Package: MEPDF 3.0

Martin Wiegand

MEPDF: Creation of Empirical Density Functions Based on Multivariate Data

Based on the input data an n-dimensional cube with sub cells of user specified side length is created. The number of sample points which fall in each sub cube is counted, and with the cell volume and overall sample size an empirical probability can be computed. A number of cubes of higher resolution can be superimposed. The basic method stems from J.L. Bentley in "Multidimensional Divide and Conquer". J. L. Bentley (1980) <doi:10.1145/358841.358850>. Furthermore a simple kernel density estimation method is made available, as well as an expansion of Bentleys method, which offers a kernel approach for the grid method.

Authors:Martin Wiegand, Saralees Nadarajah

MEPDF_3.0.tar.gz
MEPDF_3.0.tar.gz(r-4.5-noble)MEPDF_3.0.tar.gz(r-4.4-noble)
MEPDF_3.0.tgz(r-4.4-emscripten)MEPDF_3.0.tgz(r-4.3-emscripten)
MEPDF.pdf |MEPDF.html
MEPDF/json (API)

# Install 'MEPDF' in R:
install.packages('MEPDF', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

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

6 exports 0.00 score 5 dependencies 6 scripts 174 downloads

Last updated 6 years agofrom:cd5e5cfcd3. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 20 2024
R-4.5-linuxOKAug 20 2024

Exports:cubeekdeepakernelepdfnormkernelpseudokernel

Dependencies:gtoolsmvtnormplyrpracmaRcpp

Readme and manuals

Help Manual

Help pageTopics
cubecube
ekdeekde
epakernelepakernel
epdfepdf
normkernelnormkernel
pseudokernelpseudokernel