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Package: dsdp 0.1.2

Satoshi Kakihara

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/>.

Authors:Satoshi Kakihara [aut, cre], Takashi Tsuchiya [aut]

dsdp_0.1.2.tar.gz
dsdp_0.1.2.zip(r-4.7-x86_64)dsdp_0.1.2.zip(r-4.7-arm64)dsdp_0.1.2.zip(r-4.6-x86_64)dsdp_0.1.2.zip(r-4.6-arm64)dsdp_0.1.2.zip(r-4.5-x86_64)
dsdp_0.1.2.tgz(r-4.6-x86_64)dsdp_0.1.2.tgz(r-4.6-arm64)dsdp_0.1.2.tgz(r-4.5-x86_64)dsdp_0.1.2.tgz(r-4.5-arm64)
dsdp_0.1.2.tar.gz(r-4.7-arm64)dsdp_0.1.2.tar.gz(r-4.7-x86_64)dsdp_0.1.2.tar.gz(r-4.6-arm64)dsdp_0.1.2.tar.gz(r-4.6-x86_64)
dsdp_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
dsdp/json (API)

# Install 'dsdp' in R:

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

Bug tracker:https://github.com/tsuchiya-lab/dsdp/issues

Pkgdown/docs site:https://tsuchiya-lab.github.io

Uses libs:

openblas– Optimized BLAS
fortran– Runtime library for GNU Fortran applications

Datasets:

mix2gauss - Datasets of Mixture of 2 Gaussian Distributions
mix2gaussHist - Dataset of Mixture of 2 Gaussian Distributions: Histogram version
mix3gauss - Datasets of Mixture of 3 Gaussian Distributions
mixexpgamma - Dataset of Mixture of Exponential Distribution and Gamma Distribution
mixExpGammaHist - Dataset of Mixture of Exponential Distribution and Gamma Distribution: Histogram Version

On CRAN:

archived packages r-universe openblas fortran

3.40 score 5 stars 6 scripts 105 downloads 24 exports 17 dependencies

Last updated from:60ae8f9885 (on package/dsdp). Checks:13 WARNING, 2 OK. Indexed: no.

Target	Result	Time
linux-devel-arm64	WARNING	105
linux-devel-x86_64	WARNING	208
source / vignettes	OK	240
linux-release-arm64	WARNING	98
linux-release-x86_64	WARNING	111
macos-release-arm64	WARNING	119
macos-release-x86_64	WARNING	229
macos-oldrel-arm64	WARNING	121
macos-oldrel-x86_64	WARNING	328
windows-devel-arm64	WARNING	227
windows-devel-x86_64	WARNING	151
windows-release-arm64	WARNING	263
windows-release-x86_64	WARNING	104
windows-oldrel-x86_64	WARNING	116
wasm-release	OK	88

Exports:cdf_expmodel cdf_gaussmodel databinning datastats estimate eval_poly exp_est expmodel func gauss_est gaussmodel histmean igamma igammac mix2gauss_fun mix2gauss_gen mix3gauss_fun mix3gauss_gen mixexpgamma_fun mixexpgamma_gen pdf_expmodel pdf_gaussmodel polyaxb printf

Dependencies:cli cpp11 farver ggplot2 glue gtable isoband labeling lifecycle R6 RColorBrewer rlang S7 scales vctrs viridisLite withr

A Tutorial for dsdp

Rendered fromTutorial.Rmdusingknitr::rmarkdown

Last update: 2026-09-12
Started: 2026-09-12

Help page	Topics
Cumulative distribution function of Expomemtial-based model	cdf_expmodel
Cumulative distribution function of Gaussian-based model	cdf_gaussmodel
Reduce a data set to representatives of bins and their frequencies	databinning
Compute the mean and the standard deviation of a data set	datastats
dsdp: Density Estimation using Semidefinite Programming	dsdp
Generic Method for estimation	estimate
Estimate Exponential-based model 'expmodel'	estimate.expmodel
Estimate Gaussian-based model 'gaussmodel'	estimate.gaussmodel
Evaluate a polynomial	eval_poly
Estimate coefficients of a polynomial in Exponential-based Model	exp_est
Constructor for S3 class 'expmodel'	expmodel
Generic Method for evaluate the estimate	func
Return the evaluation of a vector with Exponential-based model	func.expmodel
Return the evaluation of a vector with Gaussian-based model	func.gaussmodel
Estimate coefficients of a polynomial in Gaussian-based model	gauss_est
Constructor for S3 class 'gaussmodel'	gaussmodel
Compute the mean of a data set	histmean
Incomplete Gamma Function	igamma
Complementary Incomplete Gamma Function	igammac
Datasets of Mixture of 2 Gaussian Distributions	mix2gauss
A density function of mixed Gaussian distributions	mix2gauss_fun
Generate mixed Gaussian random numbers	mix2gauss_gen
Dataset of Mixture of 2 Gaussian Distributions: Histogram version	mix2gaussHist
Datasets of Mixture of 3 Gaussian Distributions	mix3gauss
A density function of mixed gaussian distribution	mix3gauss_fun
Generate Mixed Gaussian Random Numbers	mix3gauss_gen
Dataset of Mixture of Exponential Distribution and Gamma Distribution	mixexpgamma
A density function of Mixed Exponential and Gamma Distributions	mixexpgamma_fun
Generate random numbers of Mixed Exponential and Gamma Distributions	mixexpgamma_gen
Dataset of Mixture of Exponential Distribution and Gamma Distribution: Histogram Version	mixExpGammaHist
Probability density function of Exponential-based model	pdf_expmodel
Probability density function of Gaussian-based model	pdf_gaussmodel
Plot a histogram and estimated densities/distributions of Exponential-based model object	plot.expmodel
Plot a histogram and estimated densities/distributions of Gaussian-based model object	plot.gaussmodel
Substitute a coefficient of polynomial	polyaxb
printf	printf
Summary of Exponential-based 'expmodel' object.	summary.expmodel
Summary of Gaussian-based model 'gaussmodel' object	summary.gaussmodel

Package: dsdp 0.1.2

dsdp: Density Estimation with Semidefinite Programming

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Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)