O interpretacji nieparametrycznych modeli regresyjnych

• Authors: Jacek Stelmach

Title variants

EN

Parametric Interpretation of Non-Parametric Regression Models

• Languages of publication: PL

Abstracts

EN

The advantage of the parametric regression models is the possibility of interpretation of the parameters of the regression model, i.e. to determine the direction and strength of the influence of predictors on the dependent variable. Unfortunately, in practice - the nonlinearity of the real processes, the influence of the phenomena with various probability distributions and a small number of observations limits the building of parametric models while the interpretation of non-parametric models is either impossible or very limited. Frequently such interpretation is useful in the specified range of variation. This may be a typical range of variation - for example, between the second and third quartiles, or a specific range due to the nature of the modeled phenomenon or process. It is difficult however, to build parametric models based only on the range of explanatory variables, because in this way we exclude observations giving additional knowledge into the model. The essence of this study is to enable the interpretation of non-parametric models through the creation of additional observations with these models in an interesting range of explanatory variables. These observations create secondary dataset used for the construction of a parametric model, which can now be interpreted. Presented investigations compare - using simulation - parametric models created for secondary sample with parametric models calculated for the original data.

Keywords

PL

Metoda Monte Carlo; Modele regresji; Regresja nieparametryczna

EN

Monte Carlo method; Nonparametric regression Regression models

• Publisher: Uniwersytet Ekonomiczny w Katowicach
• Journal: Studia Ekonomiczne
• Year: 2014
• Volume: 203
• Pages: 154-162

Contributors

author

Jacek Stelmach

References

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Identifiers

ISSN

2083-8611