Properties of Generalized Log Pearson Type VII Distribution

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Focusing on the generalized log Pearson (GLP) type VII distribution, this book explores its flexibility in data fitting compared to the standard log Pearson type VII. It discusses the parameter combinations that enhance the distribution's utility, including its closure under inversion, leading to various derived distributions. Theoretical properties are developed, and the distribution is characterized through conditional expectation. It effectively models datasets, validated by Anderson-Darling and Cramer-von Mises statistics, while also establishing the generalized log normal distribution as its limiting form.