On the Bennett-Hoeffding inequality

نویسنده

  • Iosif Pinelis
چکیده

The well-known Bennett-Hoeffding bound for sums of independent random variables is refined, by taking into account positive-part third moments, and at that significantly improved by using, instead of the class of all increasing exponential functions, a much larger class of generalized moment functions. The resulting bounds have certain optimality properties. The results can be extended in a standard manner to (the maximal functions of) (super)martingales. The proof of the main result relies on an apparently new method that may be referred to as infinitesimal spin-off. AMS 2000 subject classifications: Primary 60E15, 60G50; secondary 60E07, 60E10, 60G42, 60G48, 60G51.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Hoeffding-type Inequality for Ergodic Time Series

In this paper, a Hoeffding-type inequality is presented for a class of ergodic time series. The inequality is then used to construct uniformly exponentially consistent tests, which are useful tools for studying Bayesian consistency.

متن کامل

Optimal Bounds on Tail Probabilities: a Study of an Approach

In Computer Science and Statistics it is often desirable to obtain tight bounds on the decay rate of probabilities of the type Pr{Sn−E[Sn] ≥ na}, where Sn is a sum of independent random variables {Xi}i=1. This is usually done by means of Chernoff inequality, or the more general Hoeffding inequality. The latter inequality is asymptotically optimal as far as the expectations of Xi-s go, but cease...

متن کامل

Generalization Bounds for Representative Domain Adaptation

In this paper, we propose a novel framework to analyze the theoretical properties of thelearning process for a representative type of domain adaptation, which combines data frommultiple sources and one target (or briefly called representative domain adaptation). Inparticular, we use the integral probability metric to measure the difference between the dis-tributions of two d...

متن کامل

Concentration Inequalities

1.1. Azuma-Hoeffding Inequality. Concentration inequalities are inequalities that bound probabilities of deviations by a random variable from its mean or median. Our interest will be in concentration inequalities in which the deviation probabilities decay exponentially or superexponentially in the distance from the mean. One of the most basic such inequality is the Azuma-Hoeffding inequality fo...

متن کامل

Correcting the Usage of the Hoeffding Inequality in Stream Mining

Many stream classification algorithms use the Hoeffding Inequality [6] to identify the best split attribute during tree induction. We show that the prerequisites of the Inequality are violated by these algorithms, and we propose corrective steps. The new stream classification core, correctedVFDT, satisfies the prerequisites of the Hoeffding Inequality and thus provides the expected performance ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009