scholarly journals Pointwise convergence rates and central limit theorems for kernel density estimators in linear processes

2006 ◽  
Vol 76 (16) ◽  
pp. 1756-1760 ◽  
Author(s):  
Anton Schick ◽  
Wolfgang Wefelmeyer
2018 ◽  
Vol 95 ◽  
pp. 3-15 ◽  
Author(s):  
Vo Anh ◽  
Andriy Olenko ◽  
V. Vaskovych

2009 ◽  
Vol 25 (3) ◽  
pp. 748-763 ◽  
Author(s):  
Kairat T. Mynbaev

Standardized slowly varying regressors are shown to be Lp-approximable. This fact allows us to provide alternative proofs of asymptotic expansions of nonstochastic quantities and central limit results due to P.C.B. Phillips, under a less stringent assumption on linear processes. The recourse to stochastic calculus related to Brownian motion can be completely dispensed with.


1996 ◽  
Vol 9 (3) ◽  
pp. 233-254 ◽  
Author(s):  
Michel Harel ◽  
Madan L. Puri

In this paper, the central limit theorems for the density estimator and for the integrated square error are proved for the case when the underlying sequence of random variables is nonstationary. Applications to Markov processes and ARMA processes are provided.


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