A central limit theorem for mixing random fields and its statistical applications. (English) Zbl 1023.60030
Berkes, I. (ed.) et al., Limit theorems in probability and statistics. Fourth Hungarian colloquium on limit theorems in probability and statistics, Balatonlelle, Hungary, June 28-July 2, 1999. Vol. II. Budapest: János Bolyai Mathematical Society. 59-75 (2002).
Summary: A central limit theorem is proved for mixing random fields. The theorem covers the case when the locations of the observations become dense in a sequence of increasing domains. This theorem is used to prove asymptotic normality of the least squares estimator in linear models if the observations are of the above type.
For the entire collection see [Zbl 1009.00023].
For the entire collection see [Zbl 1009.00023].
