Semiparametric lower bounds for tail index estimation

Some Lower Bounds for Estrada Index

Semiparametric Tail Index Estimation: A Density Quantile Approach

Heavy tail probability distributions are important in many scientific disciplines, such as hydrology, geology, and physics among others. To this end many heavy tail distributions are commonly used in practice. In order to determine an appropriate family of distributions for a specified application it is useful to classify the probability law via its tail behavior. Through the use of Parzen’s de...

some lower bounds for estrada index

Lower Bounds for Estimation

Lower Bounds for Estrada Index

If G is an (n,m)-graph whose spectrum consists of the numbers λ1, λ2, . . . , λn, then its Estrada index is EE(G) = ∑n i=1 e λi . We establish lower bounds for EE(G) in terms of n and m. Introduction In this paper we are concerned with simple graphs, that have no loops and no multiple or directed edges. Let G be such a graph, and let n and m be the number of its vertices and edges. Then we say ...