The Annals of Statistics

Asymptotic Efficient Estimation of the Change Point with Unknown Distributions

Y. Ritov

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Abstract

Suppose $X_1,\cdots, X_n$ are distributed according to a probability measure under which $X_1,\cdots, X_n$ are independent, $X_1 \sim F_0$, for $i = 1,\cdots, \lbrack\theta_n n\rbrack$ and $X_i \sim F^{(n)}$ for $i = \lbrack\theta_nn\rbrack + 1, \cdots, n$ where $\lbrack x\rbrack$ denotes the integer part of $x$. In this paper we consider the asymptotic efficient estimation of $\theta_n$ when the distributions are not known. Our estimator is efficient in the sense that if $F^{(n)} = F_{\eta_n}, \eta_n \rightarrow 0$ and $\{F_\eta\}$ is a regular one-dimensional parametric family of distributions, then the estimator is asymptotically equivalent to the best regular estimator.

Article information

Source
Ann. Statist., Volume 18, Number 4 (1990), 1829-1839.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176347881

Digital Object Identifier
doi:10.1214/aos/1176347881

Mathematical Reviews number (MathSciNet)
MR1074438

Zentralblatt MATH identifier
0714.62027

JSTOR
links.jstor.org

Subjects
Primary: 62G05: Estimation
Secondary: 62G20: Asymptotic properties

Keywords
Asymptotic efficiency limit of experiments regular estimator

Citation

Ritov, Y. Asymptotic Efficient Estimation of the Change Point with Unknown Distributions. Ann. Statist. 18 (1990), no. 4, 1829--1839. doi:10.1214/aos/1176347881. https://projecteuclid.org/euclid.aos/1176347881


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