Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1153858 | Statistical Methodology | 2009 | 9 Pages |
Abstract
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 ppth-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.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
S.Y. Hwang, I.V. Basawa, I.K. Yeo,