Faq how are error bars calculated regression model: Difference between revisions

From Eigenvector Research Documentation Wiki
Jump to navigation Jump to search
imported>Lyle
No edit summary
imported>Lyle
 
Line 5: Line 5:
===Possible Solutions:===
===Possible Solutions:===


The error bars reported for inverse least squares models (and from the [[Ils_esterror]] function) represent the estimation error for each prediction, see:
The error bars reported for inverse least squares models (and from the <code>[[ils_esterror]]</code> function) represent the estimation error for each prediction, see:


Faber, N.M. and Bro, R., Chemomem. and Intell. Syst., 61, 133-149 (2002)
Faber, N.M. and Bro, R., Chemomem. and Intell. Syst., 61, 133-149 (2002)

Latest revision as of 13:10, 8 January 2019

Issue:

How are the error bars calculated for a regression model and can they be related to a confidence limit (confidence in the prediction)?

Possible Solutions:

The error bars reported for inverse least squares models (and from the ils_esterror function) represent the estimation error for each prediction, see:

Faber, N.M. and Bro, R., Chemomem. and Intell. Syst., 61, 133-149 (2002)

They can be read as a standard deviation of the estimate. However because the underlying distribution is not clearly known (and is a matter of research), a confidence limit is not reported.


Still having problems? Please contact our helpdesk at helpdesk@eigenvector.com