Some Properties of Exponentiated - Exponential Logistic Distribution and its Related Regression Model

Authors

DOI:

https://doi.org/10.6092/issn.1973-2201/17836

Keywords:

Logistic distribution, Logistic regression model, Simulation

Abstract

This paper introduces a new class of logistic distribution, namely Exponentiated logistic distribution, which is derived from type II logistic distribution. We have investigated its properties, discussed parameter estimation, and demonstrated its usefulness in analysing real-life medical data. The developed model provides researchers with valuable tools for accurately modelling and analysing medical phenomena, thereby contributing to advancements in healthcare research and decision-making.

References

A. A. AFIFI, S. P. AZEN (2014). Statistical Analysis: a Computer Oriented Approach. Academic Press, New York.

N. BALAKRISHNAN (2013). Handbook of the Logistic Distribution. CRC Press, Boca Raton.

N. BALAKRISHNAN, A. HOSSAIN (2007). Inference for the Type II generalized logistic distribution under progressive Type II censoring. Journal of Statistical Computation and Simulation, 77, no. 12, pp. 1013–1031.

N. BALAKRISHNAN, M. LEUNG (1988). Order statistics from the type Igeneralized logistic distribution. Communications in Statistics - Simulation and Computation, 17, no. 1, pp. 25–50.

J. BERKSON (1944). Application of the logistic function to bio-assay. Journal of the American Statistical Association, 39, no. 227, pp. 357–365.

J. BERKSON (1951). Why I prefer logits to probits. Biometrics, 7, no. 4, pp. 327–339.

G. DYKE, H. PATTERSON (1952). Analysis of factorial arrangements when the data are proportions. Biometrics, 8, no. 1, pp. 1–12.

C. EMMENS (1940). The dose/response relation for certain principles of the pituitary gland, and of the serum and urine of pregnancy. Journal of Endocrinology, 2, no. 2, pp. 194–225.

D. J. FINNEY (1947). The principles of biological assay. Supplement to the Journal of the Royal Statistical Society, 9, no. 1, pp. 46–91.

D. J. FINNEY (1978). Statistical Method in Biological Assay. Ed. 3. Charles Griffin & Company, London.

F. GALTON (1896). Application of the method of percentiles to Mr. Yule’s data on the distribution of pauperism. Journal of the Royal Statistical Society, 59, no. 2, pp. 392–396.

I. GRADSHTEYN, I. RYZHIK (2000). Table of Integrals, Series, and Products. Ed. 6. Academic Press, San Diego.

D. W. HOSMER JR, S. LEMESHOW, R. X. STURDIVANT (2013). Applied Logistic Regression, vol. 398. JohnWiley & Sons, Hoboken.

L. MANJU (2016). On generalized logistic models and applications to medical data. PhD Thesis submitted to University of Kerala (Unpublished). URL https://shodhganga.inflibnet.ac.in.

D. MCFADDEN (1973). Conditional logit analysis of qualitative choice behaviour. In Frontiers in Econometrics, Academic Press, New York, pp. 105–142.

F.OLIVER (1982). Notes on the logistic curve for human populations. Journal of the Royal Statistical Society - Series A, 145, no. 3, pp. 359–363.

R. PEARL (1924). Studies in Human Biology. Williams &Wilkins, Baltimore.

R. PEARL (1940). The aging of populations. Journal of the American Statistical Association, 35, no. 209b, pp. 277–297.

R. L. PLACKETT (1959). The analysis of life test data. Technometrics, 1, no. 1, pp. 9–19.

S. M. ROSS (2022). Simulation. Academic press, San Diego.

L. P. SAPKOTA (2020). Exponentiated exponential logistic distribution: some properties and applications. Janapriya Journal of Interdisciplinary Studies, 9, pp. 100–108.

H. SCHULTZ (1930). The standard error of a forecast from a curve. Journal of the American Statistical Association, 25, no. 170, pp. 139–185.

A. W. VAN DER VAART (2000). Asymptotic Statistics, vol. 3. Cambridge University Press, Cambridge.

E. B. WILSON, J. WORCESTER (1943). The determination of LD 50 and its sampling error in bio-assay. Proceedings of the National Academy of Sciences, 29, no. 2, pp. 79–85.

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Published

2025-09-02

How to Cite

Kumar, S., & Manju, L. (2024). Some Properties of Exponentiated - Exponential Logistic Distribution and its Related Regression Model. Statistica, 84(1), 27–61. https://doi.org/10.6092/issn.1973-2201/17836

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