| xfpoly does generally a good job for me, sometimes I would wish that the filling colour could be made transparent. Heinz PS 1: Is there a new version of the 2011 BetweenCurves around? PS 2: Any suggestion to make my clumsy coding more elegent, is highly welcome PS 2: BTW, since the recent lockdown, infection rates are coming down in Austria..... A=[12.628 13.942 17.077 17.054 15.594 14.976 14.796 11.875 13.448 16.504 17.717 19.447 16.099 13.302 13.762 16.032 19.492 22.098 20.425 21.087 20.649 14.268 19.402 22.525 26.862 23.514 27.603 23.851 15.830 21.570 28.682 26.109 29.974 28.727 24.705 21.458 27.087 28.401 33.670 35.119 33.962 28.120 21.301 27.244 37.467 37.715 39.490 37.569 30.480 27.098 38.366 36.951 35.097 43.759 39.299]'; d=(1:length(A))'; up=10^(d/53); M=[ones(up) up]; aa=M\A; B=inv(M'*M); DD=(1:110)'; U=10^(DD/53); MM=[ones(U) U]; yh = M*aa; //Fitted values yh to approximate measured y's e=A-yh; //Errors or residuals SSE=e'*e; //Sum of squared errors ybar=mean(A); R2=1-SSE/sum((A-ybar)^2); [m n]=size(M); MSE = SSE/(m-n-1); //Mean square error C=MSE*B // covariance matrix sig=sqrt(MSE); seb=sqrt(diag(C)); [aa seb] [n pp]=size(M); CONF=.95; alpha=1-CONF; ta2 = cdft('T',n-pp,1-alpha/2,alpha/2); //t-value for alpha/2 yhh= MM*aa; p=sig*sqrt(diag(1+MM*B*MM')); N=[yhh+ta2*p yhh-ta2*p]; polyX = [DD;flipdim(DD,1)]; polyY = [N(:,1);flipdim(N(:,2),1)]; plot2d([0 80],[1 100], style=0,logflag = "nl"); xgrid; xfpoly(polyX, polyY,6); plot(DD,MM*aa,'g.-'); plot(d,A,'b.') ; title('AUSTRIA daily infection rates per 100,000','fontsize',5); xlabel('days since 1 Feb 2021','fontsize',3); ylabel('number of infections per day per 100,000','fontsize',3); legend('data from Johns Hopkins GitHub','95% confidence range','model prediction','AUSTRIA recorded',4); |
AUSTRIA daily infection rates per 100,000 + confidence.pdf
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