CARBAYESST:

[gadouaka]

Bonjour
j'ai implémenté mon modèle suivant :
modele1 <- CARBayesST::ST.CARlinear(RubelaTmax+Precipit + Q_poor + Densite, family = "poisson", data = DISTRICT, W=W,burnin = 1000, n.sample = 21000, thin = 10)
modele1 ##
a chaque execution du modele, les valeurs des parametres du modele changent.
Comment pourrais je faire pour stabiliser les valeurs de parametres?
modele1 <- CARBayesST::ST.CARlinear(RubelaTmax+Precipit + Q_poor + Densite, family = "poisson", data = DISTRICT, W=W,burnin = 1000, n.sample = 21000, thin = 10)
Setting up the model.
Generating 2000 post burnin and thinned (if requested) samples.
|============================================================================================| 100%
Summarising results.
Finished in 12.8 seconds.
Warning message:
In mat2listw(W) :
style is M (missing); style should be set to a valid value

modele1 ##

#################

Model fitted

#################
Likelihood model - Poisson (log link function)
Latent structure model - Spatially autocorrelated linear time trends
Regression equation - Rubela ~ Tmax + Precipit + Q_poor + Densite

############

Results

############
Posterior quantities for selected parameters and DIC

           Mean     2.5%   97.5% n.effective Geweke.diag

(Intercept) 4.2766 -10.0434 17.5663 36.3 -0.1
Tmax -0.0190 -0.4353 0.3997 36.5 0.1
Precipit -0.0178 -0.0350 -0.0007 132.4 0.6
Q_poor -0.0542 -0.0879 -0.0158 22.8 -1.4
Densite -0.0001 -0.0278 0.0266 37.5 1.1
alpha 2.3620 1.5972 3.1459 242.8 0.8
tau2.int 5.4238 1.4953 15.7227 440.1 0.7
tau2.slo 20.9719 6.7720 61.3077 570.1 1.8
rho.int 0.2250 0.0054 0.7679 394.7 1.2
rho.slo 0.1174 0.0026 0.5219 558.0 0.5

DIC = 848.3213 p.d = 51.65122 LMPL = -599.1591

modele1 <- CARBayesST::ST.CARlinear(Rubela~Tmax+Precipit + Q_poor + Densite, family = "poisson", data = DISTRICT, W=W,burnin = 1000, n.sample = 21000, thin = 10)
Setting up the model.
Generating 2000 post burnin and thinned (if requested) samples.
|============================================================================================| 100%
Summarising results.
Finished in 13.7 seconds.
Warning message:
In mat2listw(W) :
style is M (missing); style should be set to a valid value
modele1 ##

#################

Model fitted

#################
Likelihood model - Poisson (log link function)
Latent structure model - Spatially autocorrelated linear time trends
Regression equation - Rubela ~ Tmax + Precipit + Q_poor + Densite

############

Results

############
Posterior quantities for selected parameters and DIC

           Mean     2.5%   97.5% n.effective Geweke.diag

(Intercept) 1.8843 -15.2947 16.9245 30.0 -0.5
Tmax 0.0447 -0.3809 0.5555 30.2 0.7
Precipit -0.0158 -0.0334 0.0011 128.1 -1.1
Q_poor -0.0483 -0.0812 -0.0133 26.0 -1.5
Densite -0.0036 -0.0416 0.0345 17.0 0.6
alpha 2.3941 1.6212 3.1480 245.4 0.6
tau2.int 4.7817 1.3654 12.9956 415.2 -3.2
tau2.slo 22.0837 6.5986 65.9074 423.4 0.6
rho.int 0.1951 0.0047 0.7118 357.6 -1.7
rho.slo 0.1217 0.0021 0.5580 359.3 0.3

DIC = 849.2968 p.d = 52.13339 LMPL = -578.5549

[gadouaka]

comment pourrais je faire pour stabiliser les parametres du modele?