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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 |
| 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 |
| Reference manual: | plde.pdf |
| Package source: | plde_0.1.2.tar.gz |
| Windows binaries: | r-devel: plde_0.1.2.zip, r-release: plde_0.1.2.zip, r-oldrel: plde_0.1.2.zip |
| macOS binaries: | r-release (arm64): plde_0.1.2.tgz, r-oldrel (arm64): plde_0.1.2.tgz, r-release (x86_64): plde_0.1.2.tgz, r-oldrel (x86_64): plde_0.1.2.tgz |
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