elastic.prediction {fdasrvf} | R Documentation |
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 ( |
time |
vector of size |
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.
[Package fdasrvf version 2.3.1 Index]