coef.GIC.compCL: Extracts estimated coefficients from a '"GIC.compCL"' object.
In Compack: Regression with Compositional Covariates

Description Usage Arguments Details Value Author(s) References See Also Examples

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

1 2	## S3 method for class 'GIC.compCL' coef(object, s = "lam.min", ...)

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.

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.

The coefficients at the requested tuning parameter values in s.

Zhe Sun and Kun Chen

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.

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

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))