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Interval Estimation in Linear Regression When Both Variables are Subject to Error

 

作者: Max Halperin,  

 

期刊: Journal of the American Statistical Association  (Taylor Available online 1964)
卷期: Volume 59, issue 308  

页码: 1112-1120

 

ISSN:0162-1459

 

年代: 1964

 

DOI:10.1080/01621459.1964.10480752

 

出版商: Taylor & Francis Group

 

数据来源: Taylor

 

摘要:

Define the linear functional relationship with parameters, α, β, by μ = α + βv. This paper considers the problem of confidence interval estimation of α and β separately, based on a sample of independent pairs, (xi,yi),i= 1, 2, ···,n, withExi= vi,Eyi= μi. The pairs, (xi,yi), are assumed to be independent (i≠i′), to have a common (unknown) covariance matrix Σ, and to follow the bivariate normal distribution. It is known that under these circumstances (providing instrumental variates are available) one can define a variance ratio with 2 and (n− 2) degrees of freedom,F2,n–2say, as a function of α, β, sample statistics and instrumental variates to yield a confidence region on (α, β) based on

 

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