Deconvolution based score tests in measurement error models /

Deconvolution based score tests in measurement error models /

Consider a generalized linear model with response Y and scalar predictor X. Instead of observing X, a surrogate W = X + Z is observed, where Z represents measurement error and is independent of X and Y. The efficient score test for the absence of association depends on m(w) = E(X l W = w) which is g...

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Bibliographic Details
Main Authors: Stefanski, Leonard A. (Author), Carroll, Raymond J. (Author)
Corporate Authors: National Science Foundation (U.S.) (sponsoring body.), National Institutes of Health (U.S.) (sponsoring body.)
Format: Book
Language:English
Published: College Station, Texas : Department of Statistics, Texas A & M University, [1989]
Series:Technical report (Texas A & M University. Department of Statistics) ; no. 78.
Subjects:
Errors-in-variables models.
Linear models (Statistics)
Convolutions (Mathematics)
Nonparametric statistics.
Estimation theory.
Mathematical statistics.
Statistics > Nonparametric inference > Density estimation.
Measurement error models
Deconvolution
Generalized linear models
Maximum likelihood
Score tests

Cushing: Texas A&M Publications (Remote Storage: 2-3 day retrieval)

Holdings details from Cushing: Texas A&M Publications (Remote Storage: 2-3 day retrieval)
Call Number: QA276.A12 T4 no.78
 
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