function survivalFit(miles3,miles5,miles7)%SURVIVALFIT    Create plot of datasets and fits%   SURVIVALFIT(MILES3,MILES5,MILES7)%   Creates a plot, similar to the plot in the main distribution fitting%   window, using the data that you provide as input.  You can%   apply this function to the same data you used with dfittool%   or with different data.  You may want to edit the function to%   customize the code and this help message.%%   Number of datasets:  3%   Number of fits:  3% This function was automatically generated on 08-Jan-2008 09:12:16 % Data from dataset "Damping Ratio 0.3":%    Y = miles3 % Data from dataset "Damping Ratio 0.5":%    Y = miles5 % Data from dataset "Damping Ratio 0.7":%    Y = miles7 % Force all inputs to be column vectorsmiles3 = miles3(:);miles5 = miles5(:);miles7 = miles7(:);% Set up figure to receive datasets and fitsf_ = clf;figure(f_);set(f_,'Units','Pixels','Position',[654 334 680 469.45]);legh_ = []; legt_ = {};   % handles and text for legendax_ = newplot;set(ax_,'Box','on');hold on;% --- Plot data originally in dataset "Damping Ratio 0.3"t_ = ~isnan(miles3);Data_ = miles3(t_);[Y_,X_] = ecdf(Data_,'Function','survivor'...              );  % compute empirical functionh_ = stairs(X_,Y_);set(h_,'Color',[0.333333 0 0.666667],'LineStyle','-', 'LineWidth',1);xlabel('Data');ylabel('Survivor function')legh_(end+1) = h_;legt_{end+1} = 'Damping Ratio 0.3';% --- Plot data originally in dataset "Damping Ratio 0.5"t_ = ~isnan(miles5);Data_ = miles5(t_);[Y_,X_] = ecdf(Data_,'Function','survivor'...              );  % compute empirical functionh_ = stairs(X_,Y_);set(h_,'Color',[0.333333 0.666667 0],'LineStyle','-', 'LineWidth',1);xlabel('Data');ylabel('Survivor function')legh_(end+1) = h_;legt_{end+1} = 'Damping Ratio 0.5';% --- Plot data originally in dataset "Damping Ratio 0.7"t_ = ~isnan(miles7);Data_ = miles7(t_);[Y_,X_] = ecdf(Data_,'Function','survivor'...              );  % compute empirical functionh_ = stairs(X_,Y_);set(h_,'Color',[0 0 0],'LineStyle','-', 'LineWidth',1);xlabel('Data');ylabel('Survivor function')legh_(end+1) = h_;legt_{end+1} = 'Damping Ratio 0.7';% Nudge axis limits beyond data limitsxlim_ = get(ax_,'XLim');if all(isfinite(xlim_))   xlim_ = xlim_ + [-1 1] * 0.01 * diff(xlim_);   set(ax_,'XLim',xlim_)endx_ = linspace(xlim_(1),xlim_(2),100);% --- Create fit "Weibull Fit (Damping Ratio 0.3)"% Fit this distribution to get parameter valuest_ = ~isnan(miles3);Data_ = miles3(t_);% To use parameter estimates from the original fit:%     p_ = [ 197384.2484336, 3.968708696396];p_ = wblfit(Data_, 0.05);y_ = wblcdf(x_,p_(1), p_(2)); % compute cdfy_ = 1 - y_; % convert to survivor functionh_ = plot(x_,y_,'Color',[1 0 0],...          'LineStyle','-', 'LineWidth',2,...          'Marker','none', 'MarkerSize',6);legh_(end+1) = h_;legt_{end+1} = 'Weibull Fit (Damping Ratio 0.3)';% --- Create fit "Weibull Fit (Damping Ratio 0.5)"% Fit this distribution to get parameter valuest_ = ~isnan(miles5);Data_ = miles5(t_);% To use parameter estimates from the original fit:%     p_ = [ 164694.3864163, 49994.13306482];pargs_ = cell(1,2);[pargs_{:}] = normfit(Data_, 0.05);p_ = [pargs_{:}];y_ = normcdf(x_,p_(1), p_(2)); % compute cdfy_ = 1 - y_; % convert to survivor functionh_ = plot(x_,y_,'Color',[0 0 1],...          'LineStyle','-', 'LineWidth',2,...          'Marker','none', 'MarkerSize',6);legh_(end+1) = h_;legt_{end+1} = 'Weibull Fit (Damping Ratio 0.5)';% --- Create fit "Weibull Fit (Damping Ratio 0.7)"% Fit this distribution to get parameter valuest_ = ~isnan(miles7);Data_ = miles7(t_);% To use parameter estimates from the original fit:%     p_ = [ 145835.2832132, 3.627387845666];p_ = wblfit(Data_, 0.05);y_ = wblcdf(x_,p_(1), p_(2)); % compute cdfy_ = 1 - y_; % convert to survivor functionh_ = plot(x_,y_,'Color',[0.666667 0.333333 0],...          'LineStyle','-', 'LineWidth',2,...          'Marker','none', 'MarkerSize',6);legh_(end+1) = h_;legt_{end+1} = 'Weibull Fit (Damping Ratio 0.7)';hold off;leginfo_ = {'Orientation', 'vertical', 'Location', 'NorthEast'}; h_ = legend(ax_,legh_,legt_,leginfo_{:});  % create legendset(h_,'Interpreter','none');