What is it about?
We establish conditions for the existence and uniqueness of the maximum likelihood estimator (MLE) of the model parameters. We then employ the MLE’s asymptotic normality to propose methods for testing spatio-temporal and spatial dependencies.
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Why is it important?
We can use this model to construct prediction maps to better understand the transmission of plant illness in time and space.
Perspectives
The model can be very useful for making predictions. Furthermore, programming is relatively simple.
Felipe Peraza Garay
Universidad Autonoma de Sinaloa
Read the Original
This page is a summary of: Inference for the Analysis of Ordinal Data with Spatio-Temporal Models, The International Journal of Biostatistics, April 2020, De Gruyter,
DOI: 10.1515/ijb-2019-0101.
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