fdasrvf (version 1.9.4)

elastic.prediction: Elastic Prediction from Regression Models

Description

This function performs prediction from an elastic regression model with phase-variability

Usage

elastic.prediction(f, time, model, y = NULL, smooth_data = FALSE, sparam = 25)

Arguments

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)

Value

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

References

Tucker, J. D., Wu, W., Srivastava, A., Elastic Functional Logistic Regression with Application to Physiological Signal Classification, Electronic Journal of Statistics (2014), submitted.