Open Access Open Access  Restricted Access Subscription or Fee Access

A comparison of the rates of convergence for extremes under nonlinear normalization

Bouchra Labloul, Mohammadine Belbachir, Saad el Ouardirhi

Abstract



We use the total variation distance between discrete random variables to evaluate the rate of convergence of Xn􀀀k+1;n, suitably normalised by the exponential normalization introduced by (Ravi and Mavitha, 2016) to its limit. Some examples are given for comparing the rates of convergence illustrate this result and that of (Barakat, HM, Nigm, EM and El-Adll, 2010)

Keywords


Total variation distance, distributions power, exponential norming.

Full Text:

PDF


Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.