Package: qmd 1.1.2

Nicolas Dietrich

qmd: Quantification of Multivariate Dependence

A multivariate copula-based dependence measure. For more information, see Griessenberger, Junker, Trutschnig (2022), On a multivariate copula-based dependence measure and its estimation, Electronic Journal of Statistics, 16, 2206-2251.

Authors:Nicolas Dietrich [aut, cre], Florian Griessenberger [aut], Robert R. Junker [aut], Valentin Petztel [aut], Wolfgang Trutschnig [aut]

qmd_1.1.2.tar.gz
qmd_1.1.2.tar.gz(r-4.5-noble)qmd_1.1.2.tar.gz(r-4.4-noble)
qmd_1.1.2.tgz(r-4.4-emscripten)qmd_1.1.2.tgz(r-4.3-emscripten)
qmd.pdf |qmd.html✨
qmd/json (API)

# Install 'qmd' in R:

install.packages('qmd', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

c++– GNU Standard C++ Library v3

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 240 downloads 6 exports 79 dependencies

Last updated 2 years agofrom:02de81ed38. Checks:OK: 2. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 23 2024
R-4.5-linux-x86_64	OK	Nov 23 2024

Exports:ECBC feature_selection qmd qmdrank seq_until_changes zeta1

Dependencies:ADGofTest base64enc bslib cachem cli colorspace colourpicker commonmark copula cowplot crayon data.table digest dplyr evaluate fansi farver fastmap fontawesome fs generics ggExtra ggplot2 glue gridExtra gsl gtable highr htmltools htmlwidgets httpuv isoband jquerylib jsonlite knitr labeling later lattice lifecycle magrittr MASS Matrix memoise mgcv mime miniUI munsell mvtnorm nlme numDeriv pcaPP pillar pkgconfig promises pspline qad R6 rappdirs RColorBrewer Rcpp rlang rmarkdown sass scales shiny shinyjs sourcetools stabledist tibble tidyselect tinytex utf8 vctrs viridis viridisLite withr xfun xtable yaml

Help page	Topics
Returns the sizes of the adaptive bins used for the adaptive ECBC for one vector.	.adaptive_masses
Returns a list of reverse cumulative margins of a CB copula. The nth entry is thus the copula of X1,...,Xn	.CB_make_cumulative_df
Calculates an empirical CB approximation with adaptive bin sizes. This will be faster on data with many ties.	.EACBC
Returns non 0 entries of the EACBC	.EACBC_nonzero
Calculates the empirical checkerboard approximation to some data.	.ECBC
Computes the D1-difference of two CB matrizes on a local CB dimension	.local_kernel_integral
Creates a random CB copula of resolution 2^steps	.random_CB
Generate a sample of some CB copula-	.sample_CB
Compute empirical checkerboard copula in arbitrary dimension	ECBC
Variable selection using the qmd-dependence values	feature_selection
Quantification of Multivariate Dependence	qmd
Equivalent to rank(x, ties.method = "max") but not as stupidly slow	qmdrank
Returns a vector	seq_until_changes
Multivariate dependence measure	zeta1

Package: qmd 1.1.2

qmd: Quantification of Multivariate Dependence

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