Improved computation of the standard error in the regression coefficient estimates of a multivariate calibration model

A multivariate calibration model consists of regression coefficient estimates whose significance depends on the associated standard errors. A recently introduced leave-one-out (LOO) method for computing these standard errors is modified to achieve consistency with the jackknife method. The proposed modification amounts to multiplying the LOO standard errors with the factor (n - 1)/n(1/2), where n denotes the number of calibration samples. The potential improvement for realistic values of n is illustrated using a practical example.