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- Q7828122 subject Q7020694.
- Q7828122 subject Q7157387.
- Q7828122 subject Q7483213.
- Q7828122 subject Q7849419.
- Q7828122 subject Q8646998.
- Q7828122 abstract "In applied statistics, total least squares is a type of errors-in-variables regression, a least squares data modeling technique in which observational errors on both dependent and independent variables are taken into account. It is a generalization of Deming regression and also of orthogonal regression, and can be applied to both linear and non-linear models. The total least squares approximation of the data is generically equivalent to the best, in the Frobenius norm, low-rank approximation of the data matrix.".
- Q7828122 thumbnail Total_least_squares.svg?width=300.
- Q7828122 wikiPageExternalLink 9805076.
- Q7828122 wikiPageExternalLink JGS_Amiri_Jazaeri_2012.pdf.
- Q7828122 wikiPageExternalLink thesis.pdf.
- Q7828122 wikiPageExternalLink kmath110.htm.
- Q7828122 wikiPageExternalLink index.html.
- Q7828122 wikiPageWikiLink Q102454.
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- Q7828122 wikiPageWikiLink Q598870.
- Q7828122 wikiPageWikiLink Q6692777.
- Q7828122 wikiPageWikiLink Q7020694.
- Q7828122 wikiPageWikiLink Q7157387.
- Q7828122 wikiPageWikiLink Q74304.
- Q7828122 wikiPageWikiLink Q7483213.
- Q7828122 wikiPageWikiLink Q7849419.
- Q7828122 wikiPageWikiLink Q8646998.
- Q7828122 wikiPageWikiLink Q939253.
- Q7828122 comment "In applied statistics, total least squares is a type of errors-in-variables regression, a least squares data modeling technique in which observational errors on both dependent and independent variables are taken into account. It is a generalization of Deming regression and also of orthogonal regression, and can be applied to both linear and non-linear models.".
- Q7828122 label "Total least squares".
- Q7828122 depiction Total_least_squares.svg.
