Compack (version 0.1.0)

coef.GIC.compCL: Extracts estimated coefficients from a "GIC.compCL" object.

Description

This function gets coefficients from a compCL object, using the stored "compCL.fit" object.

Usage

# S3 method for GIC.compCL
coef(object, s = "lam.min", ...)

Arguments

object

fitted "GIC.compCL" object.

s

value(s) of the penalty parameter lam at which coefficients are requested.

• s="lam.min" (default) stored in the GIC.compCL object, which gives value of lam that achieves the minimum value of GIC.

• If s is numeric, it is taken as the value(s) of lam to be used.

• If s = NULL, the whole sequence of lam stored in the GIC.compCGL object is used.

…

not used.

Value

The coefficients at the requested tuning parameter values in s.

Details

s is a vector of lambda values at which the coefficients are requested. If s is not in the lam sequence used for fitting the model, the coef function will use linear interpolation, so the function should be used with caution.

References

Lin, W., Shi, P., Peng, R. and Li, H. (2014) Variable selection in regression with compositional covariates, https://academic.oup.com/biomet/article/101/4/785/1775476. Biometrika 101 785-979.

See Also

GIC.compCL and compCL, and predict, and plot methods for "GIC.compCL" object.

Examples

# NOT RUN {
p = 30
n = 50
beta = c(1, -0.8, 0.6, 0, 0, -1.5, -0.5, 1.2)
beta = c(beta, rep(0, times = p - length(beta)))
Comp_data = comp_Model(n = n, p = p, beta = beta, intercept = FALSE)
GICm1 <- GIC.compCL(y = Comp_data$y, Z = Comp_data$X.comp, Zc = Comp_data$Zc,
                    intercept = Comp_data$intercept)
coef(GICm1)
coef(GICm1, s = c(1, 0.5, 0.1))

# }