Residual Sum Of Squares
In statistics, the residual sum of squares (RSS) is the sum of squares of residuals. It is also known as the sum of squared residuals (SSR) or the sum of squared errors of prediction (SSE). It 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.
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.
Read more about Residual Sum Of Squares: One Explanatory Variable, Matrix Expression For The OLS Residual Sum of Squares
Famous quotes containing the words residual, sum and/or squares:
“The volatile truth of our words should continually betray the inadequacy of the residual statement. Their truth is instantly translated; its literal monument alone remains.”
—Henry David Thoreau (1817–1862)
“Never is a historic deed already completed when it is done but always only when it is handed down to posterity. What we call “history” by no means represents the sum total of all significant deeds.... World history ... only comprises that tiny lighted sector which chanced to be placed in the spotlight by poetic or scholarly depictions.”
—Stefan Zweig (18811942)
“And New York is the most beautiful city in the world? It is not far from it. No urban night is like the night there.... Squares after squares of flame, set up and cut into the aether. Here is our poetry, for we have pulled down the stars to our will.”
—Ezra Pound (1885–1972)