Standard Error of Regularized Estimators

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Description

Generic function for computing standard errors of non-zero regularized estimators

Usage

1

Arguments

x

a fitted model object.

which

which penalty parameter(s)?

log

if TRUE, the computed standard error is for log(theta) for negative binomial regression, otherwise, for theta.

...

arguments passed to methods.

Value

A vector containing standard errors of non-zero regularized estimators.

Author(s)

Zhu Wang <zwang@connecticutchildrens.org>

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

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

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