Resumen de Strong laws for weighted sums of ψ-mixing random variables and applications in errors-in-variables regression models
Di Hu, Pingyan Chen, Soo Hak Sung
In this paper, we establish strong laws for weighted sums of identically distributed ψ-mixing random variables without any conditions on mixing rate. The classical Kolmogorov strong law of large numbers is extended to weighted sums of ψ-mixing random variables. Two types of weights are considered for the weighted sums. These results are applied to the least-squares estimators in the simple linear errors-in-variables regression model when the errors are ψ-mixing random vectors.
