predictIntensity: Calculate time-dependent mean

In jakejh/zeitzeiger: Regularized Supervised Learning for Data from Rhythmic Systems

Calculate time-dependent mean

Description

Calculate the expected value of each feature.

Usage

predictIntensity(fitCoef, time, period = 1, knots = NULL)

Arguments

fitCoef	Matrix of coefficients from the spline fits, where rows correspond to features and columns correspond to variables in the model.
time	Vector of values of the periodic variable for the observations, where 0 corresponds to the lowest possible value and 1 corresponds to the highest possible value.
period	Period for the periodic variable.
knots	Optional vector of knots. This argument is designed for internal use.

Value

Matrix of predicted measurements, where rows correspond to time-points and columns correspond to features.

See Also

zeitzeigerFit()

jakejh/zeitzeiger documentation built on Dec. 4, 2022, 4:11 p.m.