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least-squares method

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least-squares method

[¦lēst ′skwerz ‚meth·əd]
(statistics)
A technique of fitting a curve close to some given points which minimizes the sum of the squares of the deviations of the given points from the curve.
McGraw-Hill Dictionary of Scientific & Technical Terms, 6E, Copyright © 2003 by The McGraw-Hill Companies, Inc.
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References in periodicals archive
population density, average household size and female literacy were found to be statistically significant in the ordinary least squares regression model.
In the present study, the variance inflation factors obtained using the Least Squares method were very high, whereas those resulting from Ridge Regression and Principal Components Regression were very low.
In the same way, the optimal weighting least squares estimation for the load inertia with one plus m sets of observation data can be expressed in
To find the equation of the line of best fit in the least squares sense to the data, y = a + bx, we must find values of a, b that minimise the sum of the squares of the residuals which we can express as:
The ordinary least squares regression equation of Y is obtained by the REG procedure of SAS program.
In order to determine the geoid using the KTH method, free-air gravity anomalies (Krynski, 2007) were interpolated by the least squares prediction method on 1.5' x 3.0' grid nodes for the area 47[degrees] < [phi] <57[degrees] and 11[degrees] < [lambda] <27[degrees] (Fig.
To apply the least squares principle, we reformulate the Stokes-Darcy equations as a first-order system derived in terms of an additional vector variable (the vector of gradients of the Stokes velocities).
Keywords: Linear models Ordinary least square Method Recursive Test
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