Results 231 to 240 of about 553,645 (265)
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2009
The method of least squares controls the flow of errors via the elements of the design matrix. Hence, assuming linear systems with differing design matrices aiming at the same set of unknowns, the adjustment’s uncertainties would differ even if the uncertainties of the input data were the same.
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The method of least squares controls the flow of errors via the elements of the design matrix. Hence, assuming linear systems with differing design matrices aiming at the same set of unknowns, the adjustment’s uncertainties would differ even if the uncertainties of the input data were the same.
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Least Squares Sign-Solvability
SIAM Journal on Matrix Analysis and Applications, 1995The author constructs a family of least squares sign-solvable linear systems from the vertex-incidence matrices of trees, and develops their general properties. The structure of a least squares sign-solvable system is shown to be analogous to that of sign-solvable linear systems.
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1981
In the next three chapters we shall discuss a particular form of statistical model, which gives rise to simple statistical methods of very wide applicability. The basic model has been mentioned in Section 2.1, Equation (2.2), see also Example 3.12, but the following example illustrates how it arises in practice.
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In the next three chapters we shall discuss a particular form of statistical model, which gives rise to simple statistical methods of very wide applicability. The basic model has been mentioned in Section 2.1, Equation (2.2), see also Example 3.12, but the following example illustrates how it arises in practice.
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Review of Ordinary Least Squares and Generalized Least Squares
1984The purpose of this chapter is to review the fundamentals of ordinary least squares and generalized least squares in the context of linear regression analysis. The presentation here is somewhat condensed given our objective of focusing on more advanced topics in econometrics.
Thomas B. Fomby +2 more
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Least squares parameter estimation
Automatica, 1979Abstract This article demonstrates the application of least squares for the estimation of system parameters. Analytic as well as numerical approaches are described. The model of the system dynamics is assumed in the form of regression model. Solutions are discussed for the case of white noise and correlated noise corrupting the useful output signal ...
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An Algorithm for Least Squares
Journal of Mathematics and Physics, 1947Nielsen, K. L., Goldstein, L.
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