elastic.prediction: Elastic Prediction from Regression Models

In fdasrvf: Elastic Functional Data Analysis

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.

fdasrvf documentation built on Oct. 5, 2024, 1:08 a.m.