Often in practice the data on the mortality of a living unit correlation is due to the location of the observations in the study‎. ‎One of the most important issues in the analysis of survival data with spatial dependence‎, ‎is estimation of the parameters and prediction of the unknown values in known sites based on observations vector‎. ‎In this paper to analyze this type of survival‎, ‎Cox regression model with piecewise exponential function used as a hazard and spatial dependence as a Gaussian random field and as a latent variable is added to the model‎. ‎Because there is no closed form for posterior distribution and full conditional distributions‎, ‎also long computing for Markov chain Monte Carlo algorithms‎, ‎to analyze the model are used the approximate Bayesian methods‎.
‎A practical example of how to implement an approximate Bayesian approach is presented‎.