getRegcoeffs.regmodel function

Regression coefficients for PLS model'

Returns a matrix with regression coefficients for the PLS model which can be applied to a data directly

## S3 method for class 'regmodel'
getRegcoeffs(
  obj,
  ncomp = obj$ncomp.selected,
  ny = 1,
  full = FALSE,
  alpha = 0.05,
  ...
)

Arguments

• obj: a PLS model (object of class pls)
• ncomp: number of components to return the coefficients for
• ny: if y is multivariate which variables you want to see the coefficients for
• full: if TRUE the method also shows p-values and t-values as well as confidence intervals for the coefficients (if available)
• alpha: significance level for confidence intervals (a number between 0 and 1, e.g. 0.05)
• ...: other parameters

Returns

A matrix with regression coefficients and (optinally) statistics.

Details

The method recalculates the regression coefficients found by the PLS algorithm taking into account centering and scaling of predictors and responses, so the matrix with coefficients can be applied directly to original data (yp = Xb).

If number of components is not specified, the optimal number, selected by user or identified by a model will be used.

If Jack-knifing method was used to get statistics for the coefficient the method returns all statistics as well (p-value, t-value, confidence interval). In this case user has to specified a number of y-variable (if there are many) to get the statistics and the coefficients for. The confidence interval is computed for unstandardized coefficients.