Estimation in bivariate nonnormal distributions with stochastic variance functions

Date

2008-01-01

Author

Tiku, Moti L.
İslam, Muhammed Qamarul
SAZAK, HAKAN SAVAŞ

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Data sets in numerous areas of application can be modelled by symmetric bivariate nonnormal distributions. Estimation of parameters in such situations is considered when the mean and variance of one variable is a linear and a positive function of the other variable. This is typically true of bivariate t distribution. The resulting estimators are found to be remarkably efficient. Hypothesis testing procedures are developed and shown to be robust and powerful. Real life examples are given.

Subject Keywords

Statistics and Probability, Computational Theory and Mathematics, Applied Mathematics, Computational Mathematics

URI

https://hdl.handle.net/11511/48275

Journal

COMPUTATIONAL STATISTICS & DATA ANALYSIS

DOI

https://doi.org/10.1016/j.csda.2007.05.027

Collections

Department of Statistics, Article

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Citation Formats

M. L. Tiku, M. Q. İslam, and H. S. SAZAK, “Estimation in bivariate nonnormal distributions with stochastic variance functions,” COMPUTATIONAL STATISTICS & DATA ANALYSIS, pp. 1728–1745, 2008, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/48275.