| bvpa-package {bvpa} | R Documentation |
Bivariate Pareto Distribution
Description
Implements the EM algorithm with one-step Gradient Descent method to estimate the parameters of the Block-Basu bivariate Pareto distribution with location and scale. We also found parametric bootstrap and asymptotic confidence intervals based on the observed Fisher information scale, shape parameters, and exact confidence intervals for location parameters.
Author(s)
Biplab Paul <paul.biplab497@gmail.com> and Arabin Kumar Dey <arabin@iitg.ac.in>
References
Biplab Paul and Arabin Kumar Dey (2023). An EM algorithm for absolutely continuous Marshall-Olkin bivariate Pareto distribution with location and scale, Preprint.
E L Lehmann and George Casella (1998). Theory of Point Estimation, Springer, New York, doi.org/10.1007/b98854.
Bradley Efron and R J Tibshirani (1994). An Introduction to the Bootstrap, CRC press, New York, doi.org/10.1201/9780429246593.
A P Dempster, N M Laird and D B Rubin (1977). Maximum Likelihood from Incomplete Data via the EM Algorithm, Journal of the royal statistical society: series B (methodological), www.jstor.org/stable/2984875.