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dsdp
View on CRAN: Click
here
Download and install dsdp package within the R console
Install from CRAN:
install.packages("dsdp")
Install from Github:
library("remotes")
install_github("cran/dsdp") Install by package version:
library("remotes")
install_version("dsdp", "0.1.1") Attach the package and use:
library("dsdp")
Maintained by
Satoshi Kakihara
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-12-05
Latest Update: 2023-02-11
Description:
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
.
How to cite:
Satoshi Kakihara (2022). dsdp: Density Estimation with Semidefinite Programming. R package version 0.1.1, https://cran.r-project.org/web/packages/dsdp. Accessed 26 Jun. 2026.
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Other R packages that dsdp depends,
imports, suggests or enhances
Complete documentation for dsdp
Functions, R codes and Examples using
the dsdp R package
Some associated functions: cdf_expmodel . cdf_gaussmodel . databinning . datastats . dsdp . estimate.expmodel . estimate.gaussmodel . estimate . eval_poly . exp_est . expmodel . func.expmodel . func.gaussmodel . func . gauss_est . gaussmodel . histmean . igamma . igammac . mix2gauss . mix2gaussHist . mix2gauss_fun . mix2gauss_gen . mix3gauss . mix3gauss_fun . mix3gauss_gen . mixExpGammaHist . mixexpgamma . mixexpgamma_fun . mixexpgamma_gen . pdf_expmodel . pdf_gaussmodel . plot.expmodel . plot.gaussmodel . polyaxb . printf . summary.expmodel . summary.gaussmodel .
Some associated R codes: Full dsdp package functions and examples
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