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Residual Sum of Squares
Residual Sum of Squares

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!!! Overview
[{$pagename}] ([RSS]) (also called [Sum of Squared Errors]) is the sum of the squares of residuals (deviations predicted from actual empirical values of data).
[{$pagename}] is a measure of the discrepancy between the [data] and an estimation model. A small RSS indicates a tight fit of the model to the data.
[{$pagename}] is used as an optimality criterion in parameter selection and model selection.
In general, total sum of squares = explained sum of squares + residual sum of squares. For a proof of this in the multivariate [Ordinary Least Squares] ([OLS]) case, see partitioning in the general [OLS] model.
!! More Information
There might be more information for this subject on one of the following:
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* [#1] - [Residual_sum_of_squares|Wikipedia:Residual_sum_of_squares|target='_blank'] - based on information obtained 2018-01-03-
This page (revision-1) was last changed on 29-Nov-2024 16:16 by UnknownAuthorTop