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
DOI: 10.32614/CRAN.package.dsdp
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


Reference manual: dsdp.pdf
Vignettes: Tutorial


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


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