Add to ORKGMultivariate calibration uses an estimated relationship between a multivariate response Y (of dimension q) and an explanatory vector X (of dimension p) to predict unknown X in future from further observed responses. If the prediction sample is inconsistent with the calibration data, it is a prediction outlier (Martens and Naes, 1989). One of the main problems in multivariate calibratio
With the proliferation of multivariate calibration methods based on artificial neural networks, expr...
We propose a new method named calibrated multivariate regression (CMR) for fitting high dimensional ...
In analytical chemistry, multivariate calibration is applied when substituting a time-consuming refe...
In multivariate calibration the relationship between a g-variate response vector Y and p explanatory...
Most of the current expressions used to calculate figures of merit in multivariate calibration have ...
Ten techniques used for selection of useful predictors in multivariate calibration and in other case...
This paper gives an introduction to multivariate calibration from a chemometrics perspective and rev...
A {ital q}-vector of responses, y, is related to a {ital p}-vector of explanatory variables, x, thro...
AbstractThe problem of combining independent information from different sources in a multivariate ca...
Consider multivariate linear calibration of a single standard. We show that a selection of the q' mo...
A unifying framework for calibration and prediction in multivariate calibration is shown based on th...
AbstractIn univariate calibration problems two different estimators are commonly in use. They are re...
In univariate calibration problems two different estimators are commonly in use. They are referred t...
In the present report, an upgrade of a MATLAB graphical user interface (GUI) toolbox for implementin...
We propose a new method named calibrated multivariate regression (CMR) for fitting high dimensional ...
With the proliferation of multivariate calibration methods based on artificial neural networks, expr...
We propose a new method named calibrated multivariate regression (CMR) for fitting high dimensional ...
In analytical chemistry, multivariate calibration is applied when substituting a time-consuming refe...
In multivariate calibration the relationship between a g-variate response vector Y and p explanatory...
Most of the current expressions used to calculate figures of merit in multivariate calibration have ...
Ten techniques used for selection of useful predictors in multivariate calibration and in other case...
This paper gives an introduction to multivariate calibration from a chemometrics perspective and rev...
A {ital q}-vector of responses, y, is related to a {ital p}-vector of explanatory variables, x, thro...
AbstractThe problem of combining independent information from different sources in a multivariate ca...
Consider multivariate linear calibration of a single standard. We show that a selection of the q' mo...
A unifying framework for calibration and prediction in multivariate calibration is shown based on th...
AbstractIn univariate calibration problems two different estimators are commonly in use. They are re...
In univariate calibration problems two different estimators are commonly in use. They are referred t...
In the present report, an upgrade of a MATLAB graphical user interface (GUI) toolbox for implementin...
We propose a new method named calibrated multivariate regression (CMR) for fitting high dimensional ...
With the proliferation of multivariate calibration methods based on artificial neural networks, expr...
We propose a new method named calibrated multivariate regression (CMR) for fitting high dimensional ...
In analytical chemistry, multivariate calibration is applied when substituting a time-consuming refe...