Modified Cox-Snell Residuals in Evaluating Gompertz Regression Model with Censored Data
DOI:
https://doi.org/10.61841/dnaaav05Keywords:
Gompertz Model,, Right Censored Covariate, Cox-Snell Residuals, Simulation.Abstract
In this research, a two parameter Gompertz parametric survival model was extended to incorporate with covariate in the presence of right censored and uncensored data. The estimation procedure was studied at different sample sizes and censoring percentiles via simulation methodology. Statistically, the simulated data were assessed using the bias, standard error and root mean square error of the parameter estimates for the Gompertz regression model. Subsequently, various combinations of sample sizes and censoring levels were employed to evaluate the performance of the proposed modifications to the Cox-Snell residuals for both censored and uncensored observations. The results clearly indicate that the estimates perform well when the censoring degrees are lower, and the sample sizes are greater. The performance of the modified Cox-Snell residuals based on harmonic mean outperformed than the other approaches.
Downloads
References
1. Chen, Z. (1997). Parameter Estimation of the Gompertz Population. Biometrical Journal, 39(1), 117-124.
2. Cox, D.R., & Snell, E.J. (1968). A General Definition of Residuals. Journal of the Royal Statistical Society
Series B (Methodological), 30(2), 248-275.
3. Dey, S., Moala, F.A., & Kumar, D. (2018). Statistical properties and different methods of estimation of
Gompertz distribution with application. Journal of Statistics and Management Systems, 21(5), 839–876.
4. Garg, M.L., Rao, B.R., & Redmond, C.K. (1970). Maximum-Likelihood Estimation of the Parameters of
the Gompertz Survival Function. Journal of the Royal Statistical Society Series C (Applied Statistics), 19(2), 152-159.
5. Gompertz, B. (1825). On the Nature of the Function Expressive of the Law of Human Mortality and on a New Mode of Determining the Value of Life Contingencies. Philosophical Transactions of the Royal
Society of London, 115, 513-583.
6. Gordon, N.H. (1990). Maximum likelihood estimation for mixtures of two gompertz distributions when
censoring occurs. Communications in Statistics - Simulation and Computation, 19(2), 733–747.
7. Ieren, T.G., Kromtit, F.M., Agbor, B.U., Eraikhuemen, I.B., & Koleoso, P.O. (2019). A Power Gompertz
Distribution: Model, Properties and Application to Bladder Cancer Data. Asian Research Journal of Mathematics, 15(2), 1-14.
8. Kiani, K., & Arasan, J. (2013). Gompertz model with time-dependent covariate in the presence of interval-
, right- and left-censored data. Journal of Statistical Computation and Simulation, 83(8), 1472-1490.
9. Kiani, K., Arasan, J., & Midi, H. (2012). Interval estimations for parameters of gompertz model with time
dependent covariate and right censored data. Sains Malaysiana, 41(4), 471-480.
10. Lenart, A. (2012). The moments of the Gompertz distribution and maximum likelihood estimation of its
parameters. Scandinavian Actuarial Journal, 2014(3), 255–277.
11. Makany, R. (1991). A Theoretical Basis for Gompertz’s Curve. Biometrical Journal, 33(1), 121–128.
12. Witten, W., & Satzer, W. (1992). Gompertz survival model parameters: Estimation and sensitivity.
Applied Mathematics Letters, 5(1), 7-12.
13. Wu, J.-W., Hung, W.-L., & Tsai, C.-H. (2004). Estimation of the parameters of the Gompertz distribution
using the least squares method. Applied Mathematics and Computation, 158(1), 133–147.
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.