Open Access
Translator Disclaimer
2014 Large deviations for weighted sums of stretched exponential random variables
Nina Gantert, Kavita Ramanan, Franz Rembart
Author Affiliations +
Electron. Commun. Probab. 19: 1-14 (2014). DOI: 10.1214/ECP.v19-3266


We consider the probability that a weighted sum of n i.i.d. random variables $X_j, j = 1,\ldots,n$, with stretched exponential tails is larger than its expectation and determine the rate of its decay, under suitable conditions on the weights. We show that the decay is subexponential, and identify the rate function in terms of the tails of $X_j$ and the weights. Our result generalizes the large deviation principle given by Kiesel and Stadtmüller as well as the tail asymptotics for sums of i.i.d. random variables provided by Nagaev. As an application of our result, motivated by random projections of high-dimensional vectors, we consider the case of random, self-normalized weights that are independent of the sequence $X_j$, identify the decay rate for both the quenched and annealed large deviations in this case, and show that they coincide. As another example we consider weights derived from kernel functions that arise in nonparametric regression.


Download Citation

Nina Gantert. Kavita Ramanan. Franz Rembart. "Large deviations for weighted sums of stretched exponential random variables." Electron. Commun. Probab. 19 1 - 14, 2014.


Accepted: 12 July 2014; Published: 2014
First available in Project Euclid: 7 June 2016

zbMATH: 1314.60076
MathSciNet: MR3233203
Digital Object Identifier: 10.1214/ECP.v19-3266

Primary: 60F10
Secondary: 62G32

Keywords: kernels , large deviations , Nonparametric regression , quenched and annealed large deviations , random projections , self-normalized weights , subexponential random variables , weighted sums


Back to Top