Regresión borrosa VS. regresión por mínimos cuadrados ordinarios: caso de estudio
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| 著者: | , , |
|---|---|
| フォーマット: | artículo original |
| 状態: | Versión publicada |
| 出版日付: | 2011 |
| その他の書誌記述: | The objective of this paper is to disseminate the technique of fuzzy regression and to give a practical example of its use. To this end, classical regression is compared to several fuzzy regression models on a problem concerning the consumer confidence index with respect to the dollar rate, the latter taken as the independent variable. A brief introduction is given to each of the different methodologies employed. The results obtained using the regression algorithms, one with ordinary least squares and another two with fuzzy regression, are presented. The instances generated using the official historical data for the problem are given and the numerical results obtained with the regression methods are reported. |
| 国: | Portal de Revistas UCR |
| 機関: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| 言語: | Español |
| OAI Identifier: | oai:archivo.portal.ucr.ac.cr:article/2113 |
| オンライン･アクセス: | https://archivo.revistas.ucr.ac.cr/index.php/matematica/article/view/2113 |
| キーワード: | linear regression fuzzy regression fuzzy linear programming regresión lineal regresión borrosa programación lineal borrosa |