Book contents
- Generalized Frequency Distributions for Environmental and Water Engineering
- Generalized Frequency Distributions for Environmental and Water Engineering
- Copyright page
- Dedication
- Contents
- Preface
- Acknowledgments
- 1 Introduction
- 2 Burr–Singh–Maddala Distribution
- 3 Halphen Type A Distribution
- 4 Halphen Type B Distribution
- 5 Halphen Inverse B Distribution
- 6 Three-Parameter Generalized Gamma Distribution
- 7 Generalized Beta Lomax Distribution
- 8 Feller–Pareto Distribution
- 9 Kappa Distribution
- 10 Four-Parameter Exponential Gamma Distribution
- 11 Summary
- Appendix General Procedure for Goodness-of-Fit Study, Construction of Confidence Interval, and 95% Confidence Bound with Parametric Bootstrap Method
- Index
- References
7 - Generalized Beta Lomax Distribution
Published online by Cambridge University Press: 13 April 2022
- Generalized Frequency Distributions for Environmental and Water Engineering
- Generalized Frequency Distributions for Environmental and Water Engineering
- Copyright page
- Dedication
- Contents
- Preface
- Acknowledgments
- 1 Introduction
- 2 Burr–Singh–Maddala Distribution
- 3 Halphen Type A Distribution
- 4 Halphen Type B Distribution
- 5 Halphen Inverse B Distribution
- 6 Three-Parameter Generalized Gamma Distribution
- 7 Generalized Beta Lomax Distribution
- 8 Feller–Pareto Distribution
- 9 Kappa Distribution
- 10 Four-Parameter Exponential Gamma Distribution
- 11 Summary
- Appendix General Procedure for Goodness-of-Fit Study, Construction of Confidence Interval, and 95% Confidence Bound with Parametric Bootstrap Method
- Index
- References
Summary
The four-parameter beta Lomax (FPBL) distribution is a generalization of the beta distribution through random variable transformation. The FPBL distribution may be reduced to three-parameter distribution and may also be extended to five-parameter beta Lomax distribution by adding the location parameter. In this chapter, the FPBL distribution is derived using the entropy theory and then its parameters are estimated with the principle of maximum entropy and the method of maximum likelihood estimation.
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- Publisher: Cambridge University PressPrint publication year: 2022