Regresja logistyczna dla danych symbolicznych interwałowych

• Authors: Pełka Marcin

Title variants

EN

Logistic regression for interval-valued symbolic data

• Languages of publication: PL

Abstracts

EN

When dealing with real data situation we often have a binary (biomial, dichoto-mous) dependent variable. As the linear probability model is not such a good solution in such a situation there is a need to use nonlinear models. A quite good solution for such a sit-uation is the logistic regression model. The paper presents an adaptation of linear regression model when dealing with symbolic interval-valued variables. Four approaches poposed by de Souza et. al [2011] how to apply such variables are presented. In the empirical part re-sults obtained with the application of artificial and real data sets are shown. The best results are obtained for midpoint and bounds (joint estimation) methods.

Keywords

EN

logistic regression; interval-valued symbolic variables; symbolic data analysis

• Publisher: Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
• Journal: Econometrics. Ekonometria. Advances in Applied Data Analytics
• Year: 2015
• Issue: 2 (48)
• Pages: 44-52

Contributors

author

Pełka Marcin

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