model_selection: Optimal model selection
In plde: Penalized Log-Density Estimation Using Legendre Polynomials
Description
Usage
Arguments
Author(s)
References
Description
model_selection function gives the optimal model over the whole
plde fits based on information criterian (AIC, BIC).
The optimal model is saved at fit$optimal.
Usage
1
model_selection(fit, method = "AIC")
Arguments
fit
Entire list of plde fit by all tuning parameters
method
model selection criteria. 'AIC' or 'BIC' is used. Default is 'AIC'.
Author(s)
JungJun Lee, Jae-Hwan Jhong, Young-Rae Cho, SungHwan Kim, Ja-yong Koo
References
JungJun Lee, Jae-Hwan Jhong, Young-Rae Cho, SungHwan Kim and Ja-Yong Koo. "Penalized Log-density Estimation Using Legendre Polynomials."
Submitted to Communications in Statistics - Simulation and Computation (2017), in revision.
plde documentation built on May 1, 2019, 7:46 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Usage Arguments Author(s) References
Description
model_selection function gives the optimal model over the whole
plde fits based on information criterian (AIC, BIC).
The optimal model is saved at fit$optimal.
Usage
1 | model_selection(fit, method = "AIC")
|
Arguments
fit |
Entire list of plde fit by all tuning parameters |
method |
model selection criteria. 'AIC' or 'BIC' is used. Default is 'AIC'. |
Author(s)
JungJun Lee, Jae-Hwan Jhong, Young-Rae Cho, SungHwan Kim, Ja-yong Koo
References
JungJun Lee, Jae-Hwan Jhong, Young-Rae Cho, SungHwan Kim and Ja-Yong Koo. "Penalized Log-density Estimation Using Legendre Polynomials." Submitted to Communications in Statistics - Simulation and Computation (2017), in revision.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.