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Local asymptotic normality for bifurcating autoregressive processes and related asymptotic inference
- Hwang S.Y.;
- Basawa I.V.;
- Yeo I.K.
Citations
SCOPUS
8초록
This article is concerned with the local asymptotic normality (LAN) of the log-likelihood for the bifurcating autoregressive model (BAR) for tree structured data where each individual in one generation gives rise to two off-spring in the next generation. We derive the LAN property for the pth-order BAR model. Asymptotic optimal inference for the model parameters can be deduced as a consequence of LAN. In particular, an efficient score test is derived as an application. A simulation study is conducted to address the issue regarding how many generations are required for asymptotic results to be useful in practice. © 2008 Elsevier B.V. All rights reserved.
키워드
Bifurcating model; LAN; Martingale array; Maximum likelihood; Score test
- 제목
- Local asymptotic normality for bifurcating autoregressive processes and related asymptotic inference
- 저자
- Hwang S.Y.; Basawa I.V.; Yeo I.K.
- 발행일
- 2009-01
- 유형
- Article
- 권
- 6
- 호
- 1
- 페이지
- 61 ~ 69