content_image/309544.jpg content_image/309543.jpg content_image/309542.jpg content_image/309541.jpg
distributions 

<img src='content_image/309544.jpg'>

where ˆ F denotes the empirical cumulative distribution function based on N sample points. 

By the Glivenko-Cantelli theorem, uniformly almost surely, 

<img src='content_image/309543.jpg'>

Therefore, by Slutsky’s theorem and the continuous mapping theorem, we have that uniformly almost surely 

where the inequality follows from the fact that e$_{C}$ N ≤ 1. 

<img src='content_image/309542.jpg'>

We shall show that the limit (A.14) can be bounded from below by a positive constant that depends on ( x$_{0}$, y$_{0}$ ) and R but not on I . Since 

<img src='content_image/309541.jpg'>

