\begin{abstract}
The autologistic model is flexible for 
modeling the incidence diseases in plants. 
The single estimatiom method is using pseudo-likelihood. 
The inference is made using bootstrap saw Gibbs sampler. 
This procedure is computational very expensive and we consider 
Monte Carlo method for test the spatial dependence parameters. 
Also we consider an extencion of the model, for consider 
the temporal dimension in data with some evaluations 
in time. The methodologies was applied in Citrus 
Sudden Death and the results are compared. In three models 
analyzed, the significance of neighborhood in lines covariate 
was verified in both, bootstrap procedure and Monte Carlo method. 
The functions implemented in R are available for download in 
Rcitrus package.
\end{abstract}

\begin{kwd}
Autologistic model, Gibbs sampling, Citrus Sudden Death
\end{kwd}
