| predict.sgs {sgs} | R Documentation |
Predict using one of the following object types: "sgs", "sgs_cv", "gslope", "gslope_cv".
Description
Performs prediction from one of the following fits: fit_sgs(), fit_sgs_cv(), fit_gslope(), fit_gslope_cv(). The predictions are calculated for each "lambda" value in the path.
Usage
## S3 method for class 'sgs'
predict(object, x, ...)
Arguments
object |
Object of one of the following classes: |
x |
Input data to use for prediction. |
... |
further arguments passed to stats function. |
Value
A list containing:
response |
The predicted response. In the logistic case, this represents the predicted class probabilities. |
class |
The predicted class assignments. Only returned if type = "logistic" in the |
See Also
fit_sgs(), fit_sgs_cv(), fit_gslope(), fit_gslope_cv()
Other SGS-methods:
as_sgs(),
coef.sgs(),
fit_sgs(),
fit_sgs_cv(),
plot.sgs(),
print.sgs(),
scaled_sgs()
Other gSLOPE-methods:
coef.sgs(),
fit_gslope(),
fit_gslope_cv(),
plot.sgs(),
print.sgs()
Examples
# specify a grouping structure
groups = c(1,1,1,2,2,3,3,3,4,4)
# generate data
data = gen_toy_data(p=10, n=5, groups = groups, seed_id=3,group_sparsity=1)
# run SGS
model = fit_sgs(X = data$X, y = data$y, groups = groups, type="linear", lambda = 1, alpha=0.95,
vFDR=0.1, gFDR=0.1, standardise = "l2", intercept = TRUE, verbose=FALSE)
# use predict function
model_predictions = predict(model, x = data$X)