This function gets coefficients from a
compCL object, using
value(s) of the penalty parameter
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
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.
1 2 3 4 5 6 7 8 9
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))
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.