Modeling Of Pdfs Of Non-Gaussian Data

ISBN-13: 9783659181665 / Angielski / Miękka / 2012 / 136 str.

Luping Yang

Opis

Non-Gaussian data is encountered in a variety of fields. To make reliable judgement and reasonable simulation, it is important to establish an appropriate probability density function(PDF) model for non-Gaussian data. In this book, three PDF models are studied to represent the distribution of non-Gaussian data. They are Pade-Laplace Method, Maximum Entropy Method and Hermite Polynomial Method. Also, test of goodness of fit are conducted among the proposed PDF models and common PDF models to compare the flexibility and robustness of these PDF models.

O autorze

Luping Yang was born in Sichuan Province, China. He obtained his Bachelor of Engineering from Tongji University in Shanghai, China, in July 2009. After graduation, he joined University of Florida in pursuit of a Master of Science degree. He received his MS in civil engineering with a minor in mathematics in the fall of 2011.