plde: Penalized Log-Density Estimation Using Legendre Polynomials
We present a penalized log-density estimation method using Legendre polynomials with lasso penalty to adjust estimate's smoothness. Re-expressing the logarithm of the density estimator via a linear combination of Legendre polynomials, we can estimate parameters by maximizing the penalized log-likelihood function. Besides, we proposed an implementation strategy that builds on the coordinate decent algorithm, together with the Bayesian information criterion (BIC).
Version: |
0.1.2 |
Published: |
2018-07-01 |
DOI: |
10.32614/CRAN.package.plde |
Author: |
JungJun Lee, Jae-Hwan Jhong, Young-Rae Cho, SungHwan Kim, Ja-yong Koo |
Maintainer: |
JungJun Lee <ljjoj at korea.ac.kr> |
License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: |
no |
CRAN checks: |
plde results |
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