Afrika Statistika

A New Gamma Generalized Lindley-Loglogistic Distribution with Applications

Thatayaone Moakofi, Broderick Oluyede, Boikanyo Makubate — Mon, 22 Feb 2021 00:00:00 +0000

A new distribution called the gamma exponentiated Lindley Log-logistic (GELLLoG) distribution is developed. Some properties of the new distribution including hazard function, quantile function, moments, conditional moments, mean and median deviations, Bonferroni and Lorenz curves, distribution of the order statistics and Renyi entropy are derived. Maximum likelihood estimation technique ´ is used to estimate the model parameters. We conduct a simulation study to examine the bias and mean square error of the maximum likelihood estimators. Finally, applications to real datasets to illustrate the usefulness of the proposed distribution are presented.

Key words: Gamma distribution; Lindley distributions: Exponentiated distribution: Long-logistic distribution: Generalized distribution: Maximum likelihood estimation

Half-Logistic Odd Weibull-Topp-Leone-G Family of Distributions: Model, Properties and Applications

Fastel Chipepa, Divine Wanduku, Broderick Oluyede — Mon, 22 Feb 2021 00:00:00 +0000

A new flexible and versatile generalized family of distributions, namely, half logistic odd Weibull-Topp-Leone-G (HLOW-TL-G) distribution is presented. The distribution can be traced back to the exponentiated-G distribution. We derive the statistical properties of the proposed family of distributions. Maximum likelihood estimates of the HLOW-TL-G family of distributions are also presented. Five special cases of the proposed family are presented. A simulation study and real data applications on one of the special cases are also presented.

Key words: half-logistic-G; Topp-Leone-G; Odd Weibull-G; generalized distribution; maximum likelihood estimation

Adaptive Hyperbolic Asymmetric Power ARCH (A-HY-APARCH) model: Stability and Estimation

Charline Uwilingiyimana, Abdou Ka Diongue , Carlos Ogouyandjou — Mon, 22 Feb 2021 00:00:00 +0000

In this paper, a new asymmetric GARCH type model that generalizes the Hyperbolic Asymmetric Power ARCH (HY-APARCH) process is proposed. The proposed model takes into consideration some characteristics of financial time series data like volatility clustering, long memory and structural changes. The necessary and sufficient conditions for the asymptotic stability of the model are derived and parameter estimation methods are proposed. The Monte Carlo Simulations are done to prove the performance of the estimation method.

Key words: long range dependence; structural changes; HYAPARCH.