| elastic.prediction {fdasrvf} | R Documentation |
This function performs prediction from an elastic regression model with phase-variability
elastic.prediction(f, time, model, y = NULL, smooth_data = FALSE, sparam = 25)
f |
matrix (N x M) of M functions with N samples |
time |
vector of size N describing the sample points |
model |
list describing model from elastic regression methods |
y |
responses of test matrix f (default=NULL) |
smooth_data |
smooth data using box filter (default = F) |
sparam |
number of times to apply box filter (default = 25) |
Returns a list containing
y_pred |
predicted values of f or probabilities depending on model |
SSE |
sum of squared errors if linear |
y_labels |
labels if logistic model |
PC |
probability of classification if logistic |
Tucker, J. D., Wu, W., Srivastava, A., Elastic Functional Logistic Regression with Application to Physiological Signal Classification, Electronic Journal of Statistics (2014), submitted.