min_q_lambda: Minimization of the quadratic approximation to objective...
In plde: Penalized Log-Density Estimation Using Legendre Polynomials
Description
Usage
Arguments
Author(s)
References
See Also
Description
min_q_lambda function gives the coefficient vector
(sm$coefficients) updated by the coordinate descent algorithm iteratively
until the quadratic approximation to the objective function convergences.
Usage
1
min_q_lambda(sm)
Arguments
sm
List of plde fit
Author(s)
JungJun Lee, Jae-Hwan Jhong, Young-Rae Cho, SungHwan Kim, Ja-yong Koo
References
JungJun Lee, Jae-Hwan Jhong, Young-Rae Cho, SungHwan Kim and Ja-Yong Koo. "Penalized Log-density Estimation Using Legendre Polynomials."
Submitted to Communications in Statistics - Simulation and Computation (2017), in revision.
See Also
plde documentation built on May 1, 2019, 7:46 p.m.
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Description Usage Arguments Author(s) References See Also
Description
min_q_lambda function gives the coefficient vector
(sm$coefficients) updated by the coordinate descent algorithm iteratively
until the quadratic approximation to the objective function convergences.
Usage
1 | min_q_lambda(sm)
|
Arguments
sm |
List of plde fit |
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.
See Also
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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