Sharp large deviations under Bernsteinʼs condition
نویسندگان
چکیده
منابع مشابه
Sharp Large Deviations for Gaussian Quadratic Forms with Applications
Under regularity assumptions, we establish a sharp large deviation principle for Hermitian quadratic forms of stationary Gaussian processes. Our result is similar to the well-known Bahadur-Rao theorem [2] on the sample mean. We also provide several examples of application such as the sharp large deviation properties of the Neyman-Pearson likelihood ratio test, of the sum of squares, of the Yule...
متن کاملSharp large deviations for the fractional Ornstein - Uhlenbeck process
We investigate the sharp large deviation properties of the energy and the maximum likelihood estimator for the Ornstein-Uhlenbeck process driven by a fractional Brownian motion with Hurst index greater than one half. A.M.S. Classification: 60F10, 60G15, 60J65
متن کاملSharp large deviations for the non-stationary Ornstein-Uhlenbeck process
For the Ornstein-Uhlenbeck process, the asymptotic behavior of the maximum likelihood estimator of the drift parameter is totally different in the stable, unstable, and explosive cases. Notwithstanding of this trichotomy, we investigate sharp large deviation principles for this estimator in the three situations. In the explosive case, we exhibit a very unusual rate function with a shaped flat v...
متن کاملLarge Deviations for Solutions to Stochastic Recurrence Equations under Kesten’s Condition
In this paper we prove large deviations results for partial sums constructed from the solution to a stochastic recurrence equation. We assume Kesten’s condition [17] under which the solution of the stochastic recurrence equation has a marginal distribution with power law tails, while the noise sequence of the equations can have light tails. The results of the paper are analogs of those obtained...
متن کاملEstimating Mixed Memberships with Sharp Eigenvector Deviations
We consider the problem of estimating overlapping community memberships. Existing provable algorithms for this problem either make strong assumptions about the population [33, 16], or are too computationally expensive [3, 15]. We work under the popular Mixed Membership Stochastic Blockmodel (MMSB) [2]. Using the inherent geometry of this model, we link the inference of overlapping communities t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Comptes Rendus Mathematique
سال: 2013
ISSN: 1631-073X
DOI: 10.1016/j.crma.2013.10.015