The Features of the Statistic Counting Model for Its Application to Estimate the Probability

DOI

10.2991/meici-16.2016.94How to use a DOI?

Keywords

Statistic counting model; Description length; Probability estimation

Abstract

The statistic method is widely used to analyze the statistic features hiding behind the various data. Some famous algorithms such as Ls, LMS are based on the statistic models. Actually on the basis of the description length theory, the statistic model can be considered as the judgment system which should hold different description complexity. It implies that the corresponding features of the statistic model under description length theory are different from these characters under the numerical area. In this paper, three basic features of statistic model are discussed under the minimum description length criterion. They are description complexity, similarity measure and the adding criterion. The corresponding derivations and the discussions are also given. These features can help increasing the efficiency of the estimation of the probability distributions.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - BaiYun Yang
PY  - 2016/09
DA  - 2016/09
TI  - The Features of the Statistic Counting Model for Its Application to Estimate the Probability
BT  - Proceedings of the 2016 6th International Conference on Management, Education, Information and Control (MEICI 2016)
PB  - Atlantis Press
SP  - 450
EP  - 454
SN  - 1951-6851
UR  - https://doi.org/10.2991/meici-16.2016.94
DO  - 10.2991/meici-16.2016.94
ID  - Yang2016/09
ER  -