crossval.regmodel: Cross-validation of a regression model

In mdatools: Multivariate Data Analysis for Chemometrics

Cross-validation of a regression model

Description

Does cross-validation of a regression model

Usage

crossval.regmodel(obj, x, y, cv, cal.fun, pred.fun, cv.scope = "local")

Arguments

obj	a regression model (object of class regmodel)
x	a matrix with x values (predictors from calibration set)
y	a matrix with y values (responses from calibration set)
cv	number of segments (if cv = 1, full cross-validation will be used)
cal.fun	reference to function for model calibration
pred.fun	reference to function for getting predicted y-values (see description)
cv.scope	scope for center/scale operations inside CV loop: 'global' — using globally computed mean and std or 'local' — recompute new for each local calibration set.

Value

object of class plsres with results of cross-validation

Function 'pred.fun' must take four agruments: autoscaled x-values, array with regression coefficients, vectors for centring and scaling of y-values (if used). The function must return predicted y-values in original units (unscaled and uncentered).

mdatools documentation built on Sept. 11, 2024, 7:59 p.m.