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/>.

Package details

AuthorSatoshi Kakihara [aut, cre], Takashi Tsuchiya [aut]
MaintainerSatoshi Kakihara <skakihara@gmail.com>
LicenseMIT + file LICENSE
URL https://tsuchiya-lab.github.io/dsdp/
Package repositoryView on CRAN
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dsdp documentation built on Feb. 16, 2023, 8:36 p.m.