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The main goal in this study was to determine confidence intervals for average age, average seniority, and average money-savings, for faculty members in a university retirement system using a simulation model. The simulation—built-in Arena—considers age, seniority, and the probability of continuing in the institution as the main input random variables in the model. An annual interest rate of 7% and an average annual salary increase of 3% were considered. The scenario simulated consisted of the teacher and the university making contributions, the faculty 5% of his salary, and the university 5% of the teacher’s salary. Since the base salaries with which teachers join to university are variable, we considered a monthly salary of MXN 23 181.2, corresponding to full-time teachers with middle salaries. The results obtained by a simulation of 30 replicates showed that the confidence intervals for the average age at retirement were (55.0, 55.2) years, for the average seniority (22.1, 22.3) years, and for the average savings amount (329 795.2, 341 287.0) MXN. Moreover, the risk that a retiree of 62 years of age and more of 25 years of work, is alive after his savings runs out is approximately 98% and this happens at 64 years of age. [ABSTRACT FROM AUTHOR]

A new uniform distribution model, generalized powered uniform distribution (GPUD), which is based on incorporating the parameter k into the probability density function (pdf) associated with the power of random variable values and includes a powered mean operator, is introduced in this paper. From this new model, the shape properties of the pdf as well as the higher-order moments, the moment generating function, the model that simulates the GPUD and other important statistics can be derived. This approach allows the generalization of the distribution presented by Jayakumar and Sankaran (2016) through the new GPUD(J-S)\documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$${ GPUD }_{ (J-S)}$$\end{document} distribution. Two sets of real data related to COVID-19 and bladder cancer were tested to demonstrate the proposed model’s potential. The maximum likelihood method was used to calculate the parameter estimators by applying the maxLik package in R. The results showed that this new model is more flexible and useful than other comparable models. [ABSTRACT FROM AUTHOR]