update the model selection step. Beginning for the plots

[valse.git] / reports / bazar Emilie / sautDeDimension.m

diff --git a/reports/bazar Emilie/sautDeDimension.m b/reports/bazar Emilie/sautDeDimension.m
new file mode 100644 (file)
index 0000000..6dec1f8
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+++ b/reports/bazar Emilie/sautDeDimension.m
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+%Saut de dimension
+figure(1)
+vec=[0,10:100:1210];
+
+for r=vec
+    tableauBis(:,:,r+1) = tableauLassoMLE;
+    [aaaa,bbbb]= min(tableauLassoMLE(:,4)+r*tableauLassoMLE(:,2));
+    tableauBis(:,4,r+1) = tableauLassoMLE(:,4)+r*tableauLassoMLE(:,2);
+    reponse(r+1)=tableauLassoMLE(bbbb,3);
+end
+
+[x1,y1] = stairs(vec,reponse(vec+1))
+plot(x1,y1,'LineWidth',2)
+xlabel('$\kappa$','Interpreter','LaTex','FontSize', 45)
+ylabel('Model dimension','FontSize', 45)
+set(gca, 'FontSize', 40, 'fontName','Times');
+[Cx1,IA,IC] = unique(y1,'stable')
+hold on
+plot([x1(IA(2))-0.001,x1(IA(2))],[0,Cx1(2)],'--','LineWidth',2)
+plot([2*x1(IA(2))-0.001,2*x1(IA(2))],[0,Cx1(3)],'--','LineWidth',2)
+%plot([0,2*x1(IA(2))],[Cx1(3),Cx1(3)],'--','LineWidth',2)
+set(gca,'Box','off')
+set(gca,'YTick',unique([0:800:700]))
+set(gca,'XTick',unique([0:1300:1200]))
+text(x1(IA(2))-20,-20,'$\hat{\kappa}$','Interpreter','LaTex','FontSize',45)
+text(2*x1(IA(2))-20,-20,'$2 \hat{\kappa}$','Interpreter','LaTex','FontSize',45)
+%text(-80,Cx1(3),'$\hat{m}$','Interpreter','LaTex','FontSize',45)
+axis([0 1200 0 650])
+hold off
+
+%LLF pénalisé
+
+% figure(2)
+% plot(tableauLassoMLE(:,3),tableauLassoMLE(:,4)+0*tableauLassoMLE(:,2),'.','markersize', 20)
+% xlabel('Model dimension','FontSize', 30)
+% ylabel('Log-likelihood','Interpreter','LaTex','FontSize', 30)
+% set(gca, 'FontSize', 20, 'fontName','Times');
+figure(3)
+ind = find(tableauLassoMLE(:,4) >4000);
+tableauLassoMLE(ind,:)=[];
+plot(tableauLassoMLE(2:end,3),tableauLassoMLE(2:end,4)+1100*tableauLassoMLE(2:end,2),'.','markersize', 30)
+indiceInt = find(tableauLassoMLE(:,4)+1100*tableauLassoMLE(:,2)<-4401);
+indiceBis = find(tableauLassoMLE(:,3)==53);
+hold on
+plot(tableauLassoMLE(indiceInt,3),tableauLassoMLE(indiceInt,4)+1100*tableauLassoMLE(indiceInt,2),'sr','markersize', 30,'linewidth',5)
+plot(tableauLassoMLE(indiceBis,3),tableauLassoMLE(indiceBis,4)+1100*tableauLassoMLE(indiceBis,2),'dg','markersize', 30,'linewidth',5)
+xlabel('Model dimension','Interpreter','LaTex','FontSize', 45)
+ylabel('Penalized log-likelihood for $2 \hat{\kappa}$','Interpreter','LaTex','FontSize', 45)
+set(gca, 'FontSize', 30, 'fontName','Times');
+set(gcf,'Units','normal')
+set(gca,'Position',[.1 .1 .88 .85])
+hold off
+% figure(4)
+% plot(tableauLassoMLE(:,3),tableauLassoMLE(:,4)+3000*tableauLassoMLE(:,2),'.','markersize', 20)
+% xlabel('Model dimension','FontSize', 30)
+% ylabel('Penalized log-likelihood for $\kappa$ = 3000','Interpreter','LaTex','FontSize', 30)
+% set(gca, 'FontSize', 20, 'fontName','Times');
+% 
+% figure(5)
+% n2 = find(piLassoMLE(3,:)~=0,1)-1;
+% n3 = find(piLassoMLE(4,:)~=0,1)-1;
+% plot(tableauLassoMLE(:,3),tableauLassoMLE(:,4)+0*tableauLassoMLE(:,2),'.','markersize', 20)
+% xlabel('Model dimension','FontSize', 30)
+% ylabel('Log-likelihood','Interpreter','LaTex','FontSize', 30)
+% set(gca, 'FontSize', 20, 'fontName','Times');
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