estfunReg: Extract Empirical First Derivative of Log-likelihood Function

In mpath: Regularized Linear Models

Extract Empirical First Derivative of Log-likelihood Function

Description

Generic function for extracting the empirical first derivative of log-likelihood function of a fitted regularized model.

Usage

estfunReg(x, ...)

Arguments

x	a fitted model object.
...	arguments passed to methods.

Value

A matrix containing the empirical first derivative of log-likelihood functions. Typically, this should be an n x k matrix corresponding to n observations and k parameters. The columns should be named as in coef or terms, respectively.

Author(s)

Zhu Wang <[e-mail]>

References

Zhu Wang, Shuangge Ma and Ching-Yun Wang (2015) Variable selection for zero-inflated and overdispersed data with application to health care demand in Germany, Biometrical Journal. 57(5):867-84.

See Also

zipath

Examples

data("bioChemists", package = "pscl")
fm_zinb <- zipath(art ~ . | ., data = bioChemists, family = "negbin", nlambda=10, maxit.em=1)
res <- estfunReg(fm_zinb, which=which.min(fm_zinb$bic))

mpath documentation built on Jan. 7, 2023, 1:17 a.m.