Abstract
This paper presents the conditional least squares (CLS) estimation procedure for the class of first-order spatial integer-valued autoregressive processes, denote by SINAR(1, 1). We derive the asymptotic properties of the CLS estimators of model parameters. Simulation results are presented to assess the performance of estimators under finite sample sizes and under equidispersion and overdispersion. To illustrate the proposed methodology, two grid sampled count data sets are analyzed.
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