Interval-Valued Linear Model
| Autor: | Xun Wang, Shoumei Li, Thierry Denoeux |
|---|---|
| Přispěvatelé: | Beijing University of Technology, Heuristique et Diagnostic des Systèmes Complexes [Compiègne] (Heudiasyc), Université de Technologie de Compiègne (UTC)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Excellence 'Maîtrise des Systèmes de Systèmes Technologiques' (Labex MS2T) |
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Proper linear model
General Computer Science 020209 energy 02 engineering and technology Dp metric Best linear unbiased prediction U-statistic 01 natural sciences Generalized linear mixed model Lehmann–Scheffé theorem lcsh:QA75.5-76.95 [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] 010104 statistics & probability Minimum-variance unbiased estimator Statistics 0202 electrical engineering electronic engineering information engineering Applied mathematics 0101 mathematics D metric Mathematics best binary linear unbiased estimation Linear model QA75.5-76.95 Covariance Computational Mathematics Electronic computers. Computer science interval-valued linear model 020201 artificial intelligence & image processing lcsh:Electronic computers. Computer science least square estimation |
| Zdroj: | International Journal of Computational Intelligence Systems, Vol 8, Iss 1 (2015) International Journal of Computational Intelligence Systems International Journal of Computational Intelligence Systems, Atlantis Press, 2015, 8 (1), pp.114-127. ⟨10.1080/18756891.2014.967010⟩ Scopus-Elsevier |
| ISSN: | 1875-6883 1875-6891 |
| DOI: | 10.1080/18756891.2014.967010⟩ |
| Popis: | International audience; This paper introduces a new type of statistical model: the interval-valued linear model, which describes the linear relationship between an interval-valued output random variable and real-valued input variables. Firstly, notions of variance and covariance of set-valued and interval-valued random variables are introduced. Then, we give the definition of the interval-valued linear model and its least square estimation, as well as some properties of the least square estimator (LSE). Thirdly, we show that, whereas the best linear unbiased estimation does not exist, the best binary linear unbiased estimator exists and it is the LSE. Finally, we present simulation experiments and an application example regarding temperatures of cities affected by their latitude, which illustrates the application of the proposed model. |
| Databáze: | OpenAIRE |
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