Title: Geographically Optimal Similarity
Description: Understanding spatial association is essential for spatial
statistical inference, including factor exploration and spatial prediction.
Geographically optimal similarity (GOS) model is an effective method
for spatial prediction, as described in Yongze Song (2022)
<doi:10.1007/s11004-022-10036-8>. GOS was developed based on
the geographical similarity principle, as described in Axing Zhu (2018)
<doi:10.1080/19475683.2018.1534890>. GOS has advantages in
more accurate spatial prediction using fewer samples and
critically reduced prediction uncertainty.
Author: Yongze Song [aut, cph] ,
Wenbo Lv [aut, cre]
Maintainer: Wenbo Lv <lyu.geosocial@gmail.com>
Diff between geosimilarity versions 3.2 dated 2024-09-08 and 3.3 dated 2024-09-14
geosimilarity-3.2/geosimilarity/inst/doc/GOS.Rmd |only geosimilarity-3.2/geosimilarity/inst/doc/GOS.html |only geosimilarity-3.2/geosimilarity/vignettes/GOS.Rmd |only geosimilarity-3.2/geosimilarity/vignettes/GOS.Rmd.orig |only geosimilarity-3.3/geosimilarity/DESCRIPTION | 10 +-- geosimilarity-3.3/geosimilarity/MD5 | 26 +++++----- geosimilarity-3.3/geosimilarity/NEWS.md | 7 ++ geosimilarity-3.3/geosimilarity/R/gos.R | 8 +-- geosimilarity-3.3/geosimilarity/R/gos_bestkappa.R | 2 geosimilarity-3.3/geosimilarity/R/utils.R | 7 +- geosimilarity-3.3/geosimilarity/R/zzz.R | 2 geosimilarity-3.3/geosimilarity/build/vignette.rds |binary geosimilarity-3.3/geosimilarity/inst/doc/geosimilarity.Rmd |only geosimilarity-3.3/geosimilarity/inst/doc/geosimilarity.html |only geosimilarity-3.3/geosimilarity/man/pipe.Rd | 3 + geosimilarity-3.3/geosimilarity/vignettes/geosimilarity.Rmd |only geosimilarity-3.3/geosimilarity/vignettes/geosimilarity.Rmd.orig |only geosimilarity-3.3/geosimilarity/vignettes/precompile.R | 4 - 18 files changed, 40 insertions(+), 29 deletions(-)
Title: Spacekime Analytics, Time Complexity and Inferential Uncertainty
Description: Provide the core functionality to transform longitudinal data to
complex-time (kime) data using analytic and numerical techniques, visualize the original
time-series and reconstructed kime-surfaces, perform model based (e.g., tensor-linear regression)
and model-free classification and clustering methods in the book Dinov, ID and Velev, MV. (2021)
"Data Science: Time Complexity, Inferential Uncertainty, and Spacekime Analytics", De Gruyter STEM Series,
ISBN 978-3-11-069780-3. <https://www.degruyter.com/view/title/576646>.
The package includes 18 core functions which can be separated into three groups.
1) draw longitudinal data, such as Functional magnetic resonance imaging(fMRI) time-series, and forecast or transform the time-series data.
2) simulate real-valued time-series data, e.g., fMRI time-courses, detect the activated areas,
report the corresponding p-values, and visualize the p-values in the 3D brain space.
3) Laplace transform and kimesurface reconstructions of the fMRI d [...truncated...]
Author: Yongkai Qiu [aut],
Zhe Yin [aut],
Jinwen Cao [aut],
Yupeng Zhang [aut],
Yuyao Liu [aut],
Rongqian Zhang [aut],
Yueyang Shen [aut, cre],
Rouben Rostamian [ctb],
Ranjan Maitra [ctb],
Daniel Rowe [ctb],
Daniel Adrian [ctb] ,
Yunjie Guo [aut],
Ivo Dinov [...truncated...]
Maintainer: Yueyang Shen <petersyy@umich.edu>
Diff between TCIU versions 1.2.6 dated 2024-05-17 and 1.2.7 dated 2024-09-14
DESCRIPTION | 6 +++--- MD5 | 10 +++++----- inst/doc/tciu-LT-kimesurface.html | 16 ++++++++-------- inst/doc/tciu-fMRI-analytics.html | 32 ++++++++++++++++---------------- src/array.h | 5 +++-- src/spatial.c | 22 +++++++++++----------- 6 files changed, 46 insertions(+), 45 deletions(-)
Title: Probabilistic Regression Trees
Description: Probabilistic Regression Trees (PRTree). Functions for fitting and predicting PRTree models with some adaptations to handle missing values. The main calculations are performed in 'FORTRAN', resulting in highly efficient algorithms.
This package's implementation is based on the PRTree methodology described in Alkhoury, S.; Devijver, E.; Clausel, M.; Tami, M.; Gaussier, E.; Oppenheim, G. (2020) - "Smooth And Consistent Probabilistic Regression Trees" <https://proceedings.neurips.cc/paper_files/paper/2020/file/8289889263db4a40463e3f358bb7c7a1-Paper.pdf>.
Author: Alisson Silva Neimaier [aut, cre]
,
Taiane Schaedler Prass [aut, ths]
Maintainer: Alisson Silva Neimaier <alissonneimaier@hotmail.com>
Diff between PRTree versions 0.1.0 dated 2024-01-16 and 0.1.1 dated 2024-09-14
DESCRIPTION | 10 +++++----- MD5 | 5 +++-- inst |only src/base.f90 | 20 +++++++++++++++----- 4 files changed, 23 insertions(+), 12 deletions(-)
Title: Estimation of Entropy and Related Quantities
Description: Contains methods for the estimation of Shannon's entropy, variants of Renyi's entropy, mutual information, Kullback-Leibler divergence, and generalized Simpson's indices. The estimators used have a bias that decays exponentially fast.
Author: Lijuan Cao [aut],
Michael Grabchak [aut, cre]
Maintainer: Michael Grabchak <mgrabcha@charlotte.edu>
Diff between EntropyEstimation versions 1.2 dated 2015-01-04 and 1.2.1 dated 2024-09-14
DESCRIPTION | 21 +++++++++--- MD5 | 9 +++-- NAMESPACE | 7 +++- man/EntropyEstimation-package.Rd | 6 +-- src/EntropEst.c | 65 +++++++++++++++++++-------------------- src/init.c |only 6 files changed, 61 insertions(+), 47 deletions(-)
More information about EntropyEstimation at CRAN
Permanent link
Title: A Collection of Useful Functions by John
Description: A set of general functions that I have used in various
projects and other R packages. Miscellaneous operations on data
frames, matrices and vectors, ROC and PR statistics.
Author: John Zobolas [aut, cph, cre]
Maintainer: John Zobolas <bblodfon@gmail.com>
Diff between usefun versions 0.5.0 dated 2023-09-17 and 0.5.2 dated 2024-09-14
DESCRIPTION | 26 ++-- MD5 | 33 +++-- NAMESPACE | 7 + NEWS.md | 8 + R/bibentries.R | 28 +++- R/intersection_powerset.R |only R/operations.R | 8 - R/pr.R | 164 +++++++++++++++++++++++++--- R/roc.R | 11 - R/usefun.R | 2 README.md | 2 man/get_roc_stats.Rd | 7 - man/get_ternary_class_id.Rd | 6 - man/powerset_icounts.Rd |only man/pr.boot.Rd |only man/pr.test.Rd | 16 +- man/usefun.Rd | 3 tests/testthat/helper.R |only tests/testthat/test-intersection_powerset.R |only tests/testthat/test-pr.R | 11 + 20 files changed, 249 insertions(+), 83 deletions(-)
Title: Forest Mensuration and Management
Description: Processing forest inventory data with methods such as simple random sampling, stratified random sampling and systematic sampling. There are also functions for yield and growth predictions and model fitting, linear and nonlinear grouped data fitting, and statistical tests. References: Kershaw Jr., Ducey, Beers and Husch (2016). <doi:10.1002/9781118902028>.
Author: Sollano Rabelo Braga [aut, cre, cph],
Marcio Leles Romarco de Oliveira [aut],
Eric Bastos Gorgens [aut]
Maintainer: Sollano Rabelo Braga <sollanorb@gmail.com>
Diff between forestmangr versions 0.9.6 dated 2023-11-23 and 0.9.7 dated 2024-09-14
forestmangr-0.9.6/forestmangr/R/graybill_f.R |only forestmangr-0.9.6/forestmangr/man/graybill_f.Rd |only forestmangr-0.9.7/forestmangr/DESCRIPTION | 10 forestmangr-0.9.7/forestmangr/MD5 | 112 - forestmangr-0.9.7/forestmangr/NEWS.md | 3 forestmangr-0.9.7/forestmangr/R/Graybill_F.R |only forestmangr-0.9.7/forestmangr/R/exfm10.R | 2 forestmangr-0.9.7/forestmangr/R/exfm13.R | 2 forestmangr-0.9.7/forestmangr/R/exfm15.R | 2 forestmangr-0.9.7/forestmangr/R/exfm18.R | 4 forestmangr-0.9.7/forestmangr/R/exfm19.R | 2 forestmangr-0.9.7/forestmangr/R/exfm20.R | 2 forestmangr-0.9.7/forestmangr/R/exfm21.R | 2 forestmangr-0.9.7/forestmangr/R/exfm6.R | 4 forestmangr-0.9.7/forestmangr/R/exfm7.R | 2 forestmangr-0.9.7/forestmangr/R/exfm8.R | 2 forestmangr-0.9.7/forestmangr/R/exfm9.R | 2 forestmangr-0.9.7/forestmangr/build/vignette.rds |binary forestmangr-0.9.7/forestmangr/inst/doc/eq_group_fit_en.html | 258 +-- forestmangr-0.9.7/forestmangr/inst/doc/eq_group_fit_ptbr.html | 258 +-- forestmangr-0.9.7/forestmangr/inst/doc/invent_vol_plot_en.html | 264 +-- forestmangr-0.9.7/forestmangr/inst/doc/invent_vol_plot_ptbr.html | 264 +-- forestmangr-0.9.7/forestmangr/inst/doc/phyto_ana_en.html | 336 ++-- forestmangr-0.9.7/forestmangr/inst/doc/phyto_ana_ptbr.html | 336 ++-- forestmangr-0.9.7/forestmangr/inst/doc/sampling_en.html | 826 +++++----- forestmangr-0.9.7/forestmangr/inst/doc/sampling_ptbr.html | 652 +++---- forestmangr-0.9.7/forestmangr/inst/doc/volume_est_en.html | 184 +- forestmangr-0.9.7/forestmangr/inst/doc/volume_est_ptbr.html | 184 +- forestmangr-0.9.7/forestmangr/inst/doc/yield_growth_en.html | 134 - forestmangr-0.9.7/forestmangr/inst/doc/yield_growth_ptbr.html | 134 - forestmangr-0.9.7/forestmangr/man/Graybill_F.Rd |only forestmangr-0.9.7/forestmangr/man/avg_tree_curve.Rd | 126 - forestmangr-0.9.7/forestmangr/man/check_names.Rd | 70 forestmangr-0.9.7/forestmangr/man/exfm10.Rd | 2 forestmangr-0.9.7/forestmangr/man/exfm11.Rd | 54 forestmangr-0.9.7/forestmangr/man/exfm12.Rd | 58 forestmangr-0.9.7/forestmangr/man/exfm13.Rd | 2 forestmangr-0.9.7/forestmangr/man/exfm14.Rd | 50 forestmangr-0.9.7/forestmangr/man/exfm15.Rd | 2 forestmangr-0.9.7/forestmangr/man/exfm16.Rd | 56 forestmangr-0.9.7/forestmangr/man/exfm17.Rd | 58 forestmangr-0.9.7/forestmangr/man/exfm18.Rd | 4 forestmangr-0.9.7/forestmangr/man/exfm19.Rd | 2 forestmangr-0.9.7/forestmangr/man/exfm20.Rd | 2 forestmangr-0.9.7/forestmangr/man/exfm21.Rd | 2 forestmangr-0.9.7/forestmangr/man/exfm22.Rd | 48 forestmangr-0.9.7/forestmangr/man/exfm4.Rd | 54 forestmangr-0.9.7/forestmangr/man/exfm6.Rd | 4 forestmangr-0.9.7/forestmangr/man/exfm7.Rd | 2 forestmangr-0.9.7/forestmangr/man/exfm8.Rd | 2 forestmangr-0.9.7/forestmangr/man/exfm9.Rd | 2 forestmangr-0.9.7/forestmangr/man/lm_resid_group.Rd | 150 - forestmangr-0.9.7/forestmangr/man/na_to_0.Rd | 66 forestmangr-0.9.7/forestmangr/man/npv_irr.Rd | 124 - forestmangr-0.9.7/forestmangr/man/outliersiqr.Rd | 46 forestmangr-0.9.7/forestmangr/man/pipe.Rd | 22 forestmangr-0.9.7/forestmangr/man/pow.Rd | 86 - forestmangr-0.9.7/forestmangr/man/rm_empty_col.Rd | 72 forestmangr-0.9.7/forestmangr/man/round_df.Rd | 82 59 files changed, 2616 insertions(+), 2613 deletions(-)
Title: Robust Bayesian Variable Selection via Expectation-Maximization
Description: Variable selection methods have been extensively developed for analyzing highdimensional omics data within both the frequentist and Bayesian frameworks. This package provides implementations of the spike-and-slab quantile (group) LASSO which have been developed along the line of Bayesian hierarchical models but deeply rooted in frequentist regularization methods by utilizing Expectation–Maximization (EM) algorithm. The spike-and-slab quantile LASSO can handle data irregularity in terms of skewness and outliers in response variables, compared to its non-robust alternative, the spike-and-slab LASSO, which has also been implemented in the package. In addition, procedures for fitting the spike-and-slab quantile group LASSO and its non-robust counterpart have been implemented in the form of quantile/least-square varying coefficient mixed effect models for high-dimensional longitudinal data. The core module of this package is developed in 'C++'.
Author: Yuwen Liu [aut, cre],
Cen Wu [aut]
Maintainer: Yuwen Liu <yuwenliu9@gmail.com>
Diff between emBayes versions 0.1.5 dated 2024-03-29 and 0.1.6 dated 2024-09-14
DESCRIPTION | 14 ++-- MD5 | 26 ++++---- R/RcppExports.R | 16 +++++ R/cv.emBayes.R | 52 +++++++++++++++-- R/emBayes-package.R | 7 +- R/emBayes.R | 137 +++++++++++++++++++++++++++++++++++++++++++--- man/cv.emBayes.Rd | 11 +++ man/emBayes-package.Rd | 7 +- man/emBayes.Rd | 38 ++++++++++--- src/EM.cpp | 143 +++++++++++++++++++++++++++++++++++++++++++++++++ src/EM.h | 2 src/RcppExports.cpp | 129 ++++++++++++++++++++++++++++++++++++++++++++ src/Utilities.cpp | 92 +++++++++++++++++++++++++++++++ src/Utilities.h | 2 14 files changed, 625 insertions(+), 51 deletions(-)
Title: Wrapper Functions Around 'Charles Schwab Individual Trader API'
Description: For those wishing to interact with the 'Charles Schwab Individual Trader API' (<https://developer.schwab.com/products/trader-api--individual>) with R in a simplified manner, this package offers wrapper functions around authentication and the available API calls to streamline the process.
Author: Nick Bultman [aut, cre, cph]
Maintainer: Nick Bultman <njbultman74@gmail.com>
Diff between charlesschwabapi versions 1.0.2 dated 2024-07-17 and 1.0.3 dated 2024-09-14
DESCRIPTION | 6 +++--- MD5 | 6 +++--- R/get_authentication_tokens.R | 2 +- README.md | 11 ++++++++++- 4 files changed, 17 insertions(+), 8 deletions(-)
More information about charlesschwabapi at CRAN
Permanent link
Title: Accesses Brazilian Public Security Data from SINESP Since 2015
Description: Allows access to data from the Brazilian Public Security Information System (SINESP) by state and municipality. <https://www.gov.br/mj/pt-br/assuntos/sua-seguranca/seguranca-publica/sinesp-1>.
Author: Giovanni Vargette [aut, cre] ,
Igor Laltuf [aut] ,
Marcelo Justus [aut]
Maintainer: Giovanni Vargette <g216978@dac.unicamp.br>
Diff between BrazilCrime versions 0.2 dated 2024-06-21 and 0.2.1 dated 2024-09-14
DESCRIPTION | 20 +++--- MD5 | 11 ++- R/get_sinesp_data.R | 11 ++- README.md | 110 ++++++++++++++++++++++++++++++++-- man/figures/grafico.png |only man/figures/mapa.png |only tests/testthat/test-get_sinesp_data.R | 61 +++++++++--------- tests/testthat/testthat-problems.rds |only 8 files changed, 161 insertions(+), 52 deletions(-)
Title: Create and Evaluate Stopping Rules for Safety Monitoring
Description: Provides functions for creating, displaying, and evaluating stopping rules for safety monitoring in clinical studies. Implements stopping rule methods described in Goldman (1987) <doi:10.1016/0197-2456(87)90153-X>; Geller et al. (2003, ISBN:9781135524388); Ivanova, Qaqish, and Schell (2005) <doi:10.1111/j.1541-0420.2005.00311.x>; Chen and Chaloner (2006) <doi:10.1002/sim.2429>; and Kulldorff et al. (2011) <doi:10.1080/07474946.2011.539924>.
Author: Michael J. Martens [aut, cre],
Qinghua Lian [aut],
Brent R. Logan [ctb]
Maintainer: Michael J. Martens <mmartens@mcw.edu>
Diff between stoppingrule versions 0.4.0 dated 2024-03-17 and 0.5.0 dated 2024-09-14
DESCRIPTION | 14 ++++++++++---- MD5 | 22 +++++++++++----------- R/calc.bnd.surv.R | 23 ++++++++++++++--------- R/calc.rule.bin.R | 2 +- R/calc.rule.surv.R | 17 +++++++++++------ R/findconst.surv.R | 15 ++++++++++++--- R/table.rule.bin.R | 11 ++++++----- R/table.rule.surv.R | 2 +- man/calc.bnd.surv.Rd | 8 ++++++-- man/calc.rule.bin.Rd | 2 +- man/calc.rule.surv.Rd | 6 +++++- man/findconst.surv.Rd | 6 +++++- 12 files changed, 83 insertions(+), 45 deletions(-)
Title: Create, and Refine Data Nuggets
Description: Creating, and refining data nuggets.
Data nuggets reduce a large dataset into a small collection of nuggets of
data, each containing a center (location), weight (importance), and scale
(variability) parameter. Data nugget centers are created by choosing
observations in the dataset which are as equally spaced apart as possible.
Data nugget weights are created by counting the number observations
closest to a given data nugget center. We then say the data nugget
'contains' these observations and the data nugget center is recalculated
as the mean of these observations. Data nugget scales are created by
calculating the trace of the covariance matrix of the observations
contained within a data nugget divided by the dimension of the dataset.
Data nuggets are refined by 'splitting' data nuggets which have scales or
shapes (defined as the ratio of the two largest eigenvalues of the
covariance matrix of the observations contained within the data nugget)
Reference paper: [1] Beavers, T. E., Cheng [...truncated...]
Author: Yajie Duan [cre, ctb],
Traymon Beavers [aut],
Javier Cabrera [aut],
Ge Cheng [aut],
Kunting Qi [aut],
Mariusz Lubomirski [aut]
Maintainer: Yajie Duan <yajieritaduan@gmail.com>
Diff between datanugget versions 1.3.0 dated 2024-07-29 and 1.3.1 dated 2024-09-14
DESCRIPTION | 8 MD5 | 4 R/refineDN.R | 4809 +++++++++++++++++++++++++++++------------------------------ 3 files changed, 2412 insertions(+), 2409 deletions(-)
Title: Read Spectral and Logged Data from Foreign Files
Description: Functions for reading, and in some cases writing, foreign files
containing spectral data from spectrometers and their associated software,
output from daylight simulation models in common use, and some spectral
data repositories. As well as functions for exchange of spectral data with
other R packages. Part of the 'r4photobiology' suite,
Aphalo P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>.
Author: Pedro J. Aphalo [aut, cre] ,
Titta K. Kotilainen [ctb] ,
Glenn Davis [ctb]
Maintainer: Pedro J. Aphalo <pedro.aphalo@helsinki.fi>
Diff between photobiologyInOut versions 0.4.27 dated 2023-07-20 and 0.4.28-1 dated 2024-09-14
DESCRIPTION | 15 MD5 | 129 NAMESPACE | 4 NEWS.md | 93 R/color-wrappers.r | 12 R/on-load.r | 3 R/read-cid-spectravue-csv.r | 4 R/read-cie-csv.r |only R/read-fmi-cum.R | 16 R/read-licor-prn.r | 4 R/read-oojaz-file.r | 2 R/read-oopi-file.r | 2 R/read-ooss-file.r | 2 R/read-tuv-file.r | 696 README.md | 49 build/partial.rdb |binary build/vignette.rds |binary inst/doc/user-guide.R | 54 inst/doc/user-guide.Rmd | 50 inst/doc/user-guide.html | 840 - inst/extdata/2013-05-01.hel |16890 ++++++++++++------------ inst/extdata/2014-08-21_cum.hel | 1028 - inst/extdata/2014-08-22_cum.hel | 1028 - inst/extdata/CIE_illum_C.csv |only inst/extdata/CIE_illum_C.csv_metadata.json |only inst/extdata/CIE_sle_photopic.csv |only inst/extdata/CIE_sle_photopic.csv_metadata.json |only inst/extdata/FReDflowerID_157.csv | 802 - inst/extdata/qtuv-00.htm |only inst/extdata/reflectance.jaz | 4134 ++--- inst/extdata/spectrum-seq0.pi | 4108 ++--- inst/extdata/spectrum.JazIrrad | 8240 +++++------ inst/extdata/spectrum.jaz | 4134 ++--- inst/extdata/spectrum.pi | 4108 ++--- inst/extdata/uvspec-multi.dat | 6110 ++++---- inst/extdata/yoctopuce-data.csv | 1412 +- man/as.colorSpec.Rd | 164 man/colorSpec2mspct.Rd | 218 man/hyperSpec2mspct.Rd | 160 man/photobiologyInOut-package.Rd | 118 man/qtuv_clouds.Rd |only man/qtuv_s.e.irrad.Rd |only man/read_ASTER_txt.Rd | 146 man/read_CIE_csv.Rd |only man/read_FReD_csv.Rd | 128 man/read_avaspec_csv.Rd | 148 man/read_cid_spectravue_csv.Rd | 4 man/read_csi_dat.Rd | 116 man/read_fmi2mspct.Rd | 166 man/read_fmi_cum.Rd | 180 man/read_foreign2mspct.Rd | 88 man/read_li180_txt.Rd | 204 man/read_licor_prn.Rd | 204 man/read_macam_dta.Rd | 124 man/read_oo_jazirrad.Rd | 212 man/read_oo_pidata.Rd | 164 man/read_oo_ssirrad.Rd | 150 man/read_qtuv_txt.Rd | 111 man/read_tuv_usrout.Rd | 130 man/read_uvspec_disort.Rd | 126 man/read_uvspec_disort_vesa.Rd | 114 man/read_wasatch_csv.Rd | 266 man/read_yoctopuce_csv.Rd | 152 man/rspec2mspct.Rd | 158 man/spct_CCT.Rd | 108 man/spct_CRI.Rd | 92 man/spct_SSI.Rd | 100 tests/testthat/test-licor.R | 74 tests/testthat/test-tuv.R | 124 vignettes/user-guide.Rmd | 50 70 files changed, 29607 insertions(+), 28661 deletions(-)
More information about photobiologyInOut at CRAN
Permanent link
Title: SHAP Visualizations
Description: Visualizations for SHAP (SHapley Additive exPlanations), such
as waterfall plots, force plots, various types of importance plots,
dependence plots, and interaction plots. These plots act on a
'shapviz' object created from a matrix of SHAP values and a
corresponding feature dataset. Wrappers for the R packages 'xgboost',
'lightgbm', 'fastshap', 'shapr', 'h2o', 'treeshap', 'DALEX', and
'kernelshap' are added for convenience. By separating visualization
and computation, it is possible to display factor variables in graphs,
even if the SHAP values are calculated by a model that requires
numerical features. The plots are inspired by those provided by the
'shap' package in Python, but there is no dependency on it.
Author: Michael Mayer [aut, cre],
Adrian Stando [ctb]
Maintainer: Michael Mayer <mayermichael79@gmail.com>
Diff between shapviz versions 0.9.4 dated 2024-08-20 and 0.9.5 dated 2024-09-14
shapviz-0.9.4/shapviz/man/figures/README-dep.png |only shapviz-0.9.4/shapviz/man/figures/VIGNETTE-dep.png |only shapviz-0.9.5/shapviz/DESCRIPTION | 6 shapviz-0.9.5/shapviz/MD5 | 59 - shapviz-0.9.5/shapviz/NEWS.md | 12 shapviz-0.9.5/shapviz/R/sv_force.R | 2 shapviz-0.9.5/shapviz/R/sv_waterfall.R | 2 shapviz-0.9.5/shapviz/README.md | 56 - shapviz-0.9.5/shapviz/build/vignette.rds |binary shapviz-0.9.5/shapviz/inst/doc/basic_use.R | 29 shapviz-0.9.5/shapviz/inst/doc/basic_use.Rmd | 48 - shapviz-0.9.5/shapviz/inst/doc/basic_use.html | 98 +- shapviz-0.9.5/shapviz/inst/doc/geographic.R | 68 - shapviz-0.9.5/shapviz/inst/doc/geographic.Rmd | 70 - shapviz-0.9.5/shapviz/inst/doc/geographic.html | 138 +-- shapviz-0.9.5/shapviz/inst/doc/multiple_output.html | 8 shapviz-0.9.5/shapviz/inst/doc/tidymodels.Rmd |only shapviz-0.9.5/shapviz/inst/doc/tidymodels.html |only shapviz-0.9.5/shapviz/man/figures/README-bee.svg |only shapviz-0.9.5/shapviz/man/figures/README-dep.svg |only shapviz-0.9.5/shapviz/man/figures/README-force.svg | 381 +--------- shapviz-0.9.5/shapviz/man/figures/README-imp.svg | 360 +-------- shapviz-0.9.5/shapviz/man/figures/README-waterfall.svg | 373 +-------- shapviz-0.9.5/shapviz/man/figures/VIGNETTE-dep-ranger.png |binary shapviz-0.9.5/shapviz/man/figures/VIGNETTE-tidy-class-lgb-dep.png |only shapviz-0.9.5/shapviz/man/figures/VIGNETTE-tidy-class-lgb-imp.png |only shapviz-0.9.5/shapviz/man/figures/VIGNETTE-tidy-class-normal-dep1.png |only shapviz-0.9.5/shapviz/man/figures/VIGNETTE-tidy-class-normal-dep2.png |only shapviz-0.9.5/shapviz/man/figures/VIGNETTE-tidy-class-normal-imp.png |only shapviz-0.9.5/shapviz/man/figures/VIGNETTE-tidy-class-xgb-dep.png |only shapviz-0.9.5/shapviz/man/figures/VIGNETTE-tidy-class-xgb-imp.png |only shapviz-0.9.5/shapviz/man/figures/VIGNETTE-tidy-lgb-dep.png |only shapviz-0.9.5/shapviz/man/figures/VIGNETTE-tidy-lgb-imp.png |only shapviz-0.9.5/shapviz/man/figures/VIGNETTE-tidy-rf-dep.png |only shapviz-0.9.5/shapviz/man/figures/VIGNETTE-tidy-rf-imp.png |only shapviz-0.9.5/shapviz/man/figures/VIGNETTE-tidy-xgb-dep.png |only shapviz-0.9.5/shapviz/man/figures/VIGNETTE-tidy-xgb-imp.png |only shapviz-0.9.5/shapviz/man/figures/VIGNETTE-tidy-xgb-inter.png |only shapviz-0.9.5/shapviz/vignettes/basic_use.Rmd | 48 - shapviz-0.9.5/shapviz/vignettes/geographic.Rmd | 70 - shapviz-0.9.5/shapviz/vignettes/tidymodels.Rmd |only 41 files changed, 571 insertions(+), 1257 deletions(-)
Title: Genotypic Variance Components
Description: Functionalities to compute model based genetic components i.e. genotypic variance, phenotypic variance and heritability for given traits of different genotypes from replicated data using methodology explained by Burton, G. W. & Devane, E. H. (1953) (<doi:10.2134/agronj1953.00021962004500100005x>) and Allard, R.W. (2010, ISBN:8126524154).
Author: Muhammad Yaseen [aut, cre],
Sami Ullah [aut, ctb]
Maintainer: Muhammad Yaseen <myaseen208@gmail.com>
Diff between gvcR versions 0.1.0 dated 2018-02-20 and 0.3.0 dated 2024-09-14
gvcR-0.1.0/gvcR/R/gvc_gvar.R |only gvcR-0.1.0/gvcR/R/gvc_herit.R |only gvcR-0.1.0/gvcR/R/gvc_pvar.R |only gvcR-0.1.0/gvcR/man/gvc_gvar.Rd |only gvcR-0.1.0/gvcR/man/gvc_herit.Rd |only gvcR-0.1.0/gvcR/man/gvc_pvar.Rd |only gvcR-0.3.0/gvcR/DESCRIPTION | 20 ++++--- gvcR-0.3.0/gvcR/MD5 | 17 ++---- gvcR-0.3.0/gvcR/NAMESPACE | 8 +- gvcR-0.3.0/gvcR/NEWS.md | 6 ++ gvcR-0.3.0/gvcR/R/gvc.R |only gvcR-0.3.0/gvcR/README.md | 107 +++++++++++++++++++++++++++++++++++---- gvcR-0.3.0/gvcR/inst |only gvcR-0.3.0/gvcR/man/gvc.Rd |only 14 files changed, 127 insertions(+), 31 deletions(-)
Title: Searching for Optimal Clustering Procedure for a Data Set
Description: Distance measures (GDM1, GDM2, Sokal-Michener, Bray-Curtis, for symbolic interval-valued data), cluster quality indices (Calinski-Harabasz, Baker-Hubert, Hubert-Levine, Silhouette, Krzanowski-Lai, Hartigan, Gap, Davies-Bouldin), data normalization formulas (metric data, interval-valued symbolic data), data generation (typical and non-typical data), HINoV method, replication analysis, linear ordering methods, spectral clustering, agreement indices between two partitions, plot functions (for categorical and symbolic interval-valued data).
(MILLIGAN, G.W., COOPER, M.C. (1985) <doi:10.1007/BF02294245>,
HUBERT, L., ARABIE, P. (1985) <doi:10.1007%2FBF01908075>,
RAND, W.M. (1971) <doi:10.1080/01621459.1971.10482356>,
JAJUGA, K., WALESIAK, M. (2000) <doi:10.1007/978-3-642-57280-7_11>,
MILLIGAN, G.W., COOPER, M.C. (1988) <doi:10.1007/BF01897163>,
JAJUGA, K., WALESIAK, M., BAK, A. (2003) <doi:10.1007/978-3-642-55721-7_12>,
DAVIES, D.L., BOULDIN, D.W. (1979) &l [...truncated...]
Author: Marek Walesiak [aut] ,
Andrzej Dudek [aut, cre]
Maintainer: Andrzej Dudek <andrzej.dudek@ue.wroc.pl>
Diff between clusterSim versions 0.51-4 dated 2024-06-26 and 0.51-5 dated 2024-09-14
clusterSim-0.51-4/clusterSim/INDEX |only clusterSim-0.51-5/clusterSim/DESCRIPTION | 8 +-- clusterSim-0.51-5/clusterSim/MD5 | 27 ++++++------- clusterSim-0.51-5/clusterSim/build/partial.rdb |binary clusterSim-0.51-5/clusterSim/data/data_binary.rda |binary clusterSim-0.51-5/clusterSim/data/data_interval.rda |binary clusterSim-0.51-5/clusterSim/data/data_mixed.rda |binary clusterSim-0.51-5/clusterSim/data/data_nominal.rda |binary clusterSim-0.51-5/clusterSim/data/data_ordinal.rda |binary clusterSim-0.51-5/clusterSim/data/data_ratio.rda |binary clusterSim-0.51-5/clusterSim/man/HINoV.Symbolic.rd | 2 clusterSim-0.51-5/clusterSim/man/cluster.Gen.rd | 4 - clusterSim-0.51-5/clusterSim/man/data.Normalization.rd | 2 clusterSim-0.51-5/clusterSim/man/interval_normalization.rd | 4 - clusterSim-0.51-5/clusterSim/man/speccl.rd | 3 - 15 files changed, 25 insertions(+), 25 deletions(-)
Title: Mappable Vector Library for Handling Large Datasets
Description: Mappable vector library provides convenient way to access large datasets. Use all of your data at once, with few limits. Memory mapped data can be shared between multiple R processes. Access speed depends on storage medium, so solid state drive is recommended, preferably with PCI Express (or M.2 nvme) interface or a fast network file system. The data is memory mapped into R and then accessed using usual R list and array subscription operators. Convenience functions are provided for merging, grouping and indexing large vectors and data.frames. The layout of underlying MVL files is optimized for large datasets. The vectors are stored to guarantee alignment for vector intrinsics after memory map. The package is built on top of libMVL, which can be used as a standalone C library. libMVL has simple C API making it easy to interchange datasets with outside programs. Large MVL datasets are distributed via Academic Torrents <https://academictorrents.com/collection/mvl-datasets>.
Author: Vladimir Dergachev [aut, cre]
Maintainer: Vladimir Dergachev <support@altumrete.com>
Diff between RMVL versions 1.1.0.0 dated 2024-05-08 and 1.1.0.1 dated 2024-09-14
DESCRIPTION | 6 +++--- MD5 | 6 +++--- src/RlibMVL.c | 20 ++++++++++---------- src/libMVL.c | 2 ++ 4 files changed, 18 insertions(+), 16 deletions(-)
Title: React Helpers
Description: Make it easy to use 'React' in R with 'htmlwidget' scaffolds,
helper dependency functions, an embedded 'Babel' 'transpiler',
and examples.
Author: Facebook Inc [aut, cph] ,
Michel Weststrate [aut, cph] ,
Kent Russell [aut, cre] ,
Alan Dipert [aut] ,
Greg Lin [aut]
Maintainer: Kent Russell <kent.russell@timelyportfolio.com>
Diff between reactR versions 0.6.0 dated 2024-06-26 and 0.6.1 dated 2024-09-14
reactR-0.6.0/reactR/inst/www/react-tools/react-tools.umd.cjs |only reactR-0.6.1/reactR/DESCRIPTION | 19 +++++++---- reactR-0.6.1/reactR/MD5 | 14 ++++---- reactR-0.6.1/reactR/NEWS.md | 4 ++ reactR-0.6.1/reactR/R/dependencies.R | 2 - reactR-0.6.1/reactR/inst/doc/intro_htmlwidgets.html | 4 +- reactR-0.6.1/reactR/inst/doc/intro_inputs.html | 4 +- reactR-0.6.1/reactR/inst/doc/intro_reactR.html | 6 +-- reactR-0.6.1/reactR/inst/www/react-tools/react-tools.js |only 9 files changed, 32 insertions(+), 21 deletions(-)
Title: Inference for Phase-Type Distributions
Description: Functions to perform Bayesian inference on absorption time data for
Phase-type distributions. The methods of Bladt et al (2003)
<doi:10.1080/03461230110106435> and Aslett (2012)
<https://www.louisaslett.com/PhD_Thesis.pdf> are provided.
Author: Louis Aslett [aut, cre],
Wally Gilks [ctb]
Maintainer: Louis Aslett <louis.aslett@durham.ac.uk>
Diff between PhaseType versions 0.2.1 dated 2023-04-07 and 0.3.0 dated 2024-09-14
DESCRIPTION | 6 +++--- MD5 | 8 ++++---- NEWS | 6 ++++++ README.md | 21 ++++++++++++--------- src/utility.c | 4 ++-- 5 files changed, 27 insertions(+), 18 deletions(-)
Title: EZ-to-Use Biplots
Description: Provides users with an EZ-to-use platform for representing data
with biplots. Currently principal component analysis (PCA), canonical variate
analysis (CVA) and simple correspondence analysis (CA) biplots are included.
This is accompanied by various formatting
options for the samples and axes. Alpha-bags and concentration ellipses
are included for visual enhancements and interpretation. For an extensive
discussion on the topic, see Gower, J.C., Lubbe, S. and le Roux, N.J.
(2011, ISBN: 978-0-470-01255-0) Understanding Biplots. Wiley: Chichester.
Author: Sugnet Lubbe [aut, cre, cph] ,
Niel le Roux [aut] ,
Johane Nienkemper-Swanepoel [aut]
,
Raeesa Ganey [aut] ,
Ruan Buys [aut] ,
Zoe-Mae Adams [aut] ,
Peter Manefeldt [aut]
Maintainer: Sugnet Lubbe <muvisu@sun.ac.za>
Diff between biplotEZ versions 2.0 dated 2024-07-08 and 2.1 dated 2024-09-14
biplotEZ-2.0/biplotEZ/man/plot3D.Rd |only biplotEZ-2.1/biplotEZ/DESCRIPTION | 13 biplotEZ-2.1/biplotEZ/MD5 | 80 biplotEZ-2.1/biplotEZ/NAMESPACE | 3 biplotEZ-2.1/biplotEZ/R/CA.R | 2 biplotEZ-2.1/biplotEZ/R/CVA.R | 147 biplotEZ-2.1/biplotEZ/R/MDS.R | 3 biplotEZ-2.1/biplotEZ/R/PCA.R | 8 biplotEZ-2.1/biplotEZ/R/aesthetics.R | 437 - biplotEZ-2.1/biplotEZ/R/biplot.R | 23 biplotEZ-2.1/biplotEZ/R/calibrate_axes.R |only biplotEZ-2.1/biplotEZ/R/clouds.R | 4 biplotEZ-2.1/biplotEZ/R/more_biplots.R | 2 biplotEZ-2.1/biplotEZ/R/plot2D.R | 175 biplotEZ-2.1/biplotEZ/R/plotting.R | 86 biplotEZ-2.1/biplotEZ/R/utility.R | 3 biplotEZ-2.1/biplotEZ/inst/doc/Biplots_in_1D.html | 8 biplotEZ-2.1/biplotEZ/inst/doc/Biplots_in_3D.html | 54 biplotEZ-2.1/biplotEZ/inst/doc/CA_in_biplotEZ.Rmd | 1 biplotEZ-2.1/biplotEZ/inst/doc/CA_in_biplotEZ.html | 8 biplotEZ-2.1/biplotEZ/inst/doc/Class_separation.Rmd | 5 biplotEZ-2.1/biplotEZ/inst/doc/Class_separation.html | 4072 -------------- biplotEZ-2.1/biplotEZ/inst/doc/MDS.html | 650 -- biplotEZ-2.1/biplotEZ/inst/doc/biplotEZ.Rmd | 5 biplotEZ-2.1/biplotEZ/inst/doc/biplotEZ.html | 70 biplotEZ-2.1/biplotEZ/inst/doc/biplotEZ_enhancements.html | 12 biplotEZ-2.1/biplotEZ/man/AoD.Rd | 6 biplotEZ-2.1/biplotEZ/man/AoD.biplot.Rd | 6 biplotEZ-2.1/biplotEZ/man/CA.Rd | 3 biplotEZ-2.1/biplotEZ/man/CLPs.Rd |only biplotEZ-2.1/biplotEZ/man/CVA.Rd | 3 biplotEZ-2.1/biplotEZ/man/PCA.Rd | 6 biplotEZ-2.1/biplotEZ/man/axes.Rd | 113 biplotEZ-2.1/biplotEZ/man/axes_coordinates.Rd |only biplotEZ-2.1/biplotEZ/man/means.Rd | 52 biplotEZ-2.1/biplotEZ/man/newaxes.Rd | 61 biplotEZ-2.1/biplotEZ/man/newsamples.Rd | 60 biplotEZ-2.1/biplotEZ/man/plot.biplot.Rd | 26 biplotEZ-2.1/biplotEZ/man/samples.Rd | 83 biplotEZ-2.1/biplotEZ/vignettes/CA_in_biplotEZ.Rmd | 1 biplotEZ-2.1/biplotEZ/vignettes/Class_separation.Rmd | 5 biplotEZ-2.1/biplotEZ/vignettes/biplotEZ.Rmd | 5 biplotEZ-2.1/biplotEZ/vignettes/references.bib | 2 43 files changed, 985 insertions(+), 5318 deletions(-)
Title: Workflow for Open Reproducible Code in Science
Description: Create reproducible and transparent research projects in 'R'.
This package is based on the Workflow for Open
Reproducible Code in Science (WORCS), a step-by-step procedure based on best
practices for
Open Science. It includes an 'RStudio' project template, several
convenience functions, and all dependencies required to make your project
reproducible and transparent. WORCS is explained in the tutorial paper
by Van Lissa, Brandmaier, Brinkman, Lamprecht, Struiksma, & Vreede (2021).
<doi:10.3233/DS-210031>.
Author: Caspar J. Van Lissa [aut, cre]
,
Aaron Peikert [aut] ,
Andreas M. Brandmaier [aut]
Maintainer: Caspar J. Van Lissa <c.j.vanlissa@tilburguniversity.edu>
Diff between worcs versions 0.1.14 dated 2023-10-25 and 0.1.15 dated 2024-09-14
DESCRIPTION | 15 +- MD5 | 63 +++++--- NAMESPACE | 1 R/check_installation.R | 4 R/save_load.R | 14 - R/targets.R |only R/update_worcs_package.R |only R/worcs_badge.R | 4 R/worcs_project.R | 132 ++++++++++++++---- build/partial.rdb |binary build/vignette.rds |binary inst/doc/citation.R | 4 inst/doc/citation.Rmd | 2 inst/doc/citation.html | 13 - inst/doc/endpoints.R | 2 inst/doc/endpoints.html | 2 inst/doc/git_cloud.R | 2 inst/doc/reproduce.R | 2 inst/doc/setup-docker.R | 4 inst/doc/setup-docker.html | 2 inst/doc/setup.R | 2 inst/doc/synthetic_data.R |only inst/doc/synthetic_data.Rmd |only inst/doc/synthetic_data.html |only inst/doc/workflow.R | 4 inst/doc/workflow.Rmd | 2 inst/doc/workflow.html | 6 inst/rstudio/templates/project/resources/_targets.rmd |only inst/rstudio/templates/project/worcs.dcf | 11 + man/add_targets.Rd |only man/figures |only man/worcs_project.Rd | 4 tests/testthat/helper_usethis.R |only tests/testthat/test-checksum_markdown.R | 4 tests/testthat/test-targets.R |only vignettes/citation.Rmd | 2 vignettes/synthetic_data.Rmd |only vignettes/workflow.Rmd | 2 38 files changed, 201 insertions(+), 102 deletions(-)
Title: An Interface to IMF (International Monetary Fund) Data JSON API
Description: A straightforward interface for accessing the IMF
(International Monetary Fund) data JSON API,
available at <https://data.imf.org/>. This package offers direct access to
the primary API endpoints: Dataflow, DataStructure, and CompactData.
And, it provides an intuitive interface for exploring available
dimensions and attributes, as well as querying individual time-series datasets.
Additionally, the package implements a rate limit on API calls to reduce the
chances of exceeding service limits (limited to 10 calls every 5 seconds)
and encountering response errors.
Author: Pedro Baltazar [aut, cre]
Maintainer: Pedro Baltazar <pedrobtz@gmail.com>
Diff between imf.data versions 0.1.6 dated 2024-07-16 and 0.1.7 dated 2024-09-14
DESCRIPTION | 8 ++++---- MD5 | 8 ++++---- NEWS.md | 8 ++++++++ R/database.R | 25 ++++++++++++++++++------- R/methods.R | 5 ++++- 5 files changed, 38 insertions(+), 16 deletions(-)
Title: Machine Learning Time Series Forecasting
Description: Compute static, onestep and multistep time series forecasts for machine learning models.
Author: Ho Tsung-wu [aut, cre]
Maintainer: Ho Tsung-wu <tsungwu@ntnu.edu.tw>
Diff between iForecast versions 1.0.7 dated 2023-07-01 and 1.0.8 dated 2024-09-14
iForecast-1.0.7/iForecast/R/ttsLSTM.R |only iForecast-1.0.8/iForecast/DESCRIPTION | 18 ++- iForecast-1.0.8/iForecast/MD5 | 22 ++-- iForecast-1.0.8/iForecast/NAMESPACE | 5 - iForecast-1.0.8/iForecast/R/deprecate.R |only iForecast-1.0.8/iForecast/R/ttsAutoML.R | 8 + iForecast-1.0.8/iForecast/R/ttsCaret.R | 2 iForecast-1.0.8/iForecast/R/ttsPredict.R | 44 ++++----- iForecast-1.0.8/iForecast/man/iForecast.Rd | 18 +-- iForecast-1.0.8/iForecast/man/tts.autoML.Rd |only iForecast-1.0.8/iForecast/man/tts.caret.Rd |only iForecast-1.0.8/iForecast/man/ttsAutoML.Rd | 91 +----------------- iForecast-1.0.8/iForecast/man/ttsCaret.Rd | 135 +--------------------------- iForecast-1.0.8/iForecast/man/ttsLSTM.Rd | 113 ----------------------- 14 files changed, 78 insertions(+), 378 deletions(-)
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2024-09-10 1.0-1
Title: Bayesian Cure Rate Modeling for Time-to-Event Data
Description: A fully Bayesian approach in order to estimate a general family of cure rate models under the presence of covariates, see Papastamoulis and Milienos (2024) <doi:10.1007/s11749-024-00942-w>. The promotion time can be modelled (a) parametrically using typical distributional assumptions for time to event data (including the Weibull, Exponential, Gompertz, log-Logistic distributions), or (b) semiparametrically using finite mixtures of distributions. In both cases, user-defined families of distributions are allowed under some specific requirements. Posterior inference is carried out by constructing a Metropolis-coupled Markov chain Monte Carlo (MCMC) sampler, which combines Gibbs sampling for the latent cure indicators and Metropolis-Hastings steps with Langevin diffusion dynamics for parameter updates. The main MCMC algorithm is embedded within a parallel tempering scheme by considering heated versions of the target posterior distribution.
Author: Panagiotis Papastamoulis [aut, cre]
,
Fotios Milienos [aut]
Maintainer: Panagiotis Papastamoulis <papapast@yahoo.gr>
Diff between bayesCureRateModel versions 1.1 dated 2024-07-24 and 1.2 dated 2024-09-14
DESCRIPTION | 14 MD5 | 29 NAMESPACE | 7 R/bayesian_cure_rate_model.R | 1181 ++++++++++++++++++++++++++++++++++---- build/partial.rdb |binary data/marriage_dataset.RData |binary data/sim_mix_data.RData |only inst |only man/bayesCureRateModel-package.Rd | 20 man/compute_fdr_tpr.Rd |only man/cure_rate_MC3.Rd | 64 +- man/cure_rate_mcmc.Rd | 9 man/log_user_mixture.Rd |only man/marriage_dataset.Rd | 6 man/plot.bayesCureModel.Rd | 45 - man/predict.bayesCureModel.Rd |only man/residuals.bayesCureModel.Rd |only man/sim_mix_data.Rd |only man/summary.bayesCureModel.Rd | 34 - 19 files changed, 1222 insertions(+), 187 deletions(-)
More information about bayesCureRateModel at CRAN
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