Modeling COVID-19 Datasets with Three-Parameter Frechet Distribution

This paper derived and studied a new three- parameter model called the Type II Generalized Topp-Leone Fréchet distribution. The new model is an extension of the baseline one parameter Fréchet distribution. The new model is also an alternative to Type II Topp-Leone Fréchet distribution. The new model is obtained from Type II generalized Topp-Leone-G family of distributions with the addition of two extra positive shape parameters to control both the tail weights and the center at the same time. Various structural properties including explicit expressions for ordinary moments, mean, survival function, hazard function, quantile function, median, moment generating function and the pdf of the minimum and maximum order statistics were derived. Simulation study was also carried out to assess the performance of the estimation method used and as expected, as the sample sizes increase, the root mean square error (RMSE) and biases approaches zero and the estimated values of the parameters approach the true value of the parameters. The maximum likelihood method of parameter estimation is used to estimate the unknown model parameters. Three applications to real data sets relating to COVID-19 mortality rate are used to demonstrate the importance of the new model and the results presented showed that the new model fits the data sets better that its comparators.