期刊
STATISTICS & PROBABILITY LETTERS
卷 81, 期 8, 页码 1039-1045出版社
ELSEVIER
DOI: 10.1016/j.spl.2011.02.026
关键词
Correlation coefficient estimate; Convergence in probability; Asymptotic normality; Mixing processes
Let {X-i, Y-i} be jointly distributed second-order random variables with correlation coefficient r. The estimation of r from the observations {X-i, Y-i}(i=1)(n) is a classical problem which has been examined under the assumption of an i.i.d. setting. In this paper we examine the statistical properties of the correlation coefficient estimate when the process (X-i, Y-i) is dependent, constituting either a strongly mixing process or asymptotically uncorrelated. We establish convergence in probability (with rates) as well as asymptotic normality for the estimation error and present an explicit expression for the asymptotic variance. Published by Elsevier B.V.
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