plot_gpd.m

来自「极值理论中各种函数及图像的程序。matlab实现。」· M 代码 · 共 69 行

function out=plot_gpd(resgpd),
%Menu driven plotting facility for GPD fit
%
% USAGE: out=plot_gpd(gpdres)
%
%resgpd: Structure obtained from a former GPD fit i.e. resgpd=gpd(...)

data=resgpd.data;
threshold=resgpd.threshold;
xi=resgpd.par_ests(1);
beta=resgpd.par_ests(2);

r=1;
while r~=0, 
clc
r=input('\n\n\n\n\n\n\n\n Enter your choice for plotting !!! \n\n Enter (1) for exceedance distribution \n Enter (2) for tail of underlying distrbution \n Enter (3) for scatterplot of residuals \n Enter (4) for QQ plot of residuals \n Enter (0) to exit \n                 >');
while (r~=1) & (r~=2) &(r~=3) & (r~=4) & (r~=0),
    r=input('!!!Enter either 0,1,2,3,4 >');

end
if r>=3,
    excess=data-threshold;
    res=log(1+(xi*excess)/beta)/xi;
 end
if r==3,
    plot(res,'.')
    out=res;
    sm=csaps(1:length(res),res(1:end),0.00005,1:length(res));    
    hold on
    plot(1:length(res),sm,'k');
    xlabel('Ordering');
    ylabel('Residuals');
    hold off
end
if r==4
    out=qplot(res,0);
end
if (r==1)|(r==2),
    x=qgpd(linspace(0,1,1000),xi,threshold,beta);
    ypoints=ppoints(sort(data));
    y=pgpd(x,xi,threshold,beta);
    if r==1,
        semilogx(sort(data),ypoints,'.');
        out=[sort(data) ypoints'];
        hold on
        plot(x,y,'k');
     	  hold off   
        xlabel('x (on log scale)');
        ylabel('Fu(x-u)');
    end

    if r==2,
        prob = resgpd.p_less_thresh;
        ypoints = (1 - prob) * (1 - ypoints);
		  y = (1 - prob) * (1 - y);
        loglog(sort(data),ypoints,'.');
        hold on
        plot(x(y>0),y(y>0),'k');
        xlabel('x (on log scale)');
        ylabel('1-F(x) (on log scale)');
        set(gca,'yticklabel',get(gca,'ytick'));
        set(gca,'ytickmode','manual');
        hold off
        out=[sort(data) ypoints'];    
    end
end
end