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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/>.
Getting started
Browse package contents
Package details |
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| Author | Satoshi Kakihara [aut, cre], Takashi Tsuchiya [aut] |
| Maintainer | Satoshi Kakihara <skakihara@gmail.com> |
| License | MIT + file LICENSE |
| Version | 0.1.1 |
| URL | https://tsuchiya-lab.github.io/dsdp/ |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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Try the dsdp package in your browser
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