Complete f-moment convergence for arrays of random variables
and its applications in semiparametric
and EV regression models
Yongping He
Yan Shen
Rui Wang
Xuejun Wang
Abstract:
We study the complete f-moment convergence for arrays of
rowwise random variables satisfying a Rosenthal type moment inequality,
and then establish general results on the complete moment convergence
and complete convergence for partial sums and weighted sums of arrays of
rowwise random variables. As applications, we further describe the
statistical properties of complete f-moment convergence in both
semiparametric regression models and simple linear errors-in-variables
models. The asymptotic properties for estimators are established. We
also provide some simulations to verify the validity of the theoretical
results.
2010 AMS Mathematics Subject Classification: Primary 60F15; Secondary 62F12, 62G20.
Keywords and phrases: complete convergence, complete f-moment convergence,
strong consistency, semiparametric regression models, simple linear errors-in-variables models.