Locally kernel weighted maximum likelihood estimator for local linear multi-predictor poisson regression
We introduce a new multi-predictor regression model based on the Poisson distribution using a local linear approach called the local linear multi-predictor Poisson regression. The optimal bandwidth in this study was selected based on the maximum likelihood cross-validation (MLCV) value. The locally...
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| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | MethodsX |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2215016125001049 |
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| Summary: | We introduce a new multi-predictor regression model based on the Poisson distribution using a local linear approach called the local linear multi-predictor Poisson regression. The optimal bandwidth in this study was selected based on the maximum likelihood cross-validation (MLCV) value. The locally kernel-weighted maximum likelihood estimator is used to estimate the regression curve at a given point. Parameter estimation was performed using the Newton-Raphson iteration method. The superior points in this research are: • A new model in regression to model multi-predictor case Poisson regression problems using a local liner approach • Optimal bandwidth selection using MCLV • Application of multi predictor case Poisson regression problems using a local liner approach to health data; namely the stunting case in East Kalimantan |
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| ISSN: | 2215-0161 |