Parameter estimation of inverse Gaussian regression with application to the resilience of culinary MSMEs during extraordinary events
| Main Author: | Nisa, Eva Khoirun |
|---|---|
| Format: | Monograph PeerReviewed Book |
| Bahasa: | eng |
| Terbitan: |
Fakultas Sains Dan Teknologi
|
| Subjects: | |
| Online Access: |
https://eprints.walisongo.ac.id/id/eprint/19712/1/makalah%20edu%20stem.pdf https://eprints.walisongo.ac.id/id/eprint/19712/ |
Daftar Isi:
- Some cases in environmental studies show that the response variable follows an exponential family, for instance an inverse Gaussian distribution. Suppose that positive response variable depend on a set of predictors, we can model it using an inverse Gaussian regression. In this study, the parameter estimation of the inverse Gaussian regression using Maximum Likelihood Estimation (MLE). The parameter estimation produces a nonlinear form so that it is optimized. The optimization methods used are Fisher scoring and Broyden-Fletcher-Goldfarb-Shanno (BFGS). In this study, inverse Gaussian regression will be applied to the resilience data of culinary The Micro, small, and medium enterprises (MSMEs) during extraordinary events. This is an alternative considering the inverse Gaussian has never been applied outside of survival field. The aim of this study to obtain an inverse Gaussian regression parameter estimator and factors that influence the resilience of culinary MSMEs from the inverse Gaussian regression application. Fisher scoring and BFGS optimization produce almost the same parameter estimation values. Its application produces cost and service time that affect the resilience of culinary MSMEs during extraordinary events