spls.wrap: Build an spls model with shrinkage and selection by the...

In wrbrooks/spls.wrap: Wraps the spls package for variable selection and model-building.

Description

Build an spls model with shrinkage and selection by the LASSO.

Usage

spls.wrap(x, y, K = NULL, eta = seq(0.05, 0.95, 0.05), kappa = 0.5, select = "pls2", fit = "simpls", scale.x = TRUE, scale.y = FALSE, eps = 1e-04, maxstep = 100, trace = FALSE)

Arguments

x
y
K
eta
kappa
select
fit
scale.x
scale.y
eps
maxstep
trace

Author(s)

Wesley Brooks

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (x, y, K = NULL, eta = seq(0.05, 0.95, 0.05), kappa = 0.5, 
    select = "pls2", fit = "simpls", scale.x = TRUE, scale.y = FALSE, 
    eps = 1e-04, maxstep = 100, trace = FALSE) 
{
    result = list()
    class(result) = "spls.wrap"
    if (is.null(K)) {
        max.K = min(ncol(x), floor(nrow(x)/10))
        K = 1:max.K
    }
    cv = cv.spls(x = x, y = y, K = K, eta = eta, fit = fit, select = select, 
        scale.x = scale.x, scale.y = scale.y)
    m = spls(x = x, y = y, K = cv$K.opt, eta = cv$eta.opt, kappa = kappa, 
        select = select, fit = fit, scale.x = scale.x, scale.y = scale.y, 
        eps = eps, maxstep = maxstep, trace = trace)
    ci = ci.spls(m, plot.it = FALSE)
    coef = correct.spls(ci)
    result[["coef"]] = coef
    result[["vars"]] = rownames(coef)
  }

wrbrooks/spls.wrap documentation built on May 4, 2019, 11:59 a.m.