Provider: ingentaconnect
Database: ingentaconnect
Content: application/x-research-info-systems
TY - ABST
AU - Lorber, Avraham
AU - Kowalski, Bruce R.
TI - A Note on the Use of the Partial Least-Squares Method for Multivariate Calibration
JO - Applied Spectroscopy
PY - 1988-11-01T00:00:00///
VL - 42
IS - 8
SP - 1572
EP - 1574
KW - Regression
KW - PLS
KW - Multivariate calibration
KW - Singular value decomposition
N2 - The multivariate calibration problem is a problem of predicting the concentration in an unknown sample, *c*
_{un}, from the response vector of an unknown sample, **r**
_{un} (*J* responses). The predicting equation can be arranged in the form

*ĉ*
_{un}
= **r**
_{un}
^{T}
**R**
^{+}
**c.** (1)

**R**
^{+} is the pseudo-inverse of the calibration set matrix of responses, **R**, whose column indices correspond to the *J* sensors or wavelengths and row indices
correspond to the *I* samples (individuals), and **c** is the vector of concentrations for the *I* samples of the analyte in each of the calibration samples. Derivation of Eq. 1 is described in Ref. 1. The PLS regression involves solution of the predicting equation.
UR - http://www.ingentaconnect.com/content/sas/sas/1988/00000042/00000008/art00036
M3 - doi:10.1366/0003702884429481
UR - http://dx.doi.org/10.1366/0003702884429481
ER -