The Comparison of Inverse Gaussian and Gamma Regression: Application on Stunting Data in Jepara

Eva Khoirun Nisa; Riska  Maulina

doi:10.20956/j.v21i1.36351

Authors

Eva Khoirun Nisa UIN Walisongo
Riska Maulina UIN Walisongo Semarang

DOI:

https://doi.org/10.20956/j.v21i1.36351

Keywords:

inverse Gaussian regression, Gamma regression, Maximum Likelihood Estimation, Maximum Likelihood Ratio Test

Abstract

Many research data have distributions other than the normal distribution, called exponential family distributions. The exponential family of distributions includes the inverse Gaussian and Gamma distributions. There are parallels between these two distributions in terms of the kind of random variable and how well they work. Finding the optimal model using inverse Gaussian and Gamma regression on stunting data in Jepara is the goal of this study. Maximum Likelihood Estimation is used for parameter estimation, Maximum Likelihood Ratio Test is used for simultaneous parameter testing, and Wald testing is used for partial parameter testing. For this case, the best model is inverse Gaussian regression. Exclusive breastfeeding, low birth weight babies, clean drinking water facilities, and the number of Integrated Service Post (Posyandu) influence the percentage of stunting in Jepara..

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