Erratum to: General Bahr-Esseen inequalities and their applications
نویسندگان
چکیده
*Correspondence: [email protected] Faculty of Informatics, University of Debrecen, P.O. Box 400, Debrecen, 4002, Hungary 1 Erratum In the publication of this article [], there were two errors. ) The error in Section . Exponential inequalities and their consequences: ‘(a)X(b) = –aI{X < a} +XIa≤ |X| ≤ b + bI{X > b}.’ Should instead read: ‘(a)X(b) = aI{X < a} +XIa≤ X ≤ b + bI{X > b}.’ ) The error in Section . Convergence theorems: ‘A well-knownWLLN for pairwise independent r.v.s is the result of Csörgő, Tandori, and Totik [].’ Should instead read: ‘A well-known SLLN for pairwise independent r.v.s is the result of Csörgő, Tandori, and Totik [].’ This has now been updated in the original article [].
منابع مشابه
General Bahr-Esseen inequalities and their applications
We study the Bahr-Esseen inequality. We show that the Bahr-Esseen inequality holds with exponent p if it holds with exponent [Formula: see text] for the truncated and centered random variables. The Bahr-Esseen inequality is also true if the truncated random variables are acceptable. We then apply the results to obtain weak and strong laws of large numbers and complete convergence.
متن کاملNew Jensen and Ostrowski Type Inequalities for General Lebesgue Integral with Applications
Some new inequalities related to Jensen and Ostrowski inequalities for general Lebesgue integral are obtained. Applications for $f$-divergence measure are provided as well.
متن کاملErratum: Applications of epi-retractable and co-epi-retractable modules
In this errata, we reconsider and modify two propositions and their corollaries which were written on epi-retractable and co-epi-retractable modules.
متن کاملBerry-Esseen bounds of weighted kernel estimator for a nonparametric regression model based on linear process errors under a LNQD sequence
In this paper, the authors investigate the Berry-Esseen bounds of weighted kernel estimator for a nonparametric regression model based on linear process errors under a LNQD random variable sequence. The rate of the normal approximation is shown as [Formula: see text] under some appropriate conditions. The results obtained in the article generalize or improve the corresponding ones for mixing de...
متن کاملA Berry-Esseen type bound for the kernel density estimator based on a weakly dependent and randomly left truncated data
In many applications, the available data come from a sampling scheme that causes loss of information in terms of left truncation. In some cases, in addition to left truncation, the data are weakly dependent. In this paper we are interested in deriving the asymptotic normality as well as a Berry-Esseen type bound for the kernel density estimator of left truncated and weakly dependent data.
متن کاملذخیره 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 ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
دوره 2017 شماره
صفحات -
تاریخ انتشار 2017