<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The paper deals with independent sequences with continuous asymptotic distribution functions. We construct a compact metric space with Borel probability measure. We use its properties to prove the central limit theorem for independent sequences with continuous distribution functions.</p></abstract>

The paper deals with independent sequences with continuous asymptotic distribution functions. We construct a compact metric space with Borel probability measure. We use its properties to prove the central limit theorem for independent sequences with continuous distribution functions.

Central Limit Theorem and the Distribution of Sequences

Department of Mathematics and Informatics Faculty of Education University of Trnava

Institute of Mathematics Slovak Academy of Sciences Bratislava

Tatra Mountains Mathematical Publications

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Central Limit Theorem and the Distribution of Sequences"}

The paper deals with independent sequences with continuous asymptotic distribution functions. We construct a compact metric space with Borel probability...

Central Limit Theorem and the Distribution of Sequences

Online veröffentlicht: 31. Dez. 2020

Seitenbereich: 43 - 52

Eingereicht: 14. Apr. 2020

DOI: https://doi.org/10.2478/tmmp-2020-0031

Schlüsselwörter
asymptotic density, distribution function, probability, measure density

© 2020 Milan Paštéka, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Central Limit Theorem and the Distribution of Sequences

Online veröffentlicht: 31. Dez. 2020

Seitenbereich: 43 - 52

Eingereicht: 14. Apr. 2020

DOI: https://doi.org/10.2478/tmmp-2020-0031

Schlüsselwörterasymptotic density, distribution function, probability, measure density

© 2020 Milan Paštéka, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
asymptotic density, distribution function, probability, measure density