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 ?
This task can be accomplished by least squares method using the extended observation equation
Recursive least squares method originates from the least squares method.
When we choose to use the least squares method, it is very important to consider the way how the residual variable (error) is included into model (in the sense that, in some variants, linearization is prevented exactly by the multiplicative or additive way in which the error is included).
So when prior knowledge where the change occur is not available then recursive least square and recursive residual test is used.
Least squares mean annual wool yield indicated that males produced 0.
Before calculation of the phenotypic trend, a preliminary statistical analysis was carried out for the data to determine the significant non-genetic factors, such as calving seasons and parities by least square technique using the general linear model procedure of Harvey (1987).
The Recursive Identification Algorithm Library is designed for recursive parameter estimation of linear dynamics model ARX, ARMAX, OE using recursive identification methods: Least Square Method (RLS), Recursive Leaky Incremental Estimation (RLIE), Damped Least Squares (DLS), Adaptive Control with Selective Memory (ACSM), Instrumental Variable Method (RIV), Extended Least Square Method (RELS), Prediction Error Method (RPEM) and Extended Instrumental Variable Method (ERIV).
0], which corresponds to a least squares solution ([[?
The second estimation procedure was the Two Stage Least Squares simultaneous equation method, using pooled cross-sectional (50 states and the District of Columbia) and quarterly time series data for the period 1980-2003.
Consider the recursive least squares minimization using adaptive linear combiner[2].

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