Abstract
The beta transformation gives a great variety of shapes which allow to model symmetric, skewed and bimodal shaped densities. Such procedure generates what we call the beta generalized (beta-G) family of distributions. This chapter presents a survey on the beta-G models and their mathematical properties. We present some explicit expressions for the ordinary and incomplete moments, probability weighted moments, cumulants and generating function, mean deviations, entropies and order statistics.
Keywords: Beta-G model; Entropy; Mean deviation; Moment; Probability weighted moment; Regression model.
Related Books
Advances in Sampling Theory-Ratio Method of Estimation
Advances in Time Series Forecasting
Advances in Time Series Forecasting
Concepts and Recent Advances in Generalized Information Measures and Statistics
Exponential Data Fitting and its Applications
Predictive Analytics Using Statistics and Big Data: Concepts and Modeling
Probability Theory for Fuzzy Quantum Spaces with Statistical Applications
Reliability Calculations with the Stochastic Finite Element
Introductory Statistical Procedures with SPSS