AU - Jabbari Nooghabi, H.
TI - Almost Sure Convergence of Kernel Bivariate Distribution Function Estimator under Negative Association
PT - JOURNAL ARTICLE
TA - srtc-jsri
JN - srtc-jsri
VO - 6
VI - 2
IP - 2
4099 - http://jsri.srtc.ac.ir/article-1-113-en.html
4100 - http://jsri.srtc.ac.ir/article-1-113-en.pdf
SO - srtc-jsri 2
ABĀ - Let {Xn ,n=>1} be a strictly stationary sequence of negatively associated random variables, with common distribution function F. In this paper, we consider the estimation of the two-dimensional distribution function of (X1, Xk+1) for fixed $K /in N$ based on kernel type estimators. We introduce asymptotic normality and properties and moments. From these we derive the optimal bandwidth convergence rate, which is of order n-1. Besides of some usual conditions on the kernel function, the conditions typically impose a convenient increase rate on the covariances cov(X1,Xn).
CP - IRAN
IN -
LG - eng
PB - srtc-jsri
PG - 243
PT - Research
YR - 2010