rds |binary inst/doc/intro.R | 21 +++- inst/doc/intro.Rmd | 21 +++- inst/doc/intro.html | 242 ++++++++++++++++++++++++++-------------------------- vignettes/intro.Rmd | 21 +++- 9 files changed, 193 insertions(+), 158 deletions(-)
Title: XML Output Functions for Easy Creation of Moodle Questions
Description: Provides a set of basic functions for creating Moodle XML
output files suited for importing questions in Moodle (a learning
management system, see <https://moodle.org/> for more information).
Author: Emmanuel Curis [aut, cre, cph]
,
Virginie Lasserre [ctb]
Maintainer: Emmanuel Curis <emmanuel.curis@parisdescartes.fr>
Diff between SARP.moodle versions 0.8.7 dated 2021-02-26 and 0.9.1 dated 2022-11-22
DESCRIPTION | 8 MD5 | 38 - R/categories.R | 18 R/conversion_csv.R | 1040 ++++++++++++++++++++++++++++++++++--------------- R/glisser.R | 20 R/libre.R | 12 R/messages.R | 151 ++++++- R/numerique.R | 11 R/qcm.R | 30 - R/question.R | 4 R/redaction.R | 8 R/textes.R | 6 man/categorie.Rd | 22 - man/cvs.moodle.Rd | 67 ++- man/description.Rd | 2 man/inserer_formule.Rd | 4 man/libre.moodle.Rd | 64 ++- man/messages.Rd | 12 man/qcm.moodle.Rd | 7 man/sortie_R.Rd | 3 20 files changed, 1084 insertions(+), 443 deletions(-)
Title: Risk Regression Models and Prediction Scores for Survival
Analysis with Competing Risks
Description: Implementation of the following methods for event history analysis.
Risk regression models for survival endpoints also in the presence of competing
risks are fitted using binomial regression based on a time sequence of binary
event status variables. A formula interface for the Fine-Gray regression model
and an interface for the combination of cause-specific Cox regression models.
A toolbox for assessing and comparing performance of risk predictions (risk
markers and risk prediction models). Prediction performance is measured by the
Brier score and the area under the ROC curve for binary possibly time-dependent
outcome. Inverse probability of censoring weighting and pseudo values are used
to deal with right censored data. Lists of risk markers and lists of risk models
are assessed simultaneously. Cross-validation repeatedly splits the data, trains
the risk prediction models on one part of each split and then summarizes and
compares the performance across splits.
Author: Thomas Alexander Gerds [aut, cre],
Johan Sebastian Ohlendorff [aut],
Paul Blanche [ctb],
Rikke Mortensen [ctb],
Marvin Wright [ctb],
Nikolaj Tollenaar [ctb],
John Muschelli [ctb],
Ulla Brasch Mogensen [ctb],
Brice Ozenne [aut]
Maintainer: Thomas Alexander Gerds <tag@biostat.ku.dk>
Diff between riskRegression versions 2022.09.23 dated 2022-09-26 and 2022.11.21 dated 2022-11-22
riskRegression-2022.09.23/riskRegression/R/getInfluenceCurverHelper.R |only riskRegression-2022.09.23/riskRegression/man/IC_Nelson_Aalen_cens_time.Rd |only riskRegression-2022.09.23/riskRegression/man/colCumProd.Rd |only riskRegression-2022.09.23/riskRegression/man/colSumsCrossprod.Rd |only riskRegression-2022.09.23/riskRegression/man/rowCumProd.Rd |only riskRegression-2022.09.23/riskRegression/man/sliceMultiply_cpp.Rd |only riskRegression-2022.09.23/riskRegression/man/sliceScale_cpp.Rd |only riskRegression-2022.09.23/riskRegression/src/colSumsCrossprod.cpp |only riskRegression-2022.09.23/riskRegression/src/influenceFunctionHelpers.cpp |only riskRegression-2022.09.23/riskRegression/tests/testthat/test-score-bootstrap.R |only riskRegression-2022.11.21/riskRegression/DESCRIPTION | 14 riskRegression-2022.11.21/riskRegression/MD5 | 81 - riskRegression-2022.11.21/riskRegression/NAMESPACE | 13 riskRegression-2022.11.21/riskRegression/R/AUC.competing.risks.R | 11 riskRegression-2022.11.21/riskRegression/R/AUC.survival.R | 24 riskRegression-2022.11.21/riskRegression/R/Brier.competing.risks.R | 46 riskRegression-2022.11.21/riskRegression/R/Brier.survival.R | 54 - riskRegression-2022.11.21/riskRegression/R/IPA.R | 9 riskRegression-2022.11.21/riskRegression/R/RcppExports.R | 155 --- riskRegression-2022.11.21/riskRegression/R/Score.R | 91 + riskRegression-2022.11.21/riskRegression/R/calcCensoringWeightsCox.R |only riskRegression-2022.11.21/riskRegression/R/crossvalPerf.R | 468 ++-------- riskRegression-2022.11.21/riskRegression/R/fitters.R |only riskRegression-2022.11.21/riskRegression/R/getCensoringWeights.R | 143 +-- riskRegression-2022.11.21/riskRegression/R/getInfluenceCurve.R | 326 +----- riskRegression-2022.11.21/riskRegression/R/getPerformanceData.R | 6 riskRegression-2022.11.21/riskRegression/R/predictRisk.R | 241 +++-- riskRegression-2022.11.21/riskRegression/R/riskLevelPlot.R | 1 riskRegression-2022.11.21/riskRegression/R/sampleData.R | 1 riskRegression-2022.11.21/riskRegression/R/simPBC.R |only riskRegression-2022.11.21/riskRegression/R/transform.R | 23 riskRegression-2022.11.21/riskRegression/man/GLMnet.Rd |only riskRegression-2022.11.21/riskRegression/man/Hal9001.Rd |only riskRegression-2022.11.21/riskRegression/man/Score.Rd | 35 riskRegression-2022.11.21/riskRegression/man/predictRisk.Rd | 42 riskRegression-2022.11.21/riskRegression/man/simPBC.Rd |only riskRegression-2022.11.21/riskRegression/src/IC-Nelson-Aalen-cens-time.cpp | 70 - riskRegression-2022.11.21/riskRegression/src/IC-Nelson-Aalen-cens-time.h |only riskRegression-2022.11.21/riskRegression/src/Makevars | 1 riskRegression-2022.11.21/riskRegression/src/RcppExports.cpp | 237 +---- riskRegression-2022.11.21/riskRegression/src/arma-wrap.cpp | 36 riskRegression-2022.11.21/riskRegression/src/arma-wrap.h | 1 riskRegression-2022.11.21/riskRegression/src/colCumSum.cpp | 18 riskRegression-2022.11.21/riskRegression/src/getInfluenceFunctionAUC.cpp | 358 +++---- riskRegression-2022.11.21/riskRegression/src/getInfluenceFunctionBrier.cpp | 16 riskRegression-2022.11.21/riskRegression/src/rowCumSum.cpp | 18 riskRegression-2022.11.21/riskRegression/src/sweepCenterScale.cpp | 67 - riskRegression-2022.11.21/riskRegression/src/weightedAverageIFCumhazard.cpp |only riskRegression-2022.11.21/riskRegression/tests/testthat/test-predictCox.R | 11 riskRegression-2022.11.21/riskRegression/tests/testthat/test-score-train-test.R |only riskRegression-2022.11.21/riskRegression/vignettes/IFBrier.Rmd | 159 +-- 51 files changed, 1056 insertions(+), 1720 deletions(-)
More information about riskRegression at CRAN
Permanent link
Title: Data Simulation Based on Latent Factors
Description: Generates data based on latent factor models. Data can be continuous, polytomous, dichotomous, or mixed. Skews, cross-loadings, wording effects, population errors, and local dependencies can be added. All parameters can be manipulated. Data categorization is based on Garrido, Abad, and Ponsoda (2011) <doi:10.1177/0013164410389489>.
Author: Alexander Christensen [aut, cre]
,
Maria Dolores Nieto Canaveras [aut],
Hudson Golino [aut] ,
Luis Eduardo Garrido [aut] ,
Marcos Jimenez [aut],
Francisco Abad [ctb],
Eduardo Garcia-Garzon [ctb],
Vithor Franco [aut]
Maintainer: Alexander Christensen <alexpaulchristensen@gmail.com>
Diff between latentFactoR versions 0.0.3 dated 2022-10-13 and 0.0.4 dated 2022-11-22
DESCRIPTION | 12 ++-- MD5 | 26 ++++----- NEWS | 9 +++ R/EKC.R | 4 - R/NEST.R | 19 +++++-- R/add_cross_loadings.R | 83 ++++++++++++++++++++++++++++++- R/add_population_error.R | 93 ++++++++++++++++++++++++++++++++++- R/estimate_dimensions.R | 23 ++++++-- R/factor_forest.R | 29 +++++++++-- R/simulate_factors.R | 67 ++++++++++++++++++------- R/utils-latentFactoR.R | 116 +++++++++++++++++++++++++++++++++----------- inst/CITATION | 4 - man/add_population_error.Rd | 6 ++ man/estimate_dimensions.Rd | 3 - 14 files changed, 405 insertions(+), 89 deletions(-)
Title: Bayesian Spatial Survival Analysis with Parametric Proportional
Hazards Models
Description: Bayesian inference for parametric proportional hazards spatial
survival models; flexible spatial survival models. See Benjamin M. Taylor, Barry S. Rowlingson (2017) <doi:10.18637/jss.v077.i04>.
Author: Benjamin M. Taylor and Barry S. Rowlingson
Additional contributions
Ziyu Zheng
Maintainer: Benjamin M. Taylor <benjamin.taylor.software@gmail.com>
Diff between spatsurv versions 1.8 dated 2022-05-06 and 1.8-2 dated 2022-11-22
DESCRIPTION | 16 ++++++++-------- MD5 | 18 +++++++++--------- NAMESPACE | 2 +- R/covarianceFunctions.R | 13 ++++++++++++- R/spatsurv.R | 2 +- R/spatsurvMisc.R | 2 +- build/partial.rdb |binary data/fs.rda |binary data/fstimes.rda |binary tests/test_survspat.R | 2 +- 10 files changed, 33 insertions(+), 22 deletions(-)
Title: Log-Gaussian Cox Process
Description: Spatial and spatio-temporal modelling of point patterns using the
log-Gaussian Cox process. Bayesian inference for spatial, spatiotemporal,
multivariate and aggregated point processes using Markov chain Monte Carlo. See Benjamin M. Taylor, Tilman M. Davies, Barry S. Rowlingson, Peter J. Diggle (2015) <doi:10.18637/jss.v063.i07>.
Author: Benjamin M. Taylor, Tilman M. Davies, Barry S. Rowlingson, Peter J.
Diggle. Additional code contributions from Edzer Pebesma, Dominic Schumacher.
Maintainer: Benjamin M. Taylor <benjamin.taylor.software@gmail.com>
Diff between lgcp versions 1.8 dated 2022-05-17 and 1.8-2 dated 2022-11-22
DESCRIPTION | 10 +++++----- MD5 | 40 ++++++++++++++++++++-------------------- NAMESPACE | 14 +++++++------- R/getCounts.R | 2 +- R/lgcp.R | 2 +- R/lgcpInternals.R | 8 +++++++- R/lgcpSimSpatioTemporal.R | 2 +- build/partial.rdb |binary build/vignette.rds |binary data/wpopdata.rda |binary data/wtowncoords.rda |binary data/wtowns.rda |binary inst/doc/lgcp.pdf |binary man/getCounts.Rd | 2 +- man/lgcpSim.Rd | 2 +- man/wpopdata.Rd | 2 +- man/wtowns.Rd | 2 +- tests/fromSPDFTest.R | 2 +- tests/lgcpMethodsTest.R | 2 +- tests/mstpppClassTest.R | 2 +- tests/stpppClassTest.R | 2 +- 21 files changed, 50 insertions(+), 44 deletions(-)
Title: Confounder-Adjusted Survival Curves and Cumulative Incidence
Functions
Description: Estimate and plot confounder-adjusted survival curves using
either 'Direct Adjustment', 'Direct Adjustment with Pseudo-Values',
various forms of 'Inverse Probability of Treatment Weighting', two
forms of 'Augmented Inverse Probability of Treatment Weighting',
'Empirical Likelihood Estimation' and 'Targeted Maximum Likelihood
Estimation'. Also includes a significance test for the difference
between two adjusted survival curves and the calculation of adjusted
restricted mean survival times. Additionally enables the user to
estimate and plot cause-specific confounder-adjusted cumulative
incidence functions in the competing risks setting using the same
methods (with some exceptions).
For details, see Denz et. al (2022) <arXiv:2203.10002v1>.
Author: Robin Denz [aut, cre]
Maintainer: Robin Denz <robin.denz@rub.de>
Diff between adjustedCurves versions 0.9.0 dated 2022-09-22 and 0.9.1 dated 2022-11-22
DESCRIPTION | 6 MD5 | 78 - NEWS.md | 7 R/plot.adjustedcif.r | 586 +++---- R/plot.adjustedsurv.r | 758 +++++----- R/plot_auc_curve.r | 350 ++-- R/plot_curve_diff.r | 522 +++--- man/adjustedCurves.Rd | 108 - man/surv_strat_amato.Rd | 154 +- man/surv_strat_cupples.Rd | 150 - tests/testthat/_snaps/plot.adjustedcif/plot-ci-no-color-steps.svg | 12 tests/testthat/_snaps/plot.adjustedcif/plot-ci-single-color-steps.svg | 12 tests/testthat/_snaps/plot.adjustedcif/plot-using-boot.svg | 16 tests/testthat/_snaps/plot.adjustedcif/plot-using-conf-int-alpha.svg | 16 tests/testthat/_snaps/plot.adjustedcif/plot-using-many-many-things.svg | 16 tests/testthat/_snaps/plot.adjustedcif/plot-using-no-colors-ci.svg | 12 tests/testthat/_snaps/plot.adjustedcif/plot-with-conf-int.svg | 16 tests/testthat/_snaps/plot.adjustedsurv/plot-ci-no-color-steps.svg | 12 tests/testthat/_snaps/plot.adjustedsurv/plot-ci-single-color-steps.svg | 12 tests/testthat/_snaps/plot.adjustedsurv/plot-using-boot.svg | 16 tests/testthat/_snaps/plot.adjustedsurv/plot-using-conf-int-alpha.svg | 16 tests/testthat/_snaps/plot.adjustedsurv/plot-using-many-many-things.svg | 16 tests/testthat/_snaps/plot.adjustedsurv/plot-using-no-colors-ci.svg | 12 tests/testthat/_snaps/plot.adjustedsurv/plot-with-conf-int.svg | 16 tests/testthat/_snaps/plot_auc_curve/plot-rmst-conf-int.svg | 16 tests/testthat/_snaps/plot_auc_curve/plot-rmtl-conf-int.svg | 12 tests/testthat/_snaps/plot_curve_diff/plot-with-conf-int-boot.svg | 6 tests/testthat/_snaps/plot_curve_diff/plot-with-conf-int.svg | 6 tests/testthat/_snaps/plot_curve_diff/plot-with-fill-area-lines.svg | 10 tests/testthat/_snaps/plot_curve_diff/plot-with-fill-area-steps.svg | 6 tests/testthat/_snaps/plot_curve_diff/plot-with-lines-ci.svg | 6 tests/testthat/_snaps/plot_curve_diff/plot-with-much-stuff.svg | 6 tests/testthat/test_MI_adjustedcif.r | 12 tests/testthat/test_MI_adjustedsurv.r | 14 tests/testthat/test_adjusted_curve_test.r | 370 ++-- tests/testthat/test_plot.adjustedcif.r | 538 +++---- tests/testthat/test_plot.adjustedsurv.r | 588 +++---- tests/testthat/test_plot.curve_test.r | 204 +- tests/testthat/test_plot_auc_curve.r | 208 +- tests/testthat/test_plot_curve_diff.r | 338 ++-- 40 files changed, 2635 insertions(+), 2624 deletions(-)
More information about adjustedCurves at CRAN
Permanent link
Title: Decentralized Unequivocality in Psychological Science
Description: The constructs used to study the human psychology have
many definitions and corresponding instructions for eliciting
and coding qualitative data pertaining to constructs' content and
for measuring the constructs. This plethora of definitions and
instructions necessitates unequivocal reference to specific
definitions and instructions in empirical and secondary research.
This package implements a human- and machine-readable standard for
specifying construct definitions and instructions for measurement
and qualitative research based on 'YAML'. This standard facilitates
systematic unequivocal reference to specific construct definitions
and corresponding instructions in a decentralized manner (i.e.
without requiring central curation; Peters (2020)
<doi:10.31234/osf.io/xebhn>).
Author: Gjalt-Jorn Peters [aut, cre, ctb]
,
Rik Crutzen [ctb]
Maintainer: Gjalt-Jorn Peters <gjalt-jorn@behaviorchange.eu>
Diff between psyverse versions 0.1.0 dated 2020-03-26 and 0.2.4 dated 2022-11-22
psyverse-0.1.0/psyverse/inst/extdata/attitude_73dnt5zc.dct |only psyverse-0.1.0/psyverse/inst/extdata/behavior_73dnt605.dct |only psyverse-0.1.0/psyverse/inst/extdata/capacity_73dnt602.dct |only psyverse-0.1.0/psyverse/inst/extdata/example_dct_spec_1.dct |only psyverse-0.1.0/psyverse/inst/extdata/intention_73dnt604.dct |only psyverse-0.2.4/psyverse/DESCRIPTION | 27 psyverse-0.2.4/psyverse/MD5 | 86 ++- psyverse-0.2.4/psyverse/NAMESPACE | 12 psyverse-0.2.4/psyverse/R/dct_from_gs.R |only psyverse-0.2.4/psyverse/R/dct_from_spreadsheet.R |only psyverse-0.2.4/psyverse/R/dct_from_xlsx.R |only psyverse-0.2.4/psyverse/R/dct_object.R |only psyverse-0.2.4/psyverse/R/dct_object_to_html.R |only psyverse-0.2.4/psyverse/R/dct_object_to_yaml.R |only psyverse-0.2.4/psyverse/R/dct_sheet_to_dct.R |only psyverse-0.2.4/psyverse/R/dct_template.R | 4 psyverse-0.2.4/psyverse/R/generate_construct_overview.R | 275 ++++++---- psyverse-0.2.4/psyverse/R/generate_definitions_overview.R | 9 psyverse-0.2.4/psyverse/R/generate_instruction_overview.R | 14 psyverse-0.2.4/psyverse/R/load_dct_dir.R | 39 - psyverse-0.2.4/psyverse/R/load_dct_specs.R | 17 psyverse-0.2.4/psyverse/R/msg.R |only psyverse-0.2.4/psyverse/R/nest_in_list.R |only psyverse-0.2.4/psyverse/R/opts.R |only psyverse-0.2.4/psyverse/R/parse_dct_specs.R | 148 +++-- psyverse-0.2.4/psyverse/R/read_spreadsheet.R |only psyverse-0.2.4/psyverse/R/save_to_yaml.R |only psyverse-0.2.4/psyverse/R/viewHTML.R |only psyverse-0.2.4/psyverse/README.md | 108 --- psyverse-0.2.4/psyverse/build/vignette.rds |binary psyverse-0.2.4/psyverse/inst/doc/decentralized-construct-taxonomies.Rmd | 16 psyverse-0.2.4/psyverse/inst/doc/decentralized-construct-taxonomies.html | 246 +++++++- psyverse-0.2.4/psyverse/inst/extdata/attitude_73dnt5zc.dct.yaml |only psyverse-0.2.4/psyverse/inst/extdata/behavior_73dnt605.dct.yaml |only psyverse-0.2.4/psyverse/inst/extdata/capacity_73dnt602.dct.yaml |only psyverse-0.2.4/psyverse/inst/extdata/example.dct.yaml |only psyverse-0.2.4/psyverse/inst/extdata/intention_73dnt604.dct.yaml |only psyverse-0.2.4/psyverse/man/apply_graph_theme.Rd | 66 +- psyverse-0.2.4/psyverse/man/base30and36conversion.Rd | 82 +- psyverse-0.2.4/psyverse/man/cat0.Rd | 46 - psyverse-0.2.4/psyverse/man/dct_from_spreadsheet.Rd |only psyverse-0.2.4/psyverse/man/dct_object.Rd |only psyverse-0.2.4/psyverse/man/dct_object_to_html.Rd |only psyverse-0.2.4/psyverse/man/dct_object_to_yaml.Rd |only psyverse-0.2.4/psyverse/man/dct_sheet_to_dct.Rd |only psyverse-0.2.4/psyverse/man/dct_templates.Rd | 102 +-- psyverse-0.2.4/psyverse/man/figures |only psyverse-0.2.4/psyverse/man/generate_id.Rd | 74 +- psyverse-0.2.4/psyverse/man/invert_id.Rd | 44 - psyverse-0.2.4/psyverse/man/load_dct_specs.Rd | 245 ++++---- psyverse-0.2.4/psyverse/man/opts.Rd |only psyverse-0.2.4/psyverse/man/overview_generation.Rd | 169 +++--- psyverse-0.2.4/psyverse/man/parse_dct_specs.Rd | 65 +- psyverse-0.2.4/psyverse/man/read_spreadsheet.Rd |only psyverse-0.2.4/psyverse/man/repeatStr.Rd | 54 - psyverse-0.2.4/psyverse/man/save_to_yaml.Rd |only psyverse-0.2.4/psyverse/man/vecTxt.Rd | 108 +-- psyverse-0.2.4/psyverse/man/viewHTML.Rd |only psyverse-0.2.4/psyverse/tests/testthat/test-loading-dct-specs-from-files.R | 2 psyverse-0.2.4/psyverse/tests/testthat/test-saving-dct-specs.R |only psyverse-0.2.4/psyverse/vignettes/decentralized-construct-taxonomies.Rmd | 16 61 files changed, 1188 insertions(+), 886 deletions(-)
Title: Comprehensive and Easy to Use Quality Control of GWAS Results
Description: When evaluating the results of a genome-wide association study (GWAS), it is important to perform a quality control to ensure that the results are valid, complete, correctly formatted, and, in case of meta-analysis, consistent with other studies that have applied the same analysis. This package was developed to facilitate and streamline this process and provide the user with a comprehensive report.
Author: Alireza Ani [aut, cre],
Peter J. van der Most [aut],
Ahmad Vaez [aut],
Ilja M. Nolte [aut]
Maintainer: Alireza Ani <a.ani@umcg.nl>
Diff between GWASinspector versions 1.5.7.2 dated 2022-04-28 and 1.6.0 dated 2022-11-22
ChangeLog | 4 DESCRIPTION | 11 MD5 | 22 NAMESPACE | 1 NEWS | 4 R/aaa.R | 2 R/excelReportFunctions.R | 1280 +++++++++++++++++++++++-------------------- R/fileFunctions.R | 2 R/rSQLiteFunctions.R | 62 -- R/system_check.R | 2 R/variantMatchingFunctions.R | 3 inst/doc/GWASinspector.html | 4 12 files changed, 736 insertions(+), 661 deletions(-)
More information about fetchGoogleAnalyticsR at CRAN
Permanent link
Title: Generalized and Classical Blockmodeling of Valued Networks
Description: This is primarily meant as an implementation of generalized blockmodeling for valued networks.
In addition, measures of similarity or dissimilarity based on structural equivalence and
regular equivalence (REGE algorithms) can be computed and partitioned matrices can be plotted:
Žiberna (2007)<doi:10.1016/j.socnet.2006.04.002>, Žiberna (2008)<doi:10.1080/00222500701790207>,
Žiberna (2014)<doi:10.1016/j.socnet.2014.04.002>.
Author: Ales Žiberna [aut, cre],
Marjan Cugmas [ctb]
Maintainer: Ales Žiberna <ales.ziberna@gmail.com>
Diff between blockmodeling versions 1.1.3 dated 2022-09-01 and 1.1.4 dated 2022-11-22
CHANGES | 22 ++++++++++++++++++---- DESCRIPTION | 21 +++++++++------------ MD5 | 21 +++++++++++---------- R/RF.R | 35 +++++++++++++++++------------------ R/printBlocks.R | 6 ++++-- build |only data/baker.rda |binary data/notesBorrowing.RData |binary man/RF.Rd | 17 +++++++++-------- man/printBlocks.Rd | 4 ++-- src/blockmodelingC.c | 10 ++++------ tests/tests.R | 16 ++++++++-------- 12 files changed, 82 insertions(+), 70 deletions(-)
Title: Transfer of Hydrograph from Gauged to Ungauged Catchments
Description: A geomorphology-based hydrological modelling for transferring
streamflow measurements from gauged to ungauged catchments. Inverse
modelling enables to estimate net rainfall from streamflow measurements
following Boudhraâ et al. (2018) <doi:10.1080/02626667.2018.1425801>.
Resulting net rainfall is then estimated on the ungauged catchments
by spatial interpolation in order to finally simulate streamflow
following de Lavenne et al. (2016) <doi:10.1002/2016WR018716>.
Author: Alban de Lavenne [aut, cre] ,
Christophe Cudennec [ths] ,
Tom Loree [ctb],
Herve Squividant [ctb]
Maintainer: Alban de Lavenne <alban.delavenne@inrae.fr>
Diff between transfR versions 1.0.1 dated 2022-11-08 and 1.0.2 dated 2022-11-22
DESCRIPTION | 8 MD5 | 26 +- README.md | 10 build/partial.rdb |binary build/vignette.rds |binary data/Blavet.rda |binary data/Oudon.rda |binary inst/doc/V01_get_started.html | 6 inst/doc/V02_inputs_preparation_stars.html | 10 inst/doc/V03_inputs_preparation_whitebox.R | 21 - inst/doc/V03_inputs_preparation_whitebox.Rmd | 28 -- inst/doc/V03_inputs_preparation_whitebox.html | 305 ++++++++++++-------------- man/Blavet.Rd | 26 ++ vignettes/V03_inputs_preparation_whitebox.Rmd | 28 -- 14 files changed, 221 insertions(+), 247 deletions(-)
Title: Stepwise Split Regularized Regression
Description: Functions to perform stepwise split regularized regression. The approach first
uses a stepwise algorithm to split the variables into the models with a goodness
of fit criterion, and then regularization is applied to each model. The weights
of the models in the ensemble are determined based on a criterion selected by
the user.
Author: Anthony Christidis [aut, cre],
Stefan Van Aelst [aut],
Ruben Zamar [aut]
Maintainer: Anthony Christidis <anthony.christidis@stat.ubc.ca>
Diff between stepSplitReg versions 1.0.2 dated 2022-06-26 and 1.0.3 dated 2022-11-22
DESCRIPTION | 8 ++++---- MD5 | 22 +++++++++++----------- NEWS | 5 ++++- src/CV_WEN.cpp | 2 +- src/CV_WEN.hpp | 2 +- src/Model.cpp | 2 +- src/Model.hpp | 2 +- src/Model_Functions.hpp | 2 +- src/Set_Diff.hpp | 2 +- src/WEN.cpp | 2 +- src/WEN.hpp | 2 +- src/stepSplitReg_Main.cpp | 2 +- 12 files changed, 28 insertions(+), 25 deletions(-)
Title: Spatially Varying and Spatio-Temporal Dynamic Linear Models
Description: Fits, spatially predicts, and temporally forecasts space-time data using Gaussian Process (GP): (1) spatially varying coefficient process models and (2) spatio-temporal dynamic linear models. Bakar et al., (2016). Bakar et al., (2015).
Author: K. Shuvo Bakar, Philip Kokic, Huidong Jin
Maintainer: K. Shuvo Bakar <shuvo.bakar@gmail.com>
Diff between spTDyn versions 2.0.1 dated 2020-06-02 and 2.0.2 dated 2022-11-22
DESCRIPTION | 12 ++++++------ MD5 | 16 ++++++++-------- R/spGP.r | 4 ++-- R/spTfnc.R | 43 ++++++++++++++++++++++++++----------------- inst/CITATION | 6 ++---- inst/ChangeLog | 5 +++++ man/sp.Rd | 2 +- man/tp.Rd | 6 +++--- src/mathematics.h | 4 ++-- 9 files changed, 55 insertions(+), 43 deletions(-)
Title: Spatial Sampling Design and Analysis
Description: A design-based approach to statistical inference, with a focus on spatial data. Spatially balanced samples are selected using the Generalized Random Tessellation Stratified (GRTS) algorithm. The GRTS algorithm can be applied to finite resources (point geometries) and infinite resources (linear / linestring and areal / polygon geometries) and flexibly accommodates a diverse set of sampling design features, including stratification, unequal inclusion probabilities, proportional (to size) inclusion probabilities, legacy (historical) sites, a minimum distance between sites, and two options for replacement sites (reverse hierarchical order and nearest neighbor). Data are analyzed using a wide range of analysis functions that perform categorical variable analysis, continuous variable analysis, attributable risk analysis, risk difference analysis, relative risk analysis, change analysis, and trend analysis. spsurvey can also be used to summarize objects, visualize objects, select samples that [...truncated...]
Author: Michael Dumelle [aut, cre] ,
Tom Kincaid [aut],
Tony Olsen [aut],
Marc Weber [aut],
Don Stevens [ctb],
Denis White [ctb]
Maintainer: Michael Dumelle <Dumelle.Michael@epa.gov>
Diff between spsurvey versions 5.3.0 dated 2022-02-24 and 5.4.0 dated 2022-11-22
DESCRIPTION | 9 MD5 | 129 +- NAMESPACE | 16 NEWS.md | 100 + R/attrisk_analysis.R | 26 R/cat_analysis.R | 22 R/change_analysis.R | 181 +++ R/change_est.R | 522 +++++++++ R/changevar_mean.R | 2 R/cont_analysis.R | 64 + R/cont_cdftest.R | 2 R/data.R | 2 R/diffrisk_analysis.R | 28 R/dsgn_check.R | 2 R/grts.R | 71 + R/input_check.R | 5 R/irs.R | 35 R/percentile_est.R | 17 R/plot.R |only R/print.R |only R/relrisk_analysis.R | 28 R/sp_frame.R |only R/sp_plot.R | 11 R/sp_rbind.R | 2 R/sp_summary.R | 27 R/summary.R |only R/trend_analysis.R | 2 R/utils.R | 25 README.md | 4 inst/CITATION | 4 inst/doc/EDA.R | 90 - inst/doc/EDA.Rmd | 118 +- inst/doc/EDA.html | 106 + inst/doc/analysis.R | 2 inst/doc/analysis.Rmd | 4 inst/doc/analysis.html | 8 inst/doc/sampling.R | 41 inst/doc/sampling.Rmd | 53 inst/doc/sampling.html | 154 ++ inst/doc/start-here.Rmd | 6 inst/doc/start-here.html | 14 man/Lake_Ontario.Rd | 2 man/attrisk_analysis.Rd | 24 man/cat_analysis.Rd | 20 man/change_analysis.Rd | 152 ++ man/cont_analysis.Rd | 61 + man/diffrisk_analysis.Rd | 26 man/grts.Rd | 46 man/irs.Rd | 46 man/plot.Rd |only man/plot.sp_CDF.Rd |only man/relrisk_analysis.Rd | 26 man/sp_frame.Rd |only man/sp_plot.Rd | 9 man/sp_summary.Rd | 11 man/spsurvey-package.Rd | 1 man/summary.Rd |only tests/testthat/test-cdf_plot.R |only tests/testthat/test-change_analysis.R | 73 + tests/testthat/test-cont_analysis.R | 24 tests/testthat/test-grts.R | 1878 +++++++++++++++++---------------- tests/testthat/test-irs.R | 1880 +++++++++++++++++----------------- tests/testthat/test-plot.R |only tests/testthat/test-print.R |only tests/testthat/test-sp_frame.R |only tests/testthat/test-sp_plot.R | 2 tests/testthat/test-sp_summary.R | 4 tests/testthat/test-summary.R |only vignettes/EDA.Rmd | 118 +- vignettes/analysis.Rmd | 4 vignettes/sampling.Rmd | 53 vignettes/start-here.Rmd | 6 72 files changed, 4020 insertions(+), 2378 deletions(-)
Title: Split Generalized Linear Models
Description: Functions to compute split generalized linear models. The approach fits
generalized linear models that split the covariates into groups. The
optimal split of the variables into groups and the regularized estimation
of the coefficients are performed by minimizing an objective function
that encourages sparsity within each group and diversity among them.
Example applications can be found in Christidis et al. (2021)
<arXiv:2102.08591>.
Author: Anthony Christidis [aut, cre],
Stefan Van Aelst [aut],
Ruben Zamar [aut]
Maintainer: Anthony Christidis <anthony.christidis@stat.ubc.ca>
Diff between SplitGLM versions 1.0.4 dated 2022-06-01 and 1.0.5 dated 2022-11-22
DESCRIPTION | 8 ++++---- MD5 | 24 ++++++++++++------------ NEWS | 5 ++++- src/CV_Split_WEN.cpp | 2 +- src/CV_Split_WEN.hpp | 2 +- src/CV_Split_WEN_Main.cpp | 2 +- src/CV_WEN.cpp | 2 +- src/CV_WEN.hpp | 2 +- src/Split_WEN.cpp | 2 +- src/Split_WEN.hpp | 2 +- src/Split_WEN_Main.cpp | 2 +- src/WEN.cpp | 2 +- src/WEN.hpp | 2 +- 13 files changed, 30 insertions(+), 27 deletions(-)
Title: Projected Subset Gradient Descent
Description: Functions to generate ensembles of generalized linear models using
a greedy projected subset gradient descent algorithm. The sparsity
and diversity tuning parameters are selected by cross-validation.
Author: Anthony Christidis [aut, cre],
Stefan Van Aelst [aut],
Ruben Zamar [aut]
Maintainer: Anthony Christidis <anthony.christidis@stat.ubc.ca>
Diff between PSGD versions 1.0.1 dated 2022-07-01 and 1.0.2 dated 2022-11-22
DESCRIPTION | 8 ++++---- MD5 | 30 +++++++++++++++--------------- NEWS | 5 ++++- src/Logistic_Model.cpp | 2 +- src/Logistic_Model.hpp | 2 +- src/Main_CV_PSGD.cpp | 2 +- src/Main_PSGD.cpp | 2 +- src/Model_Functions.hpp | 2 +- src/PSGD.cpp | 8 ++++---- src/PSGD.hpp | 4 ++-- src/PS_Model.cpp | 2 +- src/PS_Model.hpp | 4 ++-- src/Set_Diff.hpp | 2 +- src/Step_Model.cpp | 2 +- src/Step_Model.hpp | 2 +- src/Stepwise_Split.hpp | 2 +- 16 files changed, 41 insertions(+), 38 deletions(-)
Title: Circle Packing
Description: Algorithms to find arrangements of non-overlapping circles.
Author: Michael Bedward [aut, cre],
David Eppstein [aut] ,
Peter Menzel [aut]
Maintainer: Michael Bedward <michael.bedward@gmail.com>
Diff between packcircles versions 0.3.4 dated 2020-12-12 and 0.3.5 dated 2022-11-22
DESCRIPTION | 12 MD5 | 19 - NEWS.md | 76 ++-- R/circleProgressiveLayout.R | 2 build/partial.rdb |only build/vignette.rds |binary inst/doc/graph_packing.html | 251 +++++++++------- inst/doc/intro.html | 438 ++++++++++++++++------------ inst/doc/progressive_packing.html | 589 +++++++++++++++++--------------------- man/circleProgressiveLayout.Rd | 2 src/RcppExports.cpp | 5 11 files changed, 739 insertions(+), 655 deletions(-)
Title: Bayesian Inference for Multinomial Models with Inequality
Constraints
Description: Implements Gibbs sampling and Bayes factors for multinomial models with
linear inequality constraints on the vector of probability parameters. As
special cases, the model class includes models that predict a linear order
of binomial probabilities (e.g., p[1] < p[2] < p[3] < .50) and mixture models
assuming that the parameter vector p must be inside the convex hull of a
finite number of predicted patterns (i.e., vertices). A formal definition of
inequality-constrained multinomial models and the implemented computational
methods is provided in: Heck, D.W., & Davis-Stober, C.P. (2019).
Multinomial models with linear inequality constraints: Overview and improvements
of computational methods for Bayesian inference. Journal of Mathematical
Psychology, 91, 70-87. <doi:10.1016/j.jmp.2019.03.004>.
Inequality-constrained multinomial models have applications in the area of
judgment and decision making to fit and test random utility models
(Regenwetter, M., Dana, J., & Davis [...truncated...]
Author: Daniel W. Heck [aut, cre]
Maintainer: Daniel W. Heck <daniel.heck@uni-marburg.de>
Diff between multinomineq versions 0.2.4 dated 2022-08-21 and 0.2.5 dated 2022-11-22
multinomineq-0.2.4/multinomineq/R/find_interior_point.R |only multinomineq-0.2.5/multinomineq/DESCRIPTION | 20 multinomineq-0.2.5/multinomineq/MD5 | 193 ++--- multinomineq-0.2.5/multinomineq/R/Ab_max.R | 33 multinomineq-0.2.5/multinomineq/R/auxiliary.R | 109 +- multinomineq-0.2.5/multinomineq/R/bf_binom.R | 30 multinomineq-0.2.5/multinomineq/R/bf_equality.R | 48 - multinomineq-0.2.5/multinomineq/R/bf_nonlinear.R | 34 multinomineq-0.2.5/multinomineq/R/checks.R | 301 ++++---- multinomineq-0.2.5/multinomineq/R/classes_ineq.R | 13 multinomineq-0.2.5/multinomineq/R/conjoint_measurement.R | 2 multinomineq-0.2.5/multinomineq/R/count_binomial.R | 84 +- multinomineq-0.2.5/multinomineq/R/count_multinomial.R | 78 +- multinomineq-0.2.5/multinomineq/R/count_nonconvex.R | 2 multinomineq-0.2.5/multinomineq/R/count_to.R | 92 +- multinomineq-0.2.5/multinomineq/R/data_hilbig2014_heck2017.R | 105 +- multinomineq-0.2.5/multinomineq/R/data_karabatsos2004.R | 28 multinomineq-0.2.5/multinomineq/R/data_regenwetter2012.R | 17 multinomineq-0.2.5/multinomineq/R/data_swop.R | 13 multinomineq-0.2.5/multinomineq/R/equality_constraints.R | 23 multinomineq-0.2.5/multinomineq/R/find_inside.R |only multinomineq-0.2.5/multinomineq/R/inside.R | 100 +- multinomineq-0.2.5/multinomineq/R/line_clipping.R | 30 multinomineq-0.2.5/multinomineq/R/ml_estimates.R | 369 +++++----- multinomineq-0.2.5/multinomineq/R/model_weights.R | 19 multinomineq-0.2.5/multinomineq/R/multinomineq_package.R | 2 multinomineq-0.2.5/multinomineq/R/nirt.R | 110 +- multinomineq-0.2.5/multinomineq/R/population_bf.R | 45 - multinomineq-0.2.5/multinomineq/R/posterior_predictive.R | 54 - multinomineq-0.2.5/multinomineq/R/postprob.R | 33 multinomineq-0.2.5/multinomineq/R/rpmultinom.R | 47 - multinomineq-0.2.5/multinomineq/R/run_parallel.R | 29 multinomineq-0.2.5/multinomineq/R/sampling_nonlinear.R | 100 +- multinomineq-0.2.5/multinomineq/R/sampling_polytope.R | 186 +++-- multinomineq-0.2.5/multinomineq/R/sampling_vertex.R | 58 + multinomineq-0.2.5/multinomineq/R/sort_inequalities.R | 47 - multinomineq-0.2.5/multinomineq/R/stochdom_Ab.R | 44 - multinomineq-0.2.5/multinomineq/R/stochdom_bf.R | 24 multinomineq-0.2.5/multinomineq/R/strategy_marginal.R | 132 ++- multinomineq-0.2.5/multinomineq/R/strategy_multiattribute.R | 215 +++-- multinomineq-0.2.5/multinomineq/R/strategy_unique.R | 68 + multinomineq-0.2.5/multinomineq/R/transform_Ab_V.R | 52 - multinomineq-0.2.5/multinomineq/inst/doc/multinomineq_intro.R | 111 +-- multinomineq-0.2.5/multinomineq/inst/doc/multinomineq_intro.Rmd | 117 +-- multinomineq-0.2.5/multinomineq/inst/doc/multinomineq_intro.html | 292 ++++--- multinomineq-0.2.5/multinomineq/man/Ab_drop_fixed.Rd | 12 multinomineq-0.2.5/multinomineq/man/Ab_max.Rd | 2 multinomineq-0.2.5/multinomineq/man/Ab_multinom.Rd | 2 multinomineq-0.2.5/multinomineq/man/Ab_sort.Rd | 20 multinomineq-0.2.5/multinomineq/man/bf_binom.Rd | 24 multinomineq-0.2.5/multinomineq/man/bf_equality.Rd | 28 multinomineq-0.2.5/multinomineq/man/bf_nonlinear.Rd | 16 multinomineq-0.2.5/multinomineq/man/count_binom.Rd | 22 multinomineq-0.2.5/multinomineq/man/count_multinom.Rd | 20 multinomineq-0.2.5/multinomineq/man/count_to_bf.Rd | 10 multinomineq-0.2.5/multinomineq/man/drop_fixed.Rd | 20 multinomineq-0.2.5/multinomineq/man/find_inside.Rd | 63 + multinomineq-0.2.5/multinomineq/man/heck2017.Rd | 36 multinomineq-0.2.5/multinomineq/man/heck2017_raw.Rd | 32 multinomineq-0.2.5/multinomineq/man/hilbig2014.Rd | 34 multinomineq-0.2.5/multinomineq/man/inside.Rd | 22 multinomineq-0.2.5/multinomineq/man/inside_binom.Rd | 40 - multinomineq-0.2.5/multinomineq/man/karabatsos2004.Rd | 28 multinomineq-0.2.5/multinomineq/man/ml_binom.Rd | 66 + multinomineq-0.2.5/multinomineq/man/model_weights.Rd | 6 multinomineq-0.2.5/multinomineq/man/population_bf.Rd | 6 multinomineq-0.2.5/multinomineq/man/postprob.Rd | 15 multinomineq-0.2.5/multinomineq/man/ppp_binom.Rd | 10 multinomineq-0.2.5/multinomineq/man/regenwetter2012.Rd | 17 multinomineq-0.2.5/multinomineq/man/rpbinom.Rd | 22 multinomineq-0.2.5/multinomineq/man/sampling_multinom.Rd | 36 multinomineq-0.2.5/multinomineq/man/sampling_nonlinear.Rd | 23 multinomineq-0.2.5/multinomineq/man/stochdom_bf.Rd | 6 multinomineq-0.2.5/multinomineq/man/strategy_marginal.Rd | 18 multinomineq-0.2.5/multinomineq/man/strategy_multiattribute.Rd | 8 multinomineq-0.2.5/multinomineq/man/strategy_postprob.Rd | 26 multinomineq-0.2.5/multinomineq/man/strategy_to_Ab.Rd | 14 multinomineq-0.2.5/multinomineq/man/strategy_unique.Rd | 10 multinomineq-0.2.5/multinomineq/man/swop5.Rd | 13 multinomineq-0.2.5/multinomineq/tests/testthat/Rplots.pdf |only multinomineq-0.2.5/multinomineq/tests/testthat/test_NIRT.R | 213 +++-- multinomineq-0.2.5/multinomineq/tests/testthat/test_V_dimensionality.R | 46 - multinomineq-0.2.5/multinomineq/tests/testthat/test_bisection.R | 13 multinomineq-0.2.5/multinomineq/tests/testthat/test_count.R | 88 +- multinomineq-0.2.5/multinomineq/tests/testthat/test_drop-add.R | 26 multinomineq-0.2.5/multinomineq/tests/testthat/test_encompassing_bf.R | 30 multinomineq-0.2.5/multinomineq/tests/testthat/test_hoijtink2014.R | 12 multinomineq-0.2.5/multinomineq/tests/testthat/test_karabatsos2005.R | 45 - multinomineq-0.2.5/multinomineq/tests/testthat/test_klaassen2018.R | 34 multinomineq-0.2.5/multinomineq/tests/testthat/test_loglik.R | 86 +- multinomineq-0.2.5/multinomineq/tests/testthat/test_ml_estimation.R | 90 +- multinomineq-0.2.5/multinomineq/tests/testthat/test_nonlinear.R | 44 - multinomineq-0.2.5/multinomineq/tests/testthat/test_sampling.R | 204 +++-- multinomineq-0.2.5/multinomineq/tests/testthat/test_sampling_vertex.R | 39 - multinomineq-0.2.5/multinomineq/tests/testthat/test_stochdom.R | 35 multinomineq-0.2.5/multinomineq/tests/testthat/test_strategy_postprob.R | 105 +- multinomineq-0.2.5/multinomineq/tests/testthat/test_strategy_predictions.R | 181 ++-- multinomineq-0.2.5/multinomineq/tests/testthat/test_transform_Ab_V.R | 20 multinomineq-0.2.5/multinomineq/vignettes/multinomineq_intro.Rmd | 117 +-- 99 files changed, 3271 insertions(+), 2393 deletions(-)
Title: Gliding Box Lacunarity and Other Metrics for 2D Random Closed
Sets
Description: Functions for estimating the gliding box lacunarity (GBL),
covariance, and pair-correlation of a random closed set (RACS) in 2D
from a binary coverage map (e.g. presence-absence land cover maps).
Contains a number of newly-developed covariance-based estimators of
GBL (Hingee et al., 2019) <doi:10.1007/s13253-019-00351-9> and
balanced estimators, proposed by Picka (2000)
<http://www.jstor.org/stable/1428408>, for covariance, centred
covariance, and pair-correlation. Also contains methods for
estimating contagion-like properties of RACS and simulating 2D Boolean
models. Binary coverage maps are usually represented as raster images
with pixel values of TRUE, FALSE or NA, with NA representing
unobserved pixels. A demo for extracting such a binary map from a
geospatial data format is provided. Binary maps may also be
represented using polygonal sets as the foreground, however for most
computations such maps are converted into raster images. The package
is based on research [...truncated...]
Author: Kassel Liam Hingee
Maintainer: Kassel Liam Hingee <kassel.hingee@gmail.com>
Diff between lacunaritycovariance versions 1.1-3 dated 2022-02-15 and 1.1-4 dated 2022-11-22
DESCRIPTION | 12 +++---- MD5 | 52 +++++++++++++++++----------------- NAMESPACE | 1 NEWS | 3 + R/contagdiscstate.R | 12 +++---- R/coverageprob.R | 1 R/gbl.R | 14 ++++----- R/gblc.R | 4 +- R/gblcc.R | 4 +- R/gblemp.R | 8 ++--- R/gblg.R | 2 - R/secondorderprops.R | 28 +++++++++--------- build/partial.rdb |binary build/vignette.rds |binary inst/doc/estimate_RACS_properties.pdf |binary man/cencovariance.Rd | 6 +-- man/contagdiscstate.Rd | 6 +-- man/contagpixelgrid.Rd | 6 +-- man/gbl.Rd | 6 +-- man/gblcc.Rd | 4 +- man/gblemp.Rd | 4 +- man/paircorr.Rd | 6 +-- man/placegrainsfromlib.Rd | 10 +++--- man/racscovariance.Rd | 6 +-- man/rbdd.Rd | 14 ++++----- man/rbdr.Rd | 8 ++--- man/rbpto.Rd | 10 +++--- 27 files changed, 114 insertions(+), 113 deletions(-)
More information about lacunaritycovariance at CRAN
Permanent link
Title: Determining and Evaluating High-Risk Zones
Description: Functions for determining and evaluating high-risk zones and
simulating and thinning point process data, as described in 'Determining
high risk zones using point process methodology - Realization by building
an R package' Seibold (2012) <http://highriskzone.r-forge.r-project.org/Bachelorarbeit.pdf>
and 'Determining high-risk zones for unexploded World War II bombs by using point
process methodology', Mahling et al. (2013) <doi:10.1111/j.1467-9876.2012.01055.x>.
Author: Heidi Seibold <Heidi.Seibold@uzh.ch>, Monia Mahling
<monia.mahling@stat.uni-muenchen.de>, Sebastian Linne
<Sebastian.Linne@campus.lmu.de>, Felix Guenther
<felix.guenther@stat.uni-muenchen.de>
Maintainer: Rickmer Schulte <R.Schulte@campus.lmu.de>
Diff between highriskzone versions 1.4.7 dated 2022-03-04 and 1.4.8 dated 2022-11-22
DESCRIPTION | 12 +++---- MD5 | 60 +++++++++++++++++++------------------- NAMESPACE | 2 - R/bootcorrect.R | 4 +- R/bootcorrect_restr.R | 2 - R/det_hrz_eval_ar.R | 2 - R/dethrz.R | 2 - R/dethrz_restr.R | 4 +- R/dethrzbase.R | 8 ++--- R/detnsintens_restr.R | 4 +- R/estintens.R | 6 +-- R/estintens_weight.R | 6 +-- R/simulationbase.R | 8 ++--- man/bootcor.Rd | 2 - man/bootcor_restr.Rd | 2 - man/bootcorr.Rd | 2 - man/check_det_hrz_input.Rd | 2 - man/check_det_hrz_restr_input.Rd | 2 - man/det_alpha.Rd | 2 - man/det_hrz.Rd | 2 - man/det_hrz_eval_ar.Rd | 2 - man/det_hrz_restr.Rd | 4 +- man/det_nsintens.Rd | 4 +- man/det_nsintens_restr.Rd | 4 +- man/det_threshold.Rd | 2 - man/det_thresholdfromarea.Rd | 2 - man/det_thresholdfromarea_rest.Rd | 2 - man/est_intens.Rd | 6 +-- man/est_intens_weight.Rd | 6 +-- man/eval_method.Rd | 2 - man/sim_nsppp.Rd | 2 - 31 files changed, 85 insertions(+), 85 deletions(-)
Title: Fitting Deep Conditional Transformation Models
Description: Allows for the specification of deep conditional transformation
models (DCTMs) and ordinal neural network transformation models, as
described in Baumann et al (2021) <doi:10.1007/978-3-030-86523-8_1> and
Kook et al (2022) <doi:10.1016/j.patcog.2021.108263>. Extensions such as
autoregressive DCTMs (Ruegamer et al, 2022, <doi:10.48550/arXiv.2110.08248>)
and transformation ensembles (Kook et al, 2022, <doi:10.48550/arXiv.2205.12729>)
are implemented.
Author: Lucas Kook [aut, cre],
Philipp Baumann [aut],
David Ruegamer [aut]
Maintainer: Lucas Kook <lucasheinrich.kook@gmail.com>
Diff between deeptrafo versions 0.1 dated 2022-11-18 and 0.1-1 dated 2022-11-22
DESCRIPTION | 6 - MD5 | 16 +-- R/helperfuns.R | 64 +------------- inst/python/layers/__init__.py | 1 inst/python/layers/__pycache__/__init__.cpython-38.pyc |binary inst/python/layers/__pycache__/eval_bsp.cpython-38.pyc |binary inst/python/layers/__pycache__/mono_layers.cpython-38.pyc |only inst/python/layers/eval_bsp.py | 6 - inst/python/layers/mono_layers.py |only tests/testthat/Rplots.pdf |binary 10 files changed, 23 insertions(+), 70 deletions(-)
Title: Competing Proximal Gradients Library
Description: Functions to generate ensembles of generalized linear models using
competing proximal gradients. The optimal sparsity and diversity
tuning parameters are selected via an alternating grid search.
Author: Anthony Christidis [aut, cre],
Stefan Van Aelst [aut],
Ruben Zamar [aut]
Maintainer: Anthony Christidis <anthony.christidis@stat.ubc.ca>
Diff between CPGLIB versions 1.1.0 dated 2022-06-03 and 1.1.1 dated 2022-11-22
DESCRIPTION | 8 ++++---- MD5 | 28 ++++++++++++++-------------- NEWS | 5 ++++- src/CPGLIB.cpp | 2 +- src/CPGLIB.hpp | 2 +- src/CPGLIB_Main.cpp | 2 +- src/CV_CPGLIB.cpp | 2 +- src/CV_CPGLIB.hpp | 2 +- src/CV_CPGLIB_Main.cpp | 2 +- src/CV_ProxGrad.cpp | 2 +- src/CV_ProxGrad.hpp | 2 +- src/CV_ProxGrad_Main.cpp | 2 +- src/ProxGrad.cpp | 2 +- src/ProxGrad.hpp | 2 +- src/ProxGrad_Main.cpp | 2 +- 15 files changed, 34 insertions(+), 31 deletions(-)
Title: Kaplan-Meier Estimator with Constraints for Right Censored Data
-- a Recursive Computational Algorithm
Description: Given constraints for right censored data, we use a recursive computational algorithm to calculate the the "constrained" Kaplan-Meier estimator. The constraint is assumed given in linear estimating equations or mean functions. We also illustrate how this leads to the empirical likelihood ratio test with right censored data and accelerated failure time model with given coefficients. EM algorithm from emplik package is used to get the initial value. The properties and performance of the EM algorithm is discussed in Mai Zhou and Yifan Yang (2015)<doi: 10.1007/s00180-015-0567-9> and Mai Zhou and Yifan Yang (2017) <doi: 10.1002/wics.1400>. More applications could be found in Mai Zhou (2015) <doi: 10.1201/b18598>.
Author: Yifan Yang [aut, cre, cph],
Mai Zhou [aut]
Maintainer: Yifan Yang <yfyang.86@hotmail.com>
Diff between kmc versions 0.2-4 dated 2020-03-16 and 0.4-2 dated 2022-11-22
DESCRIPTION | 25 ++++++---- MD5 | 30 ++++++------ NAMESPACE | 2 R/RcppExport.R | 49 ++++++++++++++++--- R/kmc.R | 79 +++++++++++++++++++++++--------- R/kmcmaskel.R | 130 ----------------------------------------------------- man/check_G_mat.Rd |only man/kmc.bjtest.Rd | 22 +++++++- man/kmc.clean.Rd |only man/kmc.solve.Rd | 61 +++++++++++++----------- man/plotkmc.Rd | 23 +++++---- src/RcppExport.cpp | 4 + src/common.h | 49 ++++++++++--------- src/kmc.cpp | 86 +++++++++++++++++++++++++++-------- src/kmc_init.c | 4 + src/surv2.c | 6 -- tests |only 17 files changed, 301 insertions(+), 269 deletions(-)
Title: Bootstrap Functions (Originally by Angelo Canty for S)
Description: Functions and datasets for bootstrapping from the
book "Bootstrap Methods and Their Application" by A. C. Davison and
D. V. Hinkley (1997, CUP), originally written by Angelo Canty for S.
Author: Angelo Canty [aut],
Brian Ripley [aut, trl, cre]
Maintainer: Brian Ripley <ripley@stats.ox.ac.uk>
Diff between boot versions 1.3-28 dated 2021-05-03 and 1.3-28.1 dated 2022-11-22
ChangeLog | 4 ++++ DESCRIPTION | 8 ++++---- MD5 | 6 +++--- man/EEF.profile.Rd | 2 +- 4 files changed, 12 insertions(+), 8 deletions(-)
Title: Organising Projects
Description: A system to help you organize projects. Most analyses have three (or more) main sections: code, results, and data, each with different requirements (version control/sharing/encryption). You provide folder locations and 'org' helps you take care of the details.
Author: Richard Aubrey White [aut, cre]
Maintainer: Richard Aubrey White <hello@rwhite.no>
Diff between org versions 2022.7.21 dated 2022-07-20 and 2022.11.23 dated 2022-11-22
org-2022.11.23/org/DESCRIPTION | 17 +++++++---------- org-2022.11.23/org/LICENSE | 2 +- org-2022.11.23/org/MD5 | 13 ++++++------- org-2022.11.23/org/R/3_onAttach.R | 2 +- org-2022.11.23/org/README.md | 18 +++++++++--------- org-2022.11.23/org/inst/doc/org.html | 14 +++++++------- org-2022.11.23/org/man/figures/logo.png |binary org-2022.7.21/org/man/figures/fhi.png |only 8 files changed, 31 insertions(+), 35 deletions(-)
Title: Algorithms for Bundling Edges in Networks and Visualizing Flow
and Metro Maps
Description: Implements several algorithms for bundling edges in networks and flow and metro map layouts. This includes force directed edge bundling <doi:10.1111/j.1467-8659.2009.01450.x>, a flow algorithm based on Steiner trees<doi:10.1080/15230406.2018.1437359> and a multicriteria optimization method for metro map layouts <doi:10.1109/TVCG.2010.24>.
Author: David Schoch [aut, cre]
Maintainer: David Schoch <david@schochastics.net>
Diff between edgebundle versions 0.4.0 dated 2022-07-04 and 0.4.1 dated 2022-11-22
DESCRIPTION | 8 ++++---- MD5 | 9 ++++++--- NEWS.md | 6 ++++++ R/edgebundle-package.R |only README.md | 22 +++++++++++----------- inst |only man/edgebundle-package.Rd |only 7 files changed, 27 insertions(+), 18 deletions(-)