Provider: ingentaconnect
Database: ingentaconnect
Content: application/x-research-info-systems
TY - ABST
AU - Lorber, Avraham
AU - Kowalski, Bruce R.
TI - Alternatives to Cross-Validatory Estimation of the Number of Factors in Multivariate Calibration
JO - Applied Spectroscopy
PY - 1990-11-01T00:00:00///
VL - 44
IS - 9
SP - 1464
EP - 1470
KW - Multivariate calibration
KW - Cross-validation
KW - PCR
KW - PLS
KW - Regression
N2 - Overcoming the collinearity problem in regression by data compression techniques [i.e., principal component regression (PCR) and partial least-squares (PLS)] requires estimation of the number of factors (principal component) to use for the model. The most common approach is to use cross-validation
for this purpose. Unfortunately, cross-validation is time consuming to carry out. Accordingly, we have searched for time-saving methods to estimate the number of factors. Two approaches were considered. The first uses the estimated standard error of the model and the second is an approximation
to a cross-validation leave-one-out method. Both alternatives have been tested on spectroscopic data. It has been found that, when the number of wavelengths is limited, both methods give results similar to those obtained by full cross-validation both for PCR and PLS. However, when the number
of wavelengths is large, the tested methods are reliable only for PCR and not for PLS.
UR - http://www.ingentaconnect.com/content/sas/sas/1990/00000044/00000009/art00005
M3 - doi:10.1366/0003702904417788
UR - http://dx.doi.org/10.1366/0003702904417788
ER -