Calibrates (builds) a PLS model for given data and parameters
pls.cal(x, y, ncomp, center, scale, method, cv, alpha, coeffs.ci, coeffs.alpha,
info, light, exclcols = NULL, exclrows = NULL, ncomp.selcrit)a matrix with x values (predictors)
a matrix with y values (responses)
number of components to calculate
logical, do mean centering or not
logical, do standardization or not
algorithm for computing PLS model (only 'simpls' is supported so far)
logical, does calibration for cross-validation or not
significance level for calculating statistical limits for residuals.
method to calculate p-values and confidence intervals for regression coefficients (so far only
jack-knifing is availavle: ='jk').
significance level for calculating confidence intervals for regression coefficients.
short text with information about the model.
run normal or light (faster) version of PLS without calculationg some performance statistics.
columns of x to be excluded from calculations (numbers, names or vector with logical values)
rows to be excluded from calculations (numbers, names or vector with logical values)
criterion for selecting optimal number of components ('min' for
first local minimum of RMSECV and 'wold' for Wold's rule.)
model an object with calibrated PLS model