# A probability density function estimation using F-transform

Kybernetika (2010)

- Volume: 46, Issue: 3, page 447-458
- ISSN: 0023-5954

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topHolčapek, Michal, and Tichý, Tomaš. "A probability density function estimation using F-transform." Kybernetika 46.3 (2010): 447-458. <http://eudml.org/doc/196338>.

@article{Holčapek2010,

abstract = {The aim of this paper is to propose a new approach to probability density function (PDF) estimation which is based on the fuzzy transform (F-transform) introduced by Perfilieva in [10]. Firstly, a smoothing filter based on the combination of the discrete direct and continuous inverse F-transform is introduced and some of the basic properties are investigated. Next, an alternative approach to PDF estimation based on the proposed smoothing filter is established and compared with the most used method of Parzen windows. Such an approach can be of a great value mainly when dealing with financial data, i. e. large samples of observations.},

author = {Holčapek, Michal, Tichý, Tomaš},

journal = {Kybernetika},

keywords = {fuzzy transform; probability density function estimation; smoothing filter; financial returns; fuzzy transform; probability density function estimation; smoothing filter; financial returns},

language = {eng},

number = {3},

pages = {447-458},

publisher = {Institute of Information Theory and Automation AS CR},

title = {A probability density function estimation using F-transform},

url = {http://eudml.org/doc/196338},

volume = {46},

year = {2010},

}

TY - JOUR

AU - Holčapek, Michal

AU - Tichý, Tomaš

TI - A probability density function estimation using F-transform

JO - Kybernetika

PY - 2010

PB - Institute of Information Theory and Automation AS CR

VL - 46

IS - 3

SP - 447

EP - 458

AB - The aim of this paper is to propose a new approach to probability density function (PDF) estimation which is based on the fuzzy transform (F-transform) introduced by Perfilieva in [10]. Firstly, a smoothing filter based on the combination of the discrete direct and continuous inverse F-transform is introduced and some of the basic properties are investigated. Next, an alternative approach to PDF estimation based on the proposed smoothing filter is established and compared with the most used method of Parzen windows. Such an approach can be of a great value mainly when dealing with financial data, i. e. large samples of observations.

LA - eng

KW - fuzzy transform; probability density function estimation; smoothing filter; financial returns; fuzzy transform; probability density function estimation; smoothing filter; financial returns

UR - http://eudml.org/doc/196338

ER -

## References

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