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.
References in periodicals archive ?
Application of the method of least squares for subordinating the solution to non-homogeneous boundary conditions prescribed on the part of the boundary reduces the problems to corresponding problems of nonconstrained optimization.
As pointed out in Sarkar's tutorial paper [30] which compared the method of least squares with Galerkin's method, our LSBRM model requires significantly more computational resources.
2) Determine the final group decision making comparison matrix revised by the method of Least squares according to the step 4.
Substituting the relations for the method of least squares:
Using the method of least squares, parameters [a.sub.0], [a.sub.1], [a.sub.2], [a.sub.3], [a.sub.4] are determined and are subsequently substituted into formula (5).
The statistically best-fit straight line is usually determined by applying the method of least squares to a series of calibration readings.
Nielsen, Evaluation of measurement intercomparisons by the method of least squares, Report DFM-99-R39, 3208 LN, Danish Institute of Fundamental Metrology, Lyngby, Denmark (2000).
The method of least squares is built on the hypothesis that the optimum description of a set of data is one that minimizes the weighted sum of squares of deviation of the data from the fitting function.
Method of least squares Method that focuses on the random variable Y in regression analysis and minimizes the sum of squared deviations in the Y direction about the regression line; used to obtain estimates of the regression parameters if and b, the intercept and slope coefficients for the equation for the line.
The method of least squares gives a good linear fit: RA = 1.285x (Solar longitude) - 131.56 r = 0.937
In this study the method of least squares will allow a closer recognition of energy in the particular tidal bands.
Using a Maple application, based on the method of least squares we obtained different graphics and approximation models.

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