  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. The extension of the SLM model in the functional framework (the FSLM
model) as well as its estimation by the truncated maximum likelihood technique
have been proposed by \cite{Ahmed}. In this paper, we propose a Bayesian
estimation of the FSLM model. The Bayesian MCMC technique is used as estimation
methods of the parameters of the model. A simulation study is conducted in
order to compare the results of the Bayesian estimation method with the
truncated maximum likelihood method. As an illustration, the proposed Bayesian
method is used to establish a relationship between the unemployment rate and
the curves of illiteracy rate observed in the 45 departments of Senegal.
