https://cris.library.msu.ac.zw//handle/11408/322 Sun, 05 Apr 2026 04:45:03 GMT 2026-04-05T04:45:03Z https://cris.library.msu.ac.zw//handle/11408/6877 Title: The New Topp-Leone Exponentiated Half Logistic-Gompertz-G Family of Distributions with Applications Authors: Charumbira, Wellington; Broderick Oluyede; Fastel Chipepa Abstract: This research introduces a new family of distributions (FoD) titled the Topp-Leone Exponentiated-Half-Logistic-Gompertz-G (TL-EHL-Gom-G) distribution. The study explores a variety of statistical properties of the developed family, such as the quantile function, series expansion, order statistics, entropy, stochastic orders and moments. Through Monte Carlo simulations, various estimation techniques were compared, including the least squares (LS), Anderson Darling (AD), maximum likelihood (ML) and Cram\'er-von-Mises (CVM) methods via root mean square error (RMSE) and average bias (Abias). The results indicated that the ML estimation method performed better than other methods, hence, the selection for estimating the model parameters. To showcase the usefulness, robustness and applicability of the model, we applied it to three real-life data, including dataset with censored observations. The TL-EHL-Gom-W distribution, a special case of the TL-EHL-Gom-G FoD showed superiority over nested and non-nested models. Wed, 01 Jan 2025 00:00:00 GMT https://cris.library.msu.ac.zw//handle/11408/6877 2025-01-01T00:00:00Z Charumbira, Wellington Broderick Oluyede Fastel Chipepa https://cris.library.msu.ac.zw//handle/11408/6873 Title: A New Topp–Leone Odd Weibull Flexible-G Family of Distributions with Applications Authors: Chipepa, Fastel; Mahmoud M. Abdelwahab; Charumbira, Wellington Fredrick; Mustafa M. Hasaballah Abstract: The acceptance of generalized distributions has significantly improved over the past two decades. In this paper, we introduce a new generalized distribution: Topp–Leone odd Weibull flexible-G family of distributions (FoD). The new FoD is a combination of two FOD; the Topp–Leone-G and odd Weibull-flexible-G families. The proposed FoD possesses more flexibility compared to the two individual FoD when considered separately. Some selected statistical properties of this new model are derived. Three special cases from the proposed family are considered. The new model exhibits symmetry and long or short tails, and it also addresses various levels of kurtosis. Monte Carlo simulation studies were conducted to verify the consistency of the maximum likelihood estimators. Two real data examples were used as illustrations on the flexibility of the new model in comparison to other competing models. The developed model proved to perform better than all the selected competing models. Wed, 01 Jan 2025 00:00:00 GMT https://cris.library.msu.ac.zw//handle/11408/6873 2025-01-01T00:00:00Z Chipepa, Fastel Mahmoud M. Abdelwahab Charumbira, Wellington Fredrick Mustafa M. Hasaballah https://cris.library.msu.ac.zw//handle/11408/6503 Title: The Harris-G power series class of distributions with applications Authors: Wellington Fredrick Charumbira; Broderick Oluyede; Fastel Chipepa; Lesego Gabaitiri Abstract: This study introduces a novel class of distributions (CoD) called the Harris-G power series (H-GPS) CoD. The model is obtained by compounding the Harris-G distribution with the power series distribution (PSD). Some statistical properties including quantile function, linear representation, distribution of order statistics, moments, probability weighted moments and Rényi entropy are developed. Four special cases including the Harris-log-logistic distribution, Harris-log-logistic logarithmic distribution, Harris-Weibull Poisson distribution and the Harris-Weibull logarithmic distribution are presented. Parameter estimation is done using maximum likelihood estimation technique. A simulation study is carried out for the special case of Harris-Weibull Poisson (H-WP) distribution. Finally the Harris-Weibull Poisson is applied to two real datasets to illustrate the usefulness and applicability of the model. Tue, 08 Oct 2024 00:00:00 GMT https://cris.library.msu.ac.zw//handle/11408/6503 2024-10-08T00:00:00Z Wellington Fredrick Charumbira Broderick Oluyede Fastel Chipepa Lesego Gabaitiri https://cris.library.msu.ac.zw//handle/11408/6489 Title: Robust modelling framework for short-term forecasting of global horizontal irradiance Authors: Edina Chandiwana; Caston Sigauke; Alphonce Bere Abstract: The increasing demand for electricity and the need for clean energy sources have increased solar energy use. Accurate forecasts of solar energy are required for easy management of the grid. This paper compares the accuracy of two Gaussian Process Regression (GPR) models combined with Additive Quantile Regression (AQR) and Bayesian Structural Time Series (BSTS) models in the 2-day ahead forecasting of global horizontal irradiance using data from the University of Pretoria from July 2020 to August 2021. Four methods were adopted for variable selection, Lasso, ElasticNet, Boruta, and GBR (Gradient Boosting Regression). The variables selected using GBR were used because they produced the lowest MAE (Minimum Absolute Errors) value. A comparison of seven models GPR (Gaussian Process Regression), Two-layer DGPR (Two-layer Deep Gaussian Process Regression), bstslong (Bayesian Structural Time Series long), AQRA (Additive Quantile Regression Averaging), QRNN(Quantile Regression Neural Network), PLAQR(Partial Linear additive Quantile Regression), and Opera(Online Prediction by ExpRt Aggregation) was made. The evaluation metrics used to select the best model were the MAE (Mean Absolute Error) and RMSE (Root Mean Square Error). Further evaluations were done using proper scoring rules and Murphy diagrams. The best individual model was found to be the GPR. The best forecast combination was AQRA ((AQR Averaging) based on MAE. However, based on RMSE, GPNN was the best forecast combination method. Companies such as Eskom could use the methods adopted in this study to control and manage the power grid. The results will promote economic development and sustainability of energy resources Mon, 12 Dec 2022 00:00:00 GMT https://cris.library.msu.ac.zw//handle/11408/6489 2022-12-12T00:00:00Z Edina Chandiwana Caston Sigauke Alphonce Bere