Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5077426 | Insurance: Mathematics and Economics | 2010 | 14 Pages |
Abstract
We develop a test for the fuzziness of regression coefficients based on the Tanaka et al. (1982) and He et al. (2007) possibilistic fuzzy regression models. We interpret the spread of the regression coefficients as a statistic measuring the fuzziness of the relationship between the corresponding independent variable and the dependent variable. We derive test distributions based on the null hypothesis that such spreads could have been obtained by estimating a possibilistic regression with data generated by a classical regression model with random errors. As an example, we show how our test detects a fuzzy regression coefficient in a solvency prediction model for German property-liability insurance companies.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Thomas R. Berry-Stölzle, Marie-Claire Koissi, Arnold F. Shapiro,