Parameter Estimation in Spatial Autoregressive Models with Missing Data and Measurement Errors
This study addresses the problem of parameter estimation in spatial autoregressive models with missing data and measurement errors in covariates. Specifically, a corrected likelihood estimation approach is employed to rectify the bias in the log-maximum likelihood function induced by measurement err...
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| Autori principali: | , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
MDPI AG
2024-05-01
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| Serie: | Axioms |
| Soggetti: | |
| Accesso online: | https://www.mdpi.com/2075-1680/13/5/315 |
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