Modeling the dependence structure of coupled lives in the Philippines using some Archimedean copulas

Date of Publication

2009

Document Type

Bachelor's Thesis

Degree Name

Bachelor of Science in Statistics Major in Actuarial Science

Subject Categories

Statistics and Probability

College

College of Science

Department/Unit

Mathematics and Statistics

Thesis Adviser

Kristine Joy E. Carpio

Defense Panel Chair

Isagani B. Jos

Defense Panel Member

Regina Tresvalles
Paolo Bautista

Abstract/Summary

Dependence can be modeled by the use of copulas. This research presents the application of copulas in modeling the dependence structure using a dataset from the Philippine Social Security System. Empirical marginal survival distribution were first computed from the data using the Kaplan-Meier Estimator that led to the computation of Gompertz distribution as the parametric marginal distribution. The bivariate survival function was estimated by the use of a simple non-parametric estimator presented in the study of Lin et al. Through the use of generators for each copula, the difference between the empirical estimates and the theoretical ones were compared and analyzed. Graphs and errors were the basis in choosing which among the candidate copulas best describes the Philippine dataset. Clayton copula best fits the joint survival function in describing the dependence structure for the Philippine dataset.

Abstract Format

html

Language

English

Format

Print

Accession Number

TU15073

Shelf Location

Archives, The Learning Commons, 12F, Henry Sy Sr. Hall

Physical Description

vii, 34 leaves, color illustrations, 28 cm.

Keywords

Copulas (Mathematical statistics); Dependence (Statistics)

Embargo Period

4-4-2021

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