zeitzeigerFitCv: Fit a periodic spline for each feature on cross-validation

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

Fit a periodic spline for each feature on cross-validation

Description

Fit a periodic spline for each feature for each fold of cross-validation.

Usage

zeitzeigerFitCv(x, time, foldid, nKnots = 3)

Arguments

x	Matrix of measurements, with observations in rows and features in columns.
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.
foldid	Vector of values indicating the fold to which each observation belongs.
nKnots	Number of internal knots to use for the periodic smoothing spline.

Value

A list consisting of the result from zeitzeigerFit() for each fold.

See Also

zeitzeigerFit(), zeitzeigerSpcCv(), zeitzeigerPredictCv()

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