| dc.contributor.author | Krzyśko, Mirosław | |
| dc.contributor.author | Smaga, Łukasz | |
| dc.date.accessioned | 2018-02-28T11:45:02Z | |
| dc.date.available | 2018-02-28T11:45:02Z | |
| dc.date.issued | 2018 | |
| dc.identifier.issn | 0208-6018 | |
| dc.identifier.uri | http://hdl.handle.net/11089/24165 | |
| dc.description.abstract | In this paper, the binary classification problem of multi‑dimensional functional data is considered. To solve this problem a regression technique based on functional logistic regression model is used. This model is re‑expressed as a particular logistic regression model by using the basis expansions of functional coefficients and explanatory variables. Based on re‑expressed model, a classification rule is proposed. To handle with outlying observations, robust methods of estimation of unknown parameters are also considered. Numerical experiments suggest that the proposed methods may behave satisfactory in practice. | en_GB |
| dc.description.abstract | W niniejszym artykule rozważany jest problem dwuetykietowej klasyfikacji wielowymiarowych danych funkcjonalnych. Zaproponowane rozwiązanie tego problemu oparto na technikach regresyjnych i modelu regresji logistycznej dla danych funkcjonalnych. Model ten został przekształcony do szczególnego modelu regresji logistycznej za pomocą rozwinięcia (będących funkcjami) współczynników regresji i zmiennych objaśniających w bazie funkcyjnej. Na podstawie tego modelu skonstruowana została reguła klasyfikacyjna. W przypadku występowania obserwacji odstających rozważane są również metody odpornej estymacji nieznanych parametrów. Eksperymenty numeryczne sugerują, że proponowane metody mogą z powodzeniem być wykorzystane w praktycznych zagadnieniach. | pl_PL |
| dc.language.iso | pl | en_GB |
| dc.publisher | Wydawnictwo Uniwersytetu Łódzkiego | en_GB |
| dc.relation.ispartofseries | Acta Universitatis Lodziensis. Folia Oeconomica;334 | |
| dc.subject | basis functions representation | en_GB |
| dc.subject | classification problem | en_GB |
| dc.subject | functional regression analysis | en_GB |
| dc.subject | logistic regression model | en_GB |
| dc.subject | multi‑dimensional functional data | en_GB |
| dc.subject | robust estimation | en_GB |
| dc.subject | analiza regresji dla danych funkcjonalnych | pl_PL |
| dc.subject | estymacja odporna | pl_PL |
| dc.subject | model regresji logistycznej | pl_PL |
| dc.subject | rozwinięcie funkcji w bazie funkcyjnej | pl_PL |
| dc.subject | wielowymiarowe dane funkcjonalne | pl_PL |
| dc.subject | zagadnienie klasyfikacji | pl_PL |
| dc.title | Selected Robust Logistic Regression Specification for Classification of Multi‑dimensional Functional Data in Presence of Outlier | en_GB |
| dc.title.alternative | Zastosowanie odpornej regresji logistycznej do klasyfikacji wielowymiarowych danych funkcjonalnych | pl_PL |
| dc.type | Article | en_GB |
| dc.rights.holder | © Copyright by Authors, Łódź 2018; © Copyright for this edition by Uniwersytet Łódzki, Łódź 2018 | en_GB |
| dc.page.number | [53]-66 | |
| dc.contributor.authorAffiliation | The President Stanisław Wojciechowski State University of Applied Sciences in Kalisz, Interfaculty Institute of Mathematics and Statistics | |
| dc.contributor.authorAffiliation | Adam Mickiewicz University in Poznań, Faculty of Mathematics and Computer Science | |
| dc.identifier.eissn | 2353-7663 | |
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| dc.contributor.authorEmail | mkrzysko@amu.edu.pl | |
| dc.contributor.authorEmail | ls@amu.edu.pl | |
| dc.identifier.doi | 10.18778/0208-6018.334.04 | |
| dc.relation.volume | 2 | en_GB |
| dc.subject.jel | C38 | |
| dc.subject.jel | C13 | |
