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dsdp: Density Estimation with Semidefinite Programming

The models of probability density functions are Gaussian or exponential distributions with polynomial correction terms. Using a maximum likelihood method, 'dsdp' computes parameters of Gaussian or exponential distributions together with degrees of polynomials by a grid search, and coefficient of polynomials by a variant of semidefinite programming. It adopts Akaike Information Criterion for model selection. See a vignette for a tutorial and more on our 'Github' repository <https://github.com/tsuchiya-lab/dsdp/>.

Version: 0.1.1
Depends: R (≥ 2.10)
Imports: ggplot2, rlang, stats
Suggests: rmarkdown, knitr
Published: 2023-02-11
Author: Satoshi Kakihara [aut, cre], Takashi Tsuchiya [aut]
Maintainer: Satoshi Kakihara <skakihara at gmail.com>
BugReports: https://github.com/tsuchiya-lab/dsdp/issues
License: MIT + file LICENSE
URL: https://tsuchiya-lab.github.io/dsdp/
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: dsdp results

Documentation:

Reference manual: dsdp.pdf
Vignettes: Tutorial

Downloads:

Package source: dsdp_0.1.1.tar.gz
Windows binaries: r-devel: dsdp_0.1.1.zip, r-release: dsdp_0.1.1.zip, r-oldrel: dsdp_0.1.1.zip
macOS binaries: r-release (arm64): dsdp_0.1.1.tgz, r-oldrel (arm64): dsdp_0.1.1.tgz, r-release (x86_64): dsdp_0.1.1.tgz, r-oldrel (x86_64): dsdp_0.1.1.tgz
Old sources: dsdp archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=dsdp to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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