An Extension of the Inverse Gaussian Distribution

Talha Arslan

Chapter 10 in Modeling and Advanced Techniques in Modern Economics, 2022, pp 211-219 from World Scientific Publishing Co. Pte. Ltd.

Abstract: In this study, an α-monotone extension of the inverse Gaussian (αIG) distribution is introduced. Then, the method of moments estimations for the parameters of the αIG distribution is provided. A real dataset is used to show the fitting performance of the αIG distribution. The results show that the αIG distribution fits the corresponding dataset better than the IG distribution if the well-known goodness-of-fit statistics are taken into account. Note that the αIG distribution is defined as a general class of the IG distribution by adding a new shape parameter. It can be considered an alternative to the IG distribution in modeling data from different areas of science.

Keywords: Harmonic Regression; Periodograms; Consumer Price Index; Food Inflation; Turkey; Gaussian Distribution; Europe Union; GDP; Panel Data; Spatial Regression; Measurement Errors; Nonlinear Time Series; Chaotic Time Series; Weibull Distribution; Location Parameters; Fiducial Approach; Hypothesis Testing; Green Swan; Financial Stability; Annex II Countries; Financial Time Series; Kernels; Stock Index; Machine Learning; Statistical Learning; Optimization; WSAR Algorithm; Deep Neural Networks; Phyton; Parameter Estimation; COVID-19; Clustering Analyses; Artificial Neural Networks; Performance Criteria; Time Series Forecasting; Statistical Inference (search for similar items in EconPapers)
JEL-codes: C1 C4 C5 C6 C63 (search for similar items in EconPapers)
Date: 2022
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