Výsledky vyhledávání

Conditional density estimation using fuzzy GARCH models

Autor: Almeida, Rui Jorge, Basturk, Nalan, Uzay Kaymak, Da Costa Sousa, Joao Miguel, Kruse, R., Berthold, MR, Moewes, C., Gil, Ma, Grzegorzewski, P., Hryniewicz, O.

Publikováno v: ResearcherID
Synergies of Soft Computing and Statistics for Intelligent Data Analysis ISBN: 9783642330414
SMPS
Advances in Intelligent Systems and Computing, 173-181
STARTPAGE=173;ENDPAGE=181;TITLE=Advances in Intelligent Systems and Computing
Synergies Of Soft Computing And Statistics For Intelligent Data Analysis. Proceedings of the 6th International Conference on Soft Methods in Probability and Statistics, SMPS 2012, Konstanz, Germany, October 4-6, 2012, 173-181
STARTPAGE=173;ENDPAGE=181;TITLE=Synergies Of Soft Computing And Statistics For Intelligent Data Analysis. Proceedings of the 6th International Conference on Soft Methods in Probability and Statistics, SMPS 2012, Konstanz, Germany, October 4-6, 2012

Time series data exhibits complex behavior including non-linearity and path-dependency. This paper proposes a flexible fuzzy GARCH model that can capture different properties of data, such as skewness, fat tails and multimodality in one single model.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b6a847a871d2de2a7d72910dde3dcf23
https://doi.org/10.1007/978-3-642-33042-1_19

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Regional spatial analysis combining fuzzy clustering and non-parametric correlation

Autor: Tutmez, Bulent, Uzay Kaymak, Kruse, R., Berthold, MR, Moewes, C., Gil, Ma, Grzegorzewski, P., Hryniewicz, O.

Publikováno v: ResearcherID
Synergies of Soft Computing and Statistics for Intelligent Data Analysis ISBN: 9783642330414
SMPS
Synergies Of Soft Computing And Statistics For Intelligent Data Analysis, 219-227
STARTPAGE=219;ENDPAGE=227;TITLE=Synergies Of Soft Computing And Statistics For Intelligent Data Analysis

In this study, regional analysis based on a limited number of data, which is an important real problem in some disciplines such as geosciences and environmental science, was considered for evaluating spatial data. A combination of fuzzy clustering an

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3e8c9129b9f50fef85bad9ef58504078
https://doi.org/10.1007/978-3-642-33042-1_24