Functional SAR Model
Wilmer Pineda-R\'ios, Ram\'on Giraldo
TL;DR
This paper introduces a functional spatial autoregressive (SAR) model with continuous-time process variables, providing a maximum likelihood estimation method and proving its convergence properties.
Contribution
It presents a novel functional SAR model with a maximum likelihood estimation procedure and theoretical convergence guarantees.
Findings
Establishment of a maximum likelihood estimator for the model.
Proofs of convergence in probability and almost sure convergence.
Framework for modeling spatial dependence with continuous-time functional data.
Abstract
In this paper, we study a functional SAR model in which explanatory variables are sampling points of a continuous-time process. We propose a procedure for the maximum likelihood estimation for the spatial parameter dependence and the parameter function. Both convergence in probability and almost sure convergence of this estimator are stated.
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Taxonomy
TopicsSpatial and Panel Data Analysis · Soil Geostatistics and Mapping · Statistical Methods and Inference