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Local influence in comparative calibration models under elliptical t-distributions
Manuel Galea1, Heleno Bolfarine, Filidor Vilca
1Departamento de Estadística, Universidad de Valparaíso, Casilla 5030, Valparaíso, Chile. manuel.galea@uv.cl
Biometrical Journal. Biometrische Zeitschrift
|January 3, 2006
Summary
This study applies local influence methods to structural comparative calibration under elliptical distributions. It evaluates model and data perturbations for robust analysis using real-world data.
Area of Science:
- Statistics
- Statistical Modeling
Background:
- Local influence analysis assesses model sensitivity to small perturbations.
- Structural comparative calibration is used for comparing calibration models.
- Elliptical distributions offer a flexible framework for multivariate data.
Purpose of the Study:
- To investigate the application of local influence diagnostics in structural comparative calibration.
- To evaluate the impact of various perturbation schemes on calibration models.
- To demonstrate the utility of these methods with a real data set.
Main Methods:
- Applying local influence (Cook, 1986) diagnostics.
- Utilizing structural comparative calibration (Bolfarine and Galea, 1995).
- Assuming multivariate elliptical distributions for measurement errors.
- Investigating different perturbation schemes.
- Employing the elliptical t-distribution for a case study.
Main Results:
- The study identifies how local influence can detect influential perturbations in structural comparative calibration.
- Perturbation schemes effectively reveal model or data set sensitivities.
- The elliptical t-distribution provides a practical case for applying these methods.
Conclusions:
- Local influence is a valuable tool for assessing the robustness of structural comparative calibration models.
- The methodology is applicable to real-world data exhibiting elliptical distributions.
- Understanding perturbation effects enhances the reliability of calibration results.
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