Title: A Graphical User Interface for Network Modeling with 'Statnet'
Description: A graphical user interface for network modeling with the 'statnet'
software.
Author: Martina Morris [cre, aut],
Emily Beylerian [aut],
Kirk Li [ctb],
Samuel Jenness [ctb]
Maintainer: Martina Morris <morrism@uw.edu>
Diff between statnetWeb versions 0.4.0 dated 2015-11-05 and 0.5.0 dated 2018-07-21
statnetWeb-0.4.0/statnetWeb/man/run_sw.Rd |only statnetWeb-0.5.0/statnetWeb/DESCRIPTION | 22 statnetWeb-0.5.0/statnetWeb/MD5 | 28 statnetWeb-0.5.0/statnetWeb/NAMESPACE | 46 statnetWeb-0.5.0/statnetWeb/R/run_sw.R | 32 statnetWeb-0.5.0/statnetWeb/R/statnetWeb-package.R | 56 statnetWeb-0.5.0/statnetWeb/README.md | 62 statnetWeb-0.5.0/statnetWeb/inst/shiny/global.R | 336 statnetWeb-0.5.0/statnetWeb/inst/shiny/server.R | 7684 ++++----- statnetWeb-0.5.0/statnetWeb/inst/shiny/ui.R | 2798 +-- statnetWeb-0.5.0/statnetWeb/inst/shiny/www/alert.js | 490 statnetWeb-0.5.0/statnetWeb/inst/shiny/www/busy.js | 28 statnetWeb-0.5.0/statnetWeb/inst/shiny/www/mycosmo.css |13462 ++++++++--------- statnetWeb-0.5.0/statnetWeb/inst/shiny/www/style.css | 1106 - statnetWeb-0.5.0/statnetWeb/man/run_sW.Rd |only statnetWeb-0.5.0/statnetWeb/man/statnetWeb.Rd | 24 16 files changed, 13097 insertions(+), 13077 deletions(-)
Title: Size-Constrained Clustering
Description: Provides wrappers for 'scclust', a C library for computationally efficient
size-constrained clustering with near-optimal performance.
See <https://github.com/fsavje/scclust> for more information.
Author: Fredrik Savje [aut, cre],
Michael Higgins [aut],
Jasjeet Sekhon [aut]
Maintainer: Fredrik Savje <fredrik.savje@yale.edu>
Diff between scclust versions 0.1.1 dated 2017-05-22 and 0.1.2 dated 2018-07-21
DESCRIPTION | 14 +++++++------- MD5 | 6 +++--- NEWS.md | 5 +++++ tests/testthat/config.R | 3 +++ 4 files changed, 18 insertions(+), 10 deletions(-)
Title: Quick Generalized Full Matching
Description: Provides functions for constructing near-optimal generalized full matching.
Generalized full matching is an extension of the original full matching method
to situations with more intricate study designs. The package is made with
large data sets in mind and derives matches more than an order of magnitude
quicker than other methods.
Author: Fredrik Savje [aut, cre],
Jasjeet Sekhon [aut],
Michael Higgins [aut]
Maintainer: Fredrik Savje <fredrik.savje@yale.edu>
Diff between quickmatch versions 0.1.2 dated 2017-05-20 and 0.1.3 dated 2018-07-21
DESCRIPTION | 14 +++++++------- MD5 | 26 +++++++++++++++----------- NAMESPACE | 1 + NEWS.md |only R/covariate_averages.R |only R/covariate_balance.R | 29 +++++++---------------------- R/lm_match.R | 2 +- R/matching_weights.R | 2 +- R/quickmatch-package.R | 8 ++++---- README.md | 30 ++++++++++++++++++++++++------ man/covariate_averages.Rd |only man/lm_match.Rd | 2 +- man/matching_weights.Rd | 2 +- man/quickmatch-package.Rd | 4 ++-- tests/testthat/test_covariate_averages.R |only tests/testthat/test_func_input_check.R | 26 ++++++++++++++++++++++++++ 16 files changed, 90 insertions(+), 56 deletions(-)
Title: Annotate Statistical Tests for 'ggplot2'
Description: Automatically performs desired statistical tests (e.g. wilcox.test(), t.test()) to compare between groups,
and adds the resulting p-values to the plot with an annotation bar.
Visualizing group differences are frequently performed by boxplots, bar plots, etc.
Statistical test results are often needed to be annotated on these plots.
This package provides a convenient function that works on 'ggplot2' objects,
performs the desired statistical test between groups of interest and annotates the test results on the plot.
Author: Jun Cheng [aut, cre]
Maintainer: Jun Cheng <s6juncheng@gmail.com>
Diff between ggpval versions 0.2.0 dated 2017-07-26 and 0.2.1 dated 2018-07-21
ggpval-0.2.0/ggpval/tests/test-add_pval.R |only ggpval-0.2.1/ggpval/DESCRIPTION | 8 ++++---- ggpval-0.2.1/ggpval/MD5 | 11 ++++++----- ggpval-0.2.1/ggpval/R/add_pval_ggplot.R | 30 ++++++++++++++++++------------ ggpval-0.2.1/ggpval/build/vignette.rds |binary ggpval-0.2.1/ggpval/inst/doc/ggpval.html | 12 ++++++------ ggpval-0.2.1/ggpval/tests/testthat |only ggpval-0.2.1/ggpval/tests/testthat.R |only 8 files changed, 34 insertions(+), 27 deletions(-)
Title: Gaussian Mixture Models, K-Means, Mini-Batch-Kmeans and
K-Medoids Clustering
Description: Gaussian mixture models, k-means, mini-batch-kmeans and k-medoids clustering with the option to plot, validate, predict (new data) and estimate the optimal number of clusters. The package takes advantage of 'RcppArmadillo' to
speed up the computationally intensive parts of the functions. For more information, see (i) "Clustering in an Object-Oriented Environment" by Anja Struyf, Mia Hubert, Peter Rousseeuw (1997), Journal of Statistical Software, <doi:10.18637/jss.v001.i04>; (ii) "Web-scale k-means clustering" by D. Sculley (2010), ACM Digital Library, <doi:10.1145/1772690.1772862>; (iii) "Armadillo: a template-based C++ library for linear algebra" by Sanderson et al (2016), The Journal of Open Source Software, <doi:10.21105/joss.00026>.
Author: Lampros Mouselimis <mouselimislampros@gmail.com>
Maintainer: Lampros Mouselimis <mouselimislampros@gmail.com>
Diff between ClusterR versions 1.1.2 dated 2018-05-06 and 1.1.3 dated 2018-07-21
DESCRIPTION | 8 ++++---- MD5 | 20 ++++++++++---------- NEWS.md | 5 +++++ R/clustering_functions.R | 12 ++++++------ README.md | 3 ++- inst/doc/the_clusterR_package.html | 12 ++++++------ man/KMeans_rcpp.Rd | 4 ++-- man/MiniBatchKmeans.Rd | 2 +- man/Optimal_Clusters_KMeans.Rd | 2 +- man/external_validation.Rd | 2 +- man/predict_KMeans.Rd | 2 +- 11 files changed, 39 insertions(+), 33 deletions(-)
Title: A GeoJson Processing Toolkit
Description: Includes functions for processing GeoJson objects <https://en.wikipedia.org/wiki/GeoJSON> relying on 'RFC 7946' <https://tools.ietf.org/pdf/rfc7946.pdf>. The geojson encoding is based on 'json11', a tiny JSON library for 'C++11' <https://github.com/dropbox/json11>. Furthermore, the source code is exported in R through the 'Rcpp' and 'RcppArmadillo' packages.
Author: Lampros Mouselimis <mouselimislampros@gmail.com>
Maintainer: Lampros Mouselimis <mouselimislampros@gmail.com>
Diff between geojsonR versions 1.0.4 dated 2017-11-30 and 1.0.5 dated 2018-07-21
DESCRIPTION | 8 ++++---- MD5 | 14 +++++++------- NEWS.md | 5 +++++ R/utils.R | 8 ++++---- README.md | 3 ++- build/vignette.rds |binary inst/doc/the_geojsonR_package.html | 4 ++-- man/shiny_from_JSON.Rd | 2 +- 8 files changed, 25 insertions(+), 19 deletions(-)
Title: The Extreme Learning Machine Algorithm
Description: Training and predict functions for Single Hidden-layer Feedforward Neural Networks (SLFN) using the Extreme Learning Machine (ELM) algorithm. The ELM algorithm differs from the traditional gradient-based algorithms for very short training times (it doesn't need any iterative tuning, this makes learning time very fast) and there is no need to set any other parameters like learning rate, momentum, epochs, etc. This is a reimplementation of the 'elmNN' package using 'RcppArmadillo' after the 'elmNN' package was archived. For more information, see "Extreme learning machine: Theory and applications" by Guang-Bin Huang, Qin-Yu Zhu, Chee-Kheong Siew (2006), Elsevier B.V, <doi:10.1016/j.neucom.2005.12.126>.
Author: Lampros Mouselimis [aut, cre],
Alberto Gosso [aut]
Maintainer: Lampros Mouselimis <mouselimislampros@gmail.com>
Diff between elmNNRcpp versions 1.0.0 dated 2018-07-05 and 1.0.1 dated 2018-07-21
DESCRIPTION | 10 ++- MD5 | 16 ++--- NEWS.md | 4 + README.md | 15 +++++ inst/doc/extreme_learning_machine.R | 85 +++++++++++++++++++++------- inst/doc/extreme_learning_machine.Rmd | 89 +++++++++++++++++++++--------- inst/doc/extreme_learning_machine.html | 97 +++++++++++++++++++++++---------- src/init.c | 2 vignettes/extreme_learning_machine.Rmd | 89 +++++++++++++++++++++--------- 9 files changed, 291 insertions(+), 116 deletions(-)
Title: Bivariate Angular Mixture Models
Description: Fit (using Bayesian methods) and simulate mixtures of univariate and bivariate angular distributions. Chakraborty and Wong (2017) <arXiv:1708.07804> .
Author: Saptarshi Chakraborty,
Samuel W.K. Wong
Maintainer: Saptarshi Chakraborty <chakra.saptarshi@gmail.com>
Diff between BAMBI versions 2.0.0 dated 2018-06-21 and 2.0.1 dated 2018-07-21
DESCRIPTION | 11 ++++++----- MD5 | 8 ++++---- NAMESPACE | 1 + R/fit_mixmodel.R | 19 ++++++++++--------- man/fit_angmix.Rd | 2 +- 5 files changed, 22 insertions(+), 19 deletions(-)
Title: Non Metric Space (Approximate) Library
Description: A Non-Metric Space Library ('NMSLIB' <https://github.com/searchivarius/nmslib>) wrapper, which according to the authors "is an efficient cross-platform similarity search library and a toolkit for evaluation of similarity search methods. The goal of the 'NMSLIB' <https://github.com/searchivarius/nmslib> Library is to create an effective and comprehensive toolkit for searching in generic non-metric spaces. Being comprehensive is important, because no single method is likely to be sufficient in all cases. Also note that exact solutions are hardly efficient in high dimensions and/or non-metric spaces. Hence, the main focus is on approximate methods". The wrapper also includes Approximate Kernel k-Nearest-Neighbor functions based on the 'NMSLIB' <https://github.com/searchivarius/nmslib> 'Python' Library.
Author: Lampros Mouselimis [aut, cre],
B. Naidan [cph] (Author of the Non-Metric Space Library (NMSLIB)),
L. Boytsov [cph] (Author of the Non-Metric Space Library (NMSLIB)),
Yu. Malkov [cph] (Author of the Non-Metric Space Library (NMSLIB)),
B. Frederickson [cph] (Author of the Non-Metric Space Library (NMSLIB)),
D. Novak [cph] (Author of the Non-Metric Space Library (NMSLIB))
Maintainer: Lampros Mouselimis <mouselimislampros@gmail.com>
Diff between nmslibR versions 1.0.2 dated 2018-05-10 and 1.0.3 dated 2018-07-21
DESCRIPTION | 8 +-- MD5 | 8 +-- NEWS.md | 4 + README.md | 84 +++++++++++++++++++------------------- inst/doc/the_nmslibR_package.html | 4 - 5 files changed, 57 insertions(+), 51 deletions(-)
Title: Structural Equation Multidimensional Scaling
Description: Fits a structural equation multidimensional scaling (SEMDS) model for asymmetric and three-way input dissimilarities. It assumes that the dissimilarities are measured with errors. The latent dissimilarities are estimated as factor scores within an SEM framework while the objects are represented in a low-dimensional space as in MDS.
Author: Patrick Mair [aut, cre],
Jose Fernando Vera [aut]
Maintainer: Patrick Mair <mair@fas.harvard.edu>
Diff between semds versions 0.9-4 dated 2018-06-14 and 0.9-5 dated 2018-07-21
semds-0.9-4/semds/R/normDissN.R |only semds-0.9-5/semds/DESCRIPTION | 11 ++++------- semds-0.9-5/semds/MD5 | 17 ++++++++--------- semds-0.9-5/semds/R/semds.R | 16 ++++++++++++---- semds-0.9-5/semds/data/AvaRegions.rda |binary semds-0.9-5/semds/data/BrahmsNorm.rda |binary semds-0.9-5/semds/data/Miller.rda |binary semds-0.9-5/semds/data/SBanks2008D.rda |binary semds-0.9-5/semds/data/SBanks2012D.rda |binary semds-0.9-5/semds/man/AvaRegions.Rd | 4 +++- 10 files changed, 27 insertions(+), 21 deletions(-)
Title: k-Nearest Neighbor Join for Spatial Data
Description: K-nearest neighbor search for projected and non-projected 'sf' spatial layers. Nearest neighbor search uses (1) C implementation of the Vincenty Formula for lon-lat point layers, (2) function nn2() from package 'RANN' for projected point layers, or (3) function st_distance() from package 'sf' for line or polygon layers.
Author: Michael Dorman [aut, cre],
Johnathan Rush [ctb],
Ian Hough [ctb],
Jan Antala [ctb, cph] (Author of C code for Vincenty distance)
Maintainer: Michael Dorman <dorman@post.bgu.ac.il>
Diff between nngeo versions 0.2.0 dated 2018-07-18 and 0.2.1 dated 2018-07-21
nngeo-0.2.0/nngeo/src/Makevars |only nngeo-0.2.0/nngeo/src/Makevars.win |only nngeo-0.2.1/nngeo/DESCRIPTION | 6 +++--- nngeo-0.2.1/nngeo/MD5 | 12 +++++------- nngeo-0.2.1/nngeo/NEWS.md | 6 +++++- nngeo-0.2.1/nngeo/build/vignette.rds |binary nngeo-0.2.1/nngeo/inst/doc/intro.pdf |binary nngeo-0.2.1/nngeo/src/distance.cpp | 1 - 8 files changed, 13 insertions(+), 12 deletions(-)
Title: Regularized Linear Models
Description: Algorithms for fitting model-based penalized coefficient paths. Currently the models include penalized Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial regression models. The penalties include least absolute shrinkage and selection operator (LASSO), smoothly clipped absolute deviation (SCAD) and minimax concave penalty (MCP), and each possibly combining with L_2 penalty. See Wang et al. (2014) <doi:10.1002/sim.6314>, Wang et al. (2015) <doi:10.1002/bimj.201400143>, Wang et al. (2016) <doi:10.1177/0962280214530608>.
Author: Zhu Wang, with contributions from Achim Zeileis, Simon Jackman, Brian Ripley, Trevor Hastie, Rob Tibshirani, Balasubramanian Narasimhan, Gil Chu and Patrick Breheny
Maintainer: Zhu Wang <zwang@connecticutchildrens.org>
Diff between mpath versions 0.3-4 dated 2017-10-23 and 0.3-5 dated 2018-07-21
DESCRIPTION | 10 +++++----- MD5 | 28 ++++++++++++++++------------ NEWS | 3 ++- R/glmreg.R | 4 ++-- R/glmregNB.R | 7 ++++--- R/zipath.R | 38 ++++++++++++++++++++++++-------------- build/vignette.rds |binary inst/doc/brcancer.R |only inst/doc/brcancer.Rnw |only inst/doc/brcancer.pdf |only inst/doc/german.R | 15 ++++++++++++++- inst/doc/german.Rnw | 12 ++++++++++-- inst/doc/german.pdf |binary inst/doc/static_german.pdf |binary man/tuning_zipath.Rd | 5 +++-- vignettes/brcancer.Rnw |only vignettes/german.Rnw | 12 ++++++++++-- 17 files changed, 90 insertions(+), 44 deletions(-)
Title: Time Series Clustering Along with Optimizations for the Dynamic
Time Warping Distance
Description: Time series clustering along with optimized techniques related
to the Dynamic Time Warping distance and its corresponding lower bounds.
Implementations of partitional, hierarchical, fuzzy, k-Shape and TADPole
clustering are available. Functionality can be easily extended with
custom distance measures and centroid definitions. Implementations of
DTW barycenter averaging, a distance based on global alignment kernels,
and the soft-DTW distance and centroid routines are also provided.
All included distance functions have custom loops optimized for the
calculation of cross-distance matrices, including parallelization support.
Several cluster validity indices are included.
Author: Alexis Sarda-Espinosa
Maintainer: Alexis Sarda <alexis.sarda@gmail.com>
Diff between dtwclust versions 5.4.1 dated 2018-06-10 and 5.5.0 dated 2018-07-21
dtwclust-5.4.1/dtwclust/src/centroids/centroids.h |only dtwclust-5.4.1/dtwclust/src/distance-calculators |only dtwclust-5.4.1/dtwclust/src/distances/distances-details.h |only dtwclust-5.4.1/dtwclust/src/distances/distances.cpp |only dtwclust-5.4.1/dtwclust/src/distances/distances.h |only dtwclust-5.4.1/dtwclust/src/distmat-fillers |only dtwclust-5.4.1/dtwclust/src/distmat-loops |only dtwclust-5.4.1/dtwclust/src/tadpole/tadpole.h |only dtwclust-5.4.1/dtwclust/src/utils/R-utils.h |only dtwclust-5.5.0/dtwclust/DESCRIPTION | 10 dtwclust-5.5.0/dtwclust/MD5 | 145 - dtwclust-5.5.0/dtwclust/NAMESPACE | 1 dtwclust-5.5.0/dtwclust/R/CENTROIDS-pam.R |only dtwclust-5.5.0/dtwclust/R/CENTROIDS-sdtw-cent.R | 180 - dtwclust-5.5.0/dtwclust/R/CLUSTERING-all-cent2.R | 473 ++--- dtwclust-5.5.0/dtwclust/R/CLUSTERING-compare-clusterings.R | 29 dtwclust-5.5.0/dtwclust/R/CLUSTERING-ddist2.R | 7 dtwclust-5.5.0/dtwclust/R/CLUSTERING-repeat-clustering.R | 16 dtwclust-5.5.0/dtwclust/R/CLUSTERING-tsclust.R | 24 dtwclust-5.5.0/dtwclust/R/DISTANCES-dtw-lb.R | 4 dtwclust-5.5.0/dtwclust/R/DISTANCES-lb-improved.R | 4 dtwclust-5.5.0/dtwclust/R/DISTANCES-lb-keogh.R | 6 dtwclust-5.5.0/dtwclust/R/DISTANCES-sdtw.R | 180 - dtwclust-5.5.0/dtwclust/R/GENERICS-cvi.R | 548 ++--- dtwclust-5.5.0/dtwclust/R/S4-TSClusters-methods.R | 4 dtwclust-5.5.0/dtwclust/R/SHINY-ssdtwclust.R | 4 dtwclust-5.5.0/dtwclust/R/UTILS-tslist.R | 106 - dtwclust-5.5.0/dtwclust/R/UTILS-utils.R | 4 dtwclust-5.5.0/dtwclust/R/pkg.R | 348 +-- dtwclust-5.5.0/dtwclust/build/vignette.rds |binary dtwclust-5.5.0/dtwclust/data/dtwclustTimings.rda |binary dtwclust-5.5.0/dtwclust/inst/NEWS.Rd | 31 dtwclust-5.5.0/dtwclust/inst/doc/dtwclust.Rnw | 327 +++ dtwclust-5.5.0/dtwclust/inst/doc/dtwclust.pdf |binary dtwclust-5.5.0/dtwclust/inst/doc/parallelization-considerations.html | 10 dtwclust-5.5.0/dtwclust/inst/doc/timing-experiments.Rmd | 6 dtwclust-5.5.0/dtwclust/inst/doc/timing-experiments.html | 42 dtwclust-5.5.0/dtwclust/man/cvi.Rd | 14 dtwclust-5.5.0/dtwclust/man/pam_cent.Rd |only dtwclust-5.5.0/dtwclust/man/sdtw_cent.Rd | 2 dtwclust-5.5.0/dtwclust/man/ssdtwclust.Rd | 4 dtwclust-5.5.0/dtwclust/man/tsclust.Rd | 16 dtwclust-5.5.0/dtwclust/src/centroids/R-gateways.h |only dtwclust-5.5.0/dtwclust/src/centroids/dba.cpp | 95 - dtwclust-5.5.0/dtwclust/src/centroids/sdtw-cent.cpp | 73 dtwclust-5.5.0/dtwclust/src/distances/R-gateways.cpp |only dtwclust-5.5.0/dtwclust/src/distances/R-gateways.h |only dtwclust-5.5.0/dtwclust/src/distances/calculators.cpp |only dtwclust-5.5.0/dtwclust/src/distances/calculators.h |only dtwclust-5.5.0/dtwclust/src/distances/details.h |only dtwclust-5.5.0/dtwclust/src/distances/dtw-basic.cpp | 156 - dtwclust-5.5.0/dtwclust/src/distances/lbi.cpp | 31 dtwclust-5.5.0/dtwclust/src/distances/lbk.cpp | 20 dtwclust-5.5.0/dtwclust/src/distances/logGAK.cpp | 97 - dtwclust-5.5.0/dtwclust/src/distances/soft-dtw.cpp | 52 dtwclust-5.5.0/dtwclust/src/distmat/R-gateways.h |only dtwclust-5.5.0/dtwclust/src/distmat/distmat-loop.cpp |only dtwclust-5.5.0/dtwclust/src/distmat/dtw-lb.cpp |only dtwclust-5.5.0/dtwclust/src/distmat/fillers.cpp |only dtwclust-5.5.0/dtwclust/src/distmat/fillers.h |only dtwclust-5.5.0/dtwclust/src/dtwclust.h | 10 dtwclust-5.5.0/dtwclust/src/tadpole/R-gateways.h |only dtwclust-5.5.0/dtwclust/src/tadpole/tadpole.cpp | 50 dtwclust-5.5.0/dtwclust/src/utils/KahanSummer.cpp | 8 dtwclust-5.5.0/dtwclust/src/utils/KahanSummer.h |only dtwclust-5.5.0/dtwclust/src/utils/R-gateways.h |only dtwclust-5.5.0/dtwclust/src/utils/R-utils.cpp | 10 dtwclust-5.5.0/dtwclust/src/utils/SurrogateMatrix.h | 33 dtwclust-5.5.0/dtwclust/src/utils/envelope.cpp | 12 dtwclust-5.5.0/dtwclust/src/utils/utils.cpp | 12 dtwclust-5.5.0/dtwclust/src/utils/utils.h | 28 dtwclust-5.5.0/dtwclust/tests/testthat/integration/custom-dist.R | 30 dtwclust-5.5.0/dtwclust/tests/testthat/integration/proxy.R | 268 +- dtwclust-5.5.0/dtwclust/tests/testthat/system/comparisons.R | 945 +++++----- dtwclust-5.5.0/dtwclust/tests/testthat/system/invalid-inputs.R | 1 dtwclust-5.5.0/dtwclust/tests/testthat/unit/centroids.R | 10 dtwclust-5.5.0/dtwclust/tests/testthat/unit/configs.R | 332 +-- dtwclust-5.5.0/dtwclust/tests/testthat/unit/cvis.R | 5 dtwclust-5.5.0/dtwclust/tests/testthat/unit/distances.R | 529 ++--- dtwclust-5.5.0/dtwclust/tests/testthat/unit/methods.R | 641 +++--- dtwclust-5.5.0/dtwclust/tests/testthat/unit/misc.R | 308 +-- dtwclust-5.5.0/dtwclust/vignettes/REFERENCES.bib | 34 dtwclust-5.5.0/dtwclust/vignettes/dtwclust.Rnw | 327 +++ dtwclust-5.5.0/dtwclust/vignettes/timing-experiments.Rmd | 6 84 files changed, 3698 insertions(+), 2970 deletions(-)
Title: Univariate Feature Selection and Compound Covariate for
Predicting Survival
Description: Univariate feature selection and compound covariate methods under the Cox model with high-dimensional features (e.g., gene expressions).
Available are survival data for non-small-cell lung cancer patients with gene expressions (Chen et al 2007 New Engl J Med) <DOI:10.1056/NEJMoa060096>,
statistical methods in Emura et al (2012 PLoS ONE) <DOI:10.1371/journal.pone.0047627>,
Emura & Chen (2016 Stat Methods Med Res) <DOI:10.1177/0962280214533378>, and Emura et al. (2018-)<to appear>.
Algorithms for generating correlated gene expressions are also available.
Author: Takeshi Emura, Hsuan-Yu Chen, Shigeyuki Matsui, Yi-Hau Chen
Maintainer: Takeshi Emura <takeshiemura@gmail.com>
Diff between compound.Cox versions 3.13 dated 2018-07-12 and 3.14 dated 2018-07-21
DESCRIPTION | 10 +++---- MD5 | 12 ++++---- R/uni.selection.R | 60 ++++++++++++++++++++++---------------------- man/compound.Cox-package.Rd | 10 +++---- man/uni.Wald.Rd | 11 ++++---- man/uni.score.Rd | 9 +++--- man/uni.selection.Rd | 53 ++++++++++++++++++++++---------------- 7 files changed, 88 insertions(+), 77 deletions(-)
Title: Unified Handling of Graphics Devices
Description: Functions for creating plots and image files in a unified way
regardless of output format (EPS, PDF, PNG, SVG, TIFF, WMF, etc.). Default
device options as well as scales and aspect ratios are controlled in a uniform
way across all device types. Switching output format requires minimal changes
in code. This package is ideal for large-scale batch processing, because it
will never leave open graphics devices or incomplete image files behind, even on
errors or user interrupts.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>
Diff between R.devices versions 2.15.1 dated 2016-11-10 and 2.16.0 dated 2018-07-21
R.devices-2.15.1/R.devices/R/006.fixVarArgs.R |only R.devices-2.15.1/R.devices/inst/exdata/capturePlot,ostype=unix,arch=i686,ptrsize=4,endian=little.rds |only R.devices-2.15.1/R.devices/inst/exdata/capturePlot,ostype=unix,arch=x86_64,ptrsize=8,endian=little.rds |only R.devices-2.15.1/R.devices/inst/exdata/capturePlot,ostype=windows,arch=i386,ptrsize=4,endian=little.rds |only R.devices-2.15.1/R.devices/inst/exdata/capturePlot,ostype=windows,arch=x86_64,ptrsize=8,endian=little.rds |only R.devices-2.16.0/R.devices/DESCRIPTION | 14 R.devices-2.16.0/R.devices/MD5 | 90 R.devices-2.16.0/R.devices/NAMESPACE | 19 R.devices-2.16.0/R.devices/NEWS | 1391 ++++--- R.devices-2.16.0/R.devices/R/999.NonDocumentedObjects.R | 6 R.devices-2.16.0/R.devices/R/DevEvalProduct.R | 945 ++-- R.devices-2.16.0/R.devices/R/capturePlot.R | 11 R.devices-2.16.0/R.devices/R/devEval.R | 1027 ++--- R.devices-2.16.0/R.devices/R/devNew.R | 679 +-- R.devices-2.16.0/R.devices/R/devOptions.R | 1191 ++---- R.devices-2.16.0/R.devices/R/deviceUtils.R | 1926 ++++------ R.devices-2.16.0/R.devices/R/eps.R | 20 R.devices-2.16.0/R.devices/R/favicon.R | 8 R.devices-2.16.0/R.devices/R/jpeg2.R | 12 R.devices-2.16.0/R.devices/R/nulldev.R |only R.devices-2.16.0/R.devices/R/png2.R | 13 R.devices-2.16.0/R.devices/R/recordedplot-methods.R | 38 R.devices-2.16.0/R.devices/R/suppressGraphics.R |only R.devices-2.16.0/R.devices/R/toNNN.R | 2 R.devices-2.16.0/R.devices/R/utils.R | 33 R.devices-2.16.0/R.devices/R/withPar.R | 142 R.devices-2.16.0/R.devices/R/zzz.R | 23 R.devices-2.16.0/R.devices/build/vignette.rds |binary R.devices-2.16.0/R.devices/inst/doc/R.devices-overview.R | 12 R.devices-2.16.0/R.devices/inst/doc/R.devices-overview.pdf |binary R.devices-2.16.0/R.devices/inst/exdata/capturePlot,engine=11,ostype=unix,arch=i686,ptrsize=4,endian=little.rds |only R.devices-2.16.0/R.devices/inst/exdata/capturePlot,engine=11,ostype=unix,arch=x86_64,ptrsize=8,endian=little.rds |only R.devices-2.16.0/R.devices/inst/exdata/capturePlot,engine=11,ostype=windows,arch=i386,ptrsize=4,endian=little.rds |only R.devices-2.16.0/R.devices/inst/exdata/capturePlot,engine=11,ostype=windows,arch=x86_64,ptrsize=8,endian=little.rds |only R.devices-2.16.0/R.devices/man/R.devices-package.Rd | 4 R.devices-2.16.0/R.devices/man/capturePlot.Rd | 5 R.devices-2.16.0/R.devices/man/devEval.Rd | 1 R.devices-2.16.0/R.devices/man/nulldev.Rd |only R.devices-2.16.0/R.devices/man/toNNN.Rd | 161 R.devices-2.16.0/R.devices/tests/DevEvalFileProduct.R | 108 R.devices-2.16.0/R.devices/tests/DevEvalProduct.R | 68 R.devices-2.16.0/R.devices/tests/dataURI.R | 36 R.devices-2.16.0/R.devices/tests/devDump.R | 124 R.devices-2.16.0/R.devices/tests/devEqualTypes.R | 4 R.devices-2.16.0/R.devices/tests/devEval.R | 417 +- R.devices-2.16.0/R.devices/tests/devIsInteractive.R | 32 R.devices-2.16.0/R.devices/tests/devIsOpen.R | 28 R.devices-2.16.0/R.devices/tests/devList.R | 104 R.devices-2.16.0/R.devices/tests/devListIndexOf.R | 30 R.devices-2.16.0/R.devices/tests/devSet.R | 128 R.devices-2.16.0/R.devices/tests/devTypeName.R | 84 R.devices-2.16.0/R.devices/tests/withPar.R | 100 52 files changed, 4540 insertions(+), 4496 deletions(-)
Title: Utility Functions for Parametric Multi-State Models
Description: Provides functions for working with multi-state modelling,
such as efficient simulation routines for estimating transition probabilities and length of stay.
It is designed as an extension to multi-state modelling capabilities provided with the 'flexsurv'
package (see Jackson (2016) <doi:10.18637/jss.v070.i08>).
Author: Stuart Lacy
Maintainer: Stuart Lacy <stuart.lacy@gmail.com>
Diff between multistateutils versions 1.1.0 dated 2018-06-17 and 1.2.0 dated 2018-07-21
multistateutils-1.1.0/multistateutils/R/individual.R |only multistateutils-1.2.0/multistateutils/DESCRIPTION | 11 multistateutils-1.2.0/multistateutils/MD5 | 53 multistateutils-1.2.0/multistateutils/NAMESPACE | 2 multistateutils-1.2.0/multistateutils/NEWS.md | 14 multistateutils-1.2.0/multistateutils/R/cohort.R | 105 + multistateutils-1.2.0/multistateutils/R/length_of_stay.R | 74 - multistateutils-1.2.0/multistateutils/R/msprep2.R |only multistateutils-1.2.0/multistateutils/R/run_simulation.R |only multistateutils-1.2.0/multistateutils/R/transition_probabilities.R | 82 - multistateutils-1.2.0/multistateutils/R/utils.R | 169 +- multistateutils-1.2.0/multistateutils/README.md | 326 +++- multistateutils-1.2.0/multistateutils/TODO | 1 multistateutils-1.2.0/multistateutils/build/vignette.rds |binary multistateutils-1.2.0/multistateutils/inst/doc/Examples.R | 103 + multistateutils-1.2.0/multistateutils/inst/doc/Examples.Rmd | 240 +++ multistateutils-1.2.0/multistateutils/inst/doc/Examples.html | 695 ++++++---- multistateutils-1.2.0/multistateutils/man/cohort_simulation.Rd |only multistateutils-1.2.0/multistateutils/man/length_of_stay.Rd | 19 multistateutils-1.2.0/multistateutils/man/msprep2.Rd |only multistateutils-1.2.0/multistateutils/man/predict_transitions.Rd | 15 multistateutils-1.2.0/multistateutils/src/des.cpp | 10 multistateutils-1.2.0/multistateutils/src/event.cpp | 2 multistateutils-1.2.0/multistateutils/src/simulation.cpp | 9 multistateutils-1.2.0/multistateutils/src/transitions.cpp | 19 multistateutils-1.2.0/multistateutils/src/transitions.h | 3 multistateutils-1.2.0/multistateutils/tests |only multistateutils-1.2.0/multistateutils/vignettes/Examples.Rmd | 240 +++ 28 files changed, 1706 insertions(+), 486 deletions(-)
More information about multistateutils at CRAN
Permanent link
Title: Artificial Spatial and Spatiotemporal Densities on Bounded
Windows
Description: A utility package containing some simple tools to design and generate density functions on bounded regions in space and space-time, and simulate iid data therefrom. See Davies & Hazelton (2010) <doi:10.1002/sim.3995> for example.
Author: Anna K. Redmond and Tilman M. Davies
Maintainer: Tilman M. Davies <tdavies@maths.otago.ac.nz>
Diff between spagmix versions 0.2-0 dated 2018-07-02 and 0.3-0 dated 2018-07-21
DESCRIPTION | 10 +++++----- MD5 | 12 ++++++++---- NAMESPACE | 5 +++-- NEWS | 21 +++++++++++++++++++++ R/lgcpmix.R |only R/rpoispoly.R |only man/lgcpmix.Rd |only man/rpoispoly.Rd |only man/spagmix-package.Rd | 15 ++++++++++----- 9 files changed, 47 insertions(+), 16 deletions(-)
Title: Compare Baseline Characteristics Between Groups
Description: Compare baseline characteristics between two or more groups. The variables being compared can be factor and numeric variables. The function will automatically judge the type and distribution of the variables, and make statistical description and bivariate analysis.
Author: Zhongheng Zhang,
Sir Run-Run Shaw hospital,
Zhejiang university school of medicine
Maintainer: Zhongheng Zhang <zh_zhang1984@zju.edu.cn>
Diff between CBCgrps versions 2.1 dated 2017-08-16 and 2.2 dated 2018-07-21
DESCRIPTION | 8 ++++---- MD5 | 10 +++++----- R/multigrps.R | 4 ++-- R/twogrps.R | 8 ++++---- man/multigrps.Rd | 2 +- man/twogrps.Rd | 2 +- 6 files changed, 17 insertions(+), 17 deletions(-)
Title: Tools for Data Diagnosis, Exploration, Transformation
Description: A collection of tools that support data diagnosis, exploration, and transformation.
Data diagnostics provides information and visualization of missing values and outliers and
unique and negative values to help you understand the distribution and quality of your data.
Data exploration provides information and visualization of the descriptive statistics of
univariate variables, normality tests and outliers, correlation of two variables, and
relationship between target variable and predictor. Data transformation supports binning
for categorizing continuous variables, imputates missing values and outliers, resolving skewness.
And it creates automated reports that support these three tasks.
Author: Choonghyun Ryu [aut, cre]
Maintainer: Choonghyun Ryu <choonghyun.ryu@gmail.com>
Diff between dlookr versions 0.3.0 dated 2018-04-27 and 0.3.2 dated 2018-07-21
dlookr-0.3.0/dlookr/inst/report/Binning_Report.Rmd |only dlookr-0.3.0/dlookr/man/correlate.Rd |only dlookr-0.3.0/dlookr/man/describe.Rd |only dlookr-0.3.0/dlookr/man/diagnose.Rd |only dlookr-0.3.0/dlookr/man/diagnose_category.Rd |only dlookr-0.3.0/dlookr/man/diagnose_numeric.Rd |only dlookr-0.3.0/dlookr/man/diagnose_outlier.Rd |only dlookr-0.3.0/dlookr/man/diagnose_report.Rd |only dlookr-0.3.0/dlookr/man/eda_report.Rd |only dlookr-0.3.0/dlookr/man/normality.Rd |only dlookr-0.3.0/dlookr/man/plot_correlate.Rd |only dlookr-0.3.0/dlookr/man/plot_normality.Rd |only dlookr-0.3.0/dlookr/man/plot_outlier.Rd |only dlookr-0.3.0/dlookr/man/target_by.Rd |only dlookr-0.3.2/dlookr/DESCRIPTION | 17 dlookr-0.3.2/dlookr/MD5 | 115 - dlookr-0.3.2/dlookr/NAMESPACE | 18 dlookr-0.3.2/dlookr/NEWS |only dlookr-0.3.2/dlookr/R/EDA.R | 16 dlookr-0.3.2/dlookr/R/correlate.R | 184 +- dlookr-0.3.2/dlookr/R/diagnose.R | 131 - dlookr-0.3.2/dlookr/R/discribe.R | 20 dlookr-0.3.2/dlookr/R/imputation.R | 2 dlookr-0.3.2/dlookr/R/normality.R | 209 +- dlookr-0.3.2/dlookr/R/target_by.R | 68 dlookr-0.3.2/dlookr/R/tbl_dbi.R |only dlookr-0.3.2/dlookr/R/utils.R | 6 dlookr-0.3.2/dlookr/inst/doc/EDA.R | 237 ++ dlookr-0.3.2/dlookr/inst/doc/EDA.Rmd | 301 +++ dlookr-0.3.2/dlookr/inst/doc/EDA.html | 446 +++++ dlookr-0.3.2/dlookr/inst/doc/diagonosis.R | 104 + dlookr-0.3.2/dlookr/inst/doc/diagonosis.Rmd | 151 + dlookr-0.3.2/dlookr/inst/doc/diagonosis.html | 203 ++ dlookr-0.3.2/dlookr/inst/doc/transformation.R | 12 dlookr-0.3.2/dlookr/inst/doc/transformation.Rmd | 12 dlookr-0.3.2/dlookr/inst/doc/transformation.html | 58 dlookr-0.3.2/dlookr/inst/report/02_RunEDA.Rnw | 13 dlookr-0.3.2/dlookr/inst/report/DataDiagnosis_Report.Rnw | 2 dlookr-0.3.2/dlookr/inst/report/EDA_Report.Rmd | 1174 +++++++------- dlookr-0.3.2/dlookr/inst/report/EDA_Report.Rnw | 2 dlookr-0.3.2/dlookr/inst/report/Transformation_Report.Rnw | 2 dlookr-0.3.2/dlookr/man/correlate.data.frame.Rd |only dlookr-0.3.2/dlookr/man/correlate.tbl_dbi.Rd |only dlookr-0.3.2/dlookr/man/describe.data.frame.Rd |only dlookr-0.3.2/dlookr/man/describe.tbl_dbi.Rd |only dlookr-0.3.2/dlookr/man/diagnose.data.frame.Rd |only dlookr-0.3.2/dlookr/man/diagnose.tbl_dbi.Rd |only dlookr-0.3.2/dlookr/man/diagnose_category.data.frame.Rd |only dlookr-0.3.2/dlookr/man/diagnose_category.tbl_dbi.Rd |only dlookr-0.3.2/dlookr/man/diagnose_numeric.data.frame.Rd |only dlookr-0.3.2/dlookr/man/diagnose_numeric.tbl_dbi.Rd |only dlookr-0.3.2/dlookr/man/diagnose_outlier.data.frame.Rd |only dlookr-0.3.2/dlookr/man/diagnose_outlier.tbl_dbi.Rd |only dlookr-0.3.2/dlookr/man/diagnose_report.data.frame.Rd |only dlookr-0.3.2/dlookr/man/diagnose_report.tbl_dbi.Rd |only dlookr-0.3.2/dlookr/man/eda_report.data.frame.Rd |only dlookr-0.3.2/dlookr/man/eda_report.tbl_dbi.Rd |only dlookr-0.3.2/dlookr/man/get_column_info.Rd |only dlookr-0.3.2/dlookr/man/normality.data.frame.Rd |only dlookr-0.3.2/dlookr/man/normality.tbl_dbi.Rd |only dlookr-0.3.2/dlookr/man/plot.relate.Rd | 12 dlookr-0.3.2/dlookr/man/plot_correlate.data.frame.Rd |only dlookr-0.3.2/dlookr/man/plot_correlate.tbl_dbi.Rd |only dlookr-0.3.2/dlookr/man/plot_normality.data.frame.Rd |only dlookr-0.3.2/dlookr/man/plot_normality.tbl_dbi.Rd |only dlookr-0.3.2/dlookr/man/plot_outlier.data.frame.Rd |only dlookr-0.3.2/dlookr/man/plot_outlier.tbl_dbi.Rd |only dlookr-0.3.2/dlookr/man/target_by.data.frame.Rd |only dlookr-0.3.2/dlookr/man/target_by.tbl_dbi.Rd |only dlookr-0.3.2/dlookr/vignettes/EDA.Rmd | 301 +++ dlookr-0.3.2/dlookr/vignettes/diagonosis.Rmd | 151 + dlookr-0.3.2/dlookr/vignettes/img/diag_agenda_html.png |binary dlookr-0.3.2/dlookr/vignettes/img/diag_table_html.png |binary dlookr-0.3.2/dlookr/vignettes/img/eda_agenda_html.png |binary dlookr-0.3.2/dlookr/vignettes/img/eda_agenda_pdf.png |binary dlookr-0.3.2/dlookr/vignettes/img/eda_anova_pdf.png |binary dlookr-0.3.2/dlookr/vignettes/img/eda_lm_pdf.png |binary dlookr-0.3.2/dlookr/vignettes/img/trans_agenda_html.png |binary dlookr-0.3.2/dlookr/vignettes/img/trans_agenda_pdf.png |binary dlookr-0.3.2/dlookr/vignettes/transformation.Rmd | 12 80 files changed, 2953 insertions(+), 1026 deletions(-)