Let {X <Subscript> n </Subscript>,n≥1} be a strictly stationary sequence of negatively associated random variables with the marginal probability density function f(x), the recursive kernel estimate of f(x) is defined by [InlineMediaObject not available: see fulltext.] where h <Subscript> n </Subscript> is a sequence of positive bandwidths...</subscript></subscript>

A central limit theorem is obtained for a stationary linear process of the form Xt=[summation operator]j=0[infinity]aj[var epsilon]t-j, where {[var epsilon]t} is a strictly stationary sequence of linearly positive quadrant dependent random variables with E[var epsilon]t=0, E[var epsilon]ts<[infinity] for some s>2, and...</[infinity]>