scholarly journals Necessary and sufficient conditions for the conditional central limit theorem

2002 ◽  
Vol 30 (3) ◽  
pp. 1044-1081 ◽  
Author(s):  
Jérôme Dedecker ◽  
Florence Merlevède
1999 ◽  
Vol 36 (4) ◽  
pp. 974-986 ◽  
Author(s):  
Bruno Tuffin

In this paper, we give necessary and sufficient conditions to ensure the validity of confidence intervals, based on the central limit theorem, in simulations of highly reliable Markovian systems. We resort to simulations because of the frequently huge state space in practical systems. So far the literature has focused on the property of bounded relative error. In this paper we focus on ‘bounded normal approximation’ which asserts that the approximation of the normal law, suggested by the central limit theorem, does not deteriorate as the reliability of the system increases. Here we see that the set of systems with bounded normal approximation is (strictly) included in the set of systems with bounded relative error.


1976 ◽  
Vol 13 (04) ◽  
pp. 809-813
Author(s):  
Holger Rootzén

In this note, necessary and sufficient conditions for the central limit theorem for the number of events in a doubly stochastic Poisson process are given.


1978 ◽  
Vol 25 (2) ◽  
pp. 250-256 ◽  
Author(s):  
Peter Hall

AbstractAn early extension of Lindeberg's central limit theorem was Bernstein's (1939) discovery of necessary and sufficient conditions for the convergence of moments in the central limit theorem. Von Bahr (1965) made a study of some asymptotic expansions in the central limit theorem, and obtained rates of convergence for moments. However, his results do not in general imply that the moments converge. Some better rates have been obtained by Bhattacharya and Rao for moments between the second and third. In this paper we give improved rates of convergence for absolute moments between the third and fourth.


2011 ◽  
Vol 11 (01) ◽  
pp. 71-80 ◽  
Author(s):  
DALIBOR VOLNÝ ◽  
MICHAEL WOODROOFE ◽  
OU ZHAO

The Central Limit Theorem is studied for stationary sequences that are sums of countable collections of linear processes. Two sets of sufficient conditions are obtained. One restricts only the coefficients and is shown to be best possible among such conditions. The other involves an interplay between the coefficients and the distribution functions of the innovations and is shown to be necessary for the Conditional Central Limit Theorem in the case of a causal process with independent innovations.


1976 ◽  
Vol 13 (4) ◽  
pp. 809-813 ◽  
Author(s):  
Holger Rootzén

In this note, necessary and sufficient conditions for the central limit theorem for the number of events in a doubly stochastic Poisson process are given.


Sign in / Sign up

Export Citation Format

Share Document