Abstract The spatial lag model (SLM) has been widely studied in the literature for spatialised data modeling in various disciplines such as geography, economics, demography, regional sciences, etc. This is an extension of the classical linear model that takes into account the proximity of spatial units in modeling. In this paper, we propose a Bayesian estimation of the functional spatial lag (FSLM) model. The Bayesian MCMC technique is used as a method of estimation for the parameters of the model. A simulation study is conducted in order to compare the results of the Bayesian functional spatial lag model with the functional spatial lag model and the functional linear model. As an illustration, the proposed Bayesian functional spatial lag model is used to establish a relationship between the unemployment rate and the curves of illiteracy rate observed in the 45 departments of Senegal.

中文翻译：

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功能空间滞后模型的贝叶斯估计

摘要空间滞后模型（SLM）在文献中已被广泛研究，用于地理，经济学，人口统计学，区域科学等各个学科的空间化数据建模。这是考虑线性关系的经典线性模型的扩展在建模中的空间单位。在本文中，我们提出了功能空间滞后（FSLM）模型的贝叶斯估计。贝叶斯MCMC技术被用作估计模型参数的方法。为了将贝叶斯功能空间滞后模型与功能空间滞后模型和功能线性模型进行比较，进行了仿真研究。举例来说，