least squares

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least squares

(lēst skwārz),
A principle of estimation invented by Gauss in which the estimates of a set of parameters in a statistical model are the quantities that minimize the sum of squared differences between the observed values of the dependent variable and the values predicted by the model.

least squares

a method of regression analysis. The line on a graph that best summarizes the relationship between two variables is the one that ensures that there is the least value of the sum of the squares of the deviation between the fitted curve and each of the original data points.
References in periodicals archive ?
The predictor which yields the smallest sum of squared errors is chosen as the predictor for the entire signal at a given scale.
The statistics cited are the sum of squared errors, the mean squared errors, the root mean squared errors (RMSE) and the bias (sum of prediction minus outcome).
The sum of squared errors of the Administration's real output growth forecasts is largest for Canada, the United States and West Germany.
The sum of squared errors is largest for Italy and the United Kingdom.
2~,(6) since the Lotus 1-2-3 output does not include sum of squared errors, and use it to determine how much weight to assign to each regression.