survivalFit(miles3,miles5,miles7)

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 vectors
miles3 = miles3(:);
miles5 = miles5(:);
miles7 = miles7(:);

% Set up figure to receive datasets and fits
f_ = clf;
figure(f_);
set(f_,'Units','Pixels','Position',[654 334 680 469.45]);
legh_ = []; legt_ = {};   % handles and text for legend
ax_ = 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 function
h_ = 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 function
h_ = 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 function
h_ = 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 limits
xlim_ = get(ax_,'XLim');
if all(isfinite(xlim_))
   xlim_ = xlim_ + [-1 1] * 0.01 * diff(xlim_);
   set(ax_,'XLim',xlim_)
end

x_ = linspace(xlim_(1),xlim_(2),100);

% --- Create fit "Weibull Fit (Damping Ratio 0.3)"

% Fit this distribution to get parameter values
t_ = ~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 cdf
y_ = 1 - y_; % convert to survivor function
h_ = 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 values
t_ = ~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 cdf
y_ = 1 - y_; % convert to survivor function
h_ = 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 values
t_ = ~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 cdf
y_ = 1 - y_; % convert to survivor function
h_ = 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 legend
set(h_,'Interpreter','none');