The Annals of Statistics

The Asymptotic Effect of Substituting Estimators for Parameters in Certain Types of Statistics

Donald A. Pierce

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Abstract

In a variety of statistical problems, one is interested in the limiting distribution of statistics $\hat{T}_n = T_n(y_1, y_2, \cdots, y_n; \hat{\lambda}_n)$, where $\hat{\lambda}_n$ is an estimator of a parameter in the distribution of the $y_i$ and where the limiting distribution of $T_n = T_n(y_1, y_2, \cdots, y_n; \lambda)$ is relatively easy to find. For cases in which the limiting distribution of $T_n$ is normal with mean independent of $\lambda$, a useful method is given for finding the limiting distribution of $\hat{T}_n$. A simple application to testing normality in regression models is given.

Article information

Source
Ann. Statist., Volume 10, Number 2 (1982), 475-478.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176345788

Digital Object Identifier
doi:10.1214/aos/1176345788

Mathematical Reviews number (MathSciNet)
MR653522

Zentralblatt MATH identifier
0488.62012

JSTOR
links.jstor.org

Subjects
Primary: 62E20: Asymptotic distribution theory
Secondary: 62F05: Asymptotic properties of tests

Keywords
Asymptotic distributions goodness-of-fit tests nuisance parameters residuals

Citation

Pierce, Donald A. The Asymptotic Effect of Substituting Estimators for Parameters in Certain Types of Statistics. Ann. Statist. 10 (1982), no. 2, 475--478. doi:10.1214/aos/1176345788. https://projecteuclid.org/euclid.aos/1176345788


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