Get the coefficients from a fitted cv.ptLasso model.
Arguments
- object
fitted
"cv.ptLasso"object.- model
string indicating which coefficients to retrieve. Must be one of "all", "individual", "overall" or "pretrain".
- alpha
value between 0 and 1, indicating which alpha to use. If
NULL, return coefficients from all models. Only impacts the results for model = "all" or model = "pretrain".- ...
other arguments to be passed to the
"coef"function. May be e.g.s = "lambda.min".
Examples
set.seed(1234)
out = gaussian.example.data(k=2, class.sizes = c(50, 50))
x = out$x; y=out$y; groups = out$group;
cvfit = cv.ptLasso(x, y, groups = groups, family = "gaussian", type.measure = "mse")
# Get all model coefficients.
names(coef(cvfit))
#> [1] "individual" "pretrain" "overall"
coef(cvfit, model = "overall") # Overall model only
#> 62 x 1 sparse Matrix of class "dgCMatrix"
#> lambda.1se
#> (Intercept) -2.0911194
#> groups2 6.9480612
#> .
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#> 2.7965296
#> 3.3203621
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#> 0.5383593
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length(coef(cvfit, model = "individual")) # List of coefficients for each group model
#> [1] 2
length(coef(cvfit, model = "pretrain", alpha = .5)) # List of coefficients for each group model
#> [1] 2