Results 161 to 170 of about 430,573 (198)

Second‐order inference for generalized least squares

Canadian Journal of Statistics, 1987
AbstractConfidence regions for generalized least squares are commonly derived from a measure of departure calculated on the tangent plane at the MLE or on the tangent plane at the true value; the first gives approximate confidence regions, the second exact.
Fraser, D. A. S., Massam, H.
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Feasible Generalized Least Squares Estimation

1984
There are instances in econometric modeling when an investigator is willing to specify the structure of the error variance-covariance matrix, Ω, of a generalized least squares model up to a few unknown parameters, say θl θ2,..., θp. This would occur, for example, when correlation in the errors of a time series regression model is suspected or when ...
Thomas B. Fomby, Stanley R. Johnson, R. Carter Hill   +2 more
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Generalized Least Squares

Technometrics, 2005
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Alternating Least Squares in Generalized Linear Models

Journal of Contemporary Mathematical Analysis (Armenian Academy of Sciences), 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Solving Generalized Least-Squares Problems with LSQR

SIAM Journal on Matrix Analysis and Applications, 1999
An iterative method, referred as \(\text{LSQR}(A^{-1})\), for solving augmented linear systems in generalized least squares sense is given. It is shown that the new method is a natural extension of the LSQR algorithm. Numerical experiments comparing the \(\text{LSQR}(A^{-1})\) method with the preconditioned Krylov method are considered, too.
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Integrative oncology: Addressing the global challenges of cancer prevention and treatment

Ca-A Cancer Journal for Clinicians, 2022
Jun J Mao,, Msce, Lorenzo Cohen, Karen M Mustian   +2 more
exaly  

WLS and Generalized Least Squares

2017
The concepts of a random vector, the expected value of a random vector, and the covariance of a random vector are needed before covering generalized least squares. Recall that for random variables Y i and Y j , the covariance of Y i and Y j is Cov(Y i , Y j ) ≡ σ i, j = E[(Y i −E(Y i ))(Y j −E(Y j )] = E(Y i Y j ) −E(Y i )E(Y j )provided the second ...
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Generalized Least Squares

1977
ERIC A. HANUSHEK, JOHN E. JACKSON
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Obesity and adverse breast cancer risk and outcome: Mechanistic insights and strategies for intervention

Ca-A Cancer Journal for Clinicians, 2017
Cynthia Morata-Tarifa, Joyce M Slingerland   +1 more
exaly  

Multidisciplinary standards of care and recent progress in pancreatic ductal adenocarcinoma

Ca-A Cancer Journal for Clinicians, 2020
Aaron J Grossberg, William L Hwang, Anirban Maitra   +2 more
exaly