require(geoR) ## ## Comparando simulações com diferentes valores de $\phi$ ## for(i in 0:9){ jpeg(paste("phi",i, ".jpg", sep=""), wid=600, hei=600) par(mfrow=c(2,2), mar=c(1.5,.5,1.5,0), mgp=c(1, .5, 0)) set.seed(234+i) ap1 <- grf(961, grid="reg", cov.pars=c(1, 0)) set.seed(234+i) ap2 <- grf(961, grid="reg", cov.pars=c(1, .1)) set.seed(234+i) ap3 <- grf(961, grid="reg", cov.pars=c(1, .25)) set.seed(234+i) ap4 <- grf(961, grid="reg", cov.pars=c(1, .75)) iis <- range(c(ap1$data, ap2$data, ap3$data, ap4$data)) image(ap1, xlab="", ylab="", col=gray(seq(1,0,l=21)), zlim=iis) mtext(expression(phi==0), cex=1.5) image(ap2, xlab="", ylab="", col=gray(seq(1,0,l=21)), zlim=iis) mtext(expression(phi==0.10), cex=1.5) image(ap3, xlab="", ylab="", col=gray(seq(1,0,l=21)), zlim=iis) mtext(expression(phi==0.25), cex=1.5) image(ap4, xlab="", ylab="", col=gray(seq(1,0,l=21)), zlim=iis) mtext(expression(phi==0.75), cex=1.5) dev.off() } ## ## Comparando simulações com diferentes valores de $\sigma^2$ ## for(i in 0:9){ jpeg(paste("sigma",i, ".jpg", sep=""), wid=600, hei=600) par(mfrow=c(2,2), mar=c(1.5,.5,1.5,0), mgp=c(1, .5, 0)) set.seed(234+i) ap1 <- grf(961, grid="reg", cov.pars=c(1, 0.3)) set.seed(234+i) ap2 <- grf(961, grid="reg", cov.pars=c(2, .3)) set.seed(234+i) ap3 <- grf(961, grid="reg", cov.pars=c(3, .3)) set.seed(234+i) ap4 <- grf(961, grid="reg", cov.pars=c(5, .3)) iis <- range(c(ap1$data, ap2$data, ap3$data, ap4$data)) image(ap1, xlab="", ylab="", col=gray(seq(1,0,l=21)), zlim=iis) mtext(expression(sigma^2==1), cex=1.5) image(ap2, xlab="", ylab="", col=gray(seq(1,0,l=21)), zlim=iis) mtext(expression(sigma^2==2), cex=1.5) image(ap3, xlab="", ylab="", col=gray(seq(1,0,l=21)), zlim=iis) mtext(expression(sigma^2==3), cex=1.5) image(ap4, xlab="", ylab="", col=gray(seq(1,0,l=21)), zlim=iis) mtext(expression(sigma^2==5), cex=1.5) dev.off() } ## ## Comparando simulações com diferentes níveis de ruído ## for(i in 0:9){ jpeg(paste("tau",i, ".jpg", sep=""), wid=600, hei=600) par(mfrow=c(2,2), mar=c(1.5,.5,1.5,0), mgp=c(1, .5, 0)) set.seed(234+i) ap1 <- grf(961, grid="reg", cov.pars=c(1, 0.3), nug=0) set.seed(234+i) ap2 <- grf(961, grid="reg", cov.pars=c(.75, .3), nug=0.25) set.seed(234+i) ap3 <- grf(961, grid="reg", cov.pars=c(.5, .3), nug=0.5) set.seed(234+i) ap4 <- grf(961, grid="reg", cov.pars=c(.1, .3), nug=.9) iis <- range(c(ap1$data, ap2$data, ap3$data, ap4$data)) image(ap1, xlab="", ylab="", col=gray(seq(1,0,l=21)), zlim=iis) mtext(expression(paste(sigma^2==1, " e ", tau^2 == 0), cex=1.5)) image(ap2, xlab="", ylab="", col=gray(seq(1,0,l=21)), zlim=iis) mtext(expression(paste(sigma^2==0.75, " e ", tau^2 == 0.25), cex=1.5)) image(ap3, xlab="", ylab="", col=gray(seq(1,0,l=21)), zlim=iis) mtext(expression(paste(sigma^2==0.5, " e ", tau^2 == 0.5), cex=1.5)) image(ap4, xlab="", ylab="", col=gray(seq(1,0,l=21)), zlim=iis) mtext(expression(paste(sigma^2==0.1, " e ", tau^2 == 0.9), cex=1.5)) dev.off() } ## ## Comparando simulações com diferentes funções de correlação ## for(i in 0:9){ jpeg(paste("model",i, ".jpg", sep=""), wid=600, hei=600) par(mfrow=c(2,2), mar=c(1.5,.5,1.5,0), mgp=c(1, .5, 0)) set.seed(234+i) ap1 <- grf(961, grid="reg", cov.pars=c(1, .25)) set.seed(234+i) ap2 <- grf(961, grid="reg", cov.pars=c(1, .75), cov.model="sph") set.seed(234+i) ap3 <- grf(961, grid="reg", cov.pars=c(1, .14), kappa=2) set.seed(234+i) ap4 <- grf(961, grid="reg", cov.pars=c(1, .095), kappa=5) iis <- range(c(ap1$data, ap2$data, ap3$data, ap4$data)) image(ap1, xlab="", ylab="", col=gray(seq(1,0,l=21)), zlim=iis) mtext("exponencial", cex=1.5) image(ap2, xlab="", ylab="", col=gray(seq(1,0,l=21)), zlim=iis) mtext("esferico", cex=1.5) image(ap3, xlab="", ylab="", col=gray(seq(1,0,l=21)), zlim=iis) mtext(expression(paste("Matern com ", kappa==2)), cex=1.5) image(ap4, xlab="", ylab="", col=gray(seq(1,0,l=21)), zlim=iis) mtext(expression(paste("Matern com ", kappa==5)), cex=1.5) dev.off() } ## ## Comparando simulações com diferentes anisotropias ## for(i in 0:9){ jpeg(paste("aniso",i, ".jpg", sep=""), wid=600, hei=600) par(mfrow=c(2,2), mar=c(1.5,.5,1.5,0), mgp=c(1, .5, 0)) set.seed(234+i) ap1 <- grf(961, grid="reg", cov.pars=c(1, .25), aniso.pars=c(pi/4, 2)) set.seed(234+i) ap2 <- grf(961, grid="reg", cov.pars=c(1, .25), aniso.pars=c(pi/4, 4)) set.seed(234+i) ap3 <- grf(961, grid="reg", cov.pars=c(1, .25), aniso.pars=c(2*pi/3, 2)) set.seed(234+i) ap4 <- grf(961, grid="reg", cov.pars=c(1, .25), aniso.pars=c(2*pi/3, 4)) iis <- range(c(ap1$data, ap2$data, ap3$data, ap4$data)) image(ap1, xlab="", ylab="", col=gray(seq(1,0,l=21)), zlim=iis) mtext(expression(paste(phi[a]==pi/4, " \ ,\ ", phi[r] == 2), cex=1.5)) image(ap2, xlab="", ylab="", col=gray(seq(1,0,l=21)), zlim=iis) mtext(expression(paste(phi[a]==pi/4, " \ ,\ ", phi[r] == 4), cex=1.5)) image(ap3, xlab="", ylab="", col=gray(seq(1,0,l=21)), zlim=iis) mtext(expression(paste(phi[a]== 2*pi/3, " \ ,\ ", phi[r] == 2), cex=1.5)) image(ap4, xlab="", ylab="", col=gray(seq(1,0,l=21)), zlim=iis) mtext(expression(paste(phi[a]==2*pi/3, " \ ,\ ", phi[r] == 4), cex=1.5)) dev.off() } system("convert -delay 300 phi*.jpg phiD2.gif") system("convert -delay 300 sigma*.jpg sigmaD2.gif") system("convert -delay 300 tau*.jpg tauD2.gif") system("convert -delay 300 model*.jpg modelD2.gif") system("convert -delay 300 aniso*.jpg anisoD2.gif")