A finite collection of random variables, X<sub>1</sub>,…, X<sub>n</sub> （n≥2）, is said to be negatively associated （NA） if any two coordinatewise nondecreasing （or nonincreasing） functi...A finite collection of random variables, X<sub>1</sub>,…, X<sub>n</sub> （n≥2）, is said to be negatively associated （NA） if any two coordinatewise nondecreasing （or nonincreasing） functions f<sub>1</sub> and f<sub>2</sub> on R<sup>n</sup>, such that （?）<sub>j</sub>=f<sub>j</sub>（X<sub>1</sub>,…,X<sub>n</sub>） have a finite variance for j=1, 2 and Cov（（?）<sub>1</sub>,（?）<sub>2</sub>）≤0; an infinite collection is said to be NA if every finite subcollection is NA. It is relative to a lot of practical problems, such as reliability theory, percolation models and multivariate statistical analysis. Matula （1992） studied the strong laws of large numbers for an NA sequence. Recent-展开更多
文摘A finite collection of random variables, X<sub>1</sub>,…, X<sub>n</sub> （n≥2）, is said to be negatively associated （NA） if any two coordinatewise nondecreasing （or nonincreasing） functions f<sub>1</sub> and f<sub>2</sub> on R<sup>n</sup>, such that （?）<sub>j</sub>=f<sub>j</sub>（X<sub>1</sub>,…,X<sub>n</sub>） have a finite variance for j=1, 2 and Cov（（?）<sub>1</sub>,（?）<sub>2</sub>）≤0; an infinite collection is said to be NA if every finite subcollection is NA. It is relative to a lot of practical problems, such as reliability theory, percolation models and multivariate statistical analysis. Matula （1992） studied the strong laws of large numbers for an NA sequence. Recent-
