fget.features: Utility function to extract features from an object of 'class...

In features: Feature Extraction for Discretely-Sampled Functional Data

Description

This is a utility function that operates only on objects of class "features" that are returned by the function features(). Some of the key extracted features include mean value, first and second derivatives, critical points (i.e. local maxima and minima), curvature of function at critical points, wiggliness of the function, noise in data, and outliers in data.

Usage

fget(x)

Arguments

x	An object of class "features"

Value

A list with a number of extracted features of the underlying smooth function:

f	: a numeric vector containing 10 basic features of the function (in order): mean, min, max, std.dev, noise, signal-to-noise ratio, minimum and maximum of first derivative, wiggliness, and number of critical points
cpts	: Locations of the critical points (e.g. points where the first derivative is zero)
curvature	: Value of second derivative at the critical points
outliers	: Locations of outlying data points

See Also

features, plot.features, plot

Examples

# Estimating the smooth and the derivatives of a noisy and discretely sampled function. 
n <- 200
x <- sort(runif(n))
y <- exp(-0.2 * sin(2*pi*x)) + rnorm(n, sd=0.05)

ans <- features(x, y)
fget(ans)

features documentation built on May 2, 2019, 9:23 a.m.