source: issm/oecreview/Archive/14312-15392/ISSM-14325-14326.diff

../trunk-jpl/src/m/miscellaneous/prctile_issm.m

@@ -35 +35 @@
 
 %  check for any NaN in any columns
 
-                if ~any(isnan(x))
+                if ~any(any((isnan(x))))
                         x=sort(x,1);
                         n=size(x,1);
 

../trunk-jpl/src/m/miscellaneous/normfit_issm.m

@@ -7 +7 @@
                 alpha=0.05;
         end
 
-%  remove any NaN
+%  check for any NaN in any columns
 
-        if find(isnan(x))
-                muhat   =zeros(1,size(x,2));
-                sigmahat=zeros(1,size(x,2));
-                muci    =zeros(2,size(x,2));
-                sigmaci =zeros(2,size(x,2));
-                for j=1:size(x,2)
-                        [muhat(j),sigmahat(j),muci(:,j),sigmaci(:,j)]=normfit_issm(x(~isnan(x(:,j)),j),alpha);
-                end
-                return
-        end
+        if ~any(any((isnan(x))))
 
 %  explicitly calculate the moments
 
-        muhat   =mean(x);
-        sigmahat=std(x);
+                muhat   =mean(x);
+                sigmahat=std(x);
 
-        if (nargout>2)
-                prob=1.-alpha/2.;
+                if (nargout>2)
+                        prob=1.-alpha/2.;
 
-                if (size(x,1) == 1)
-                        % operate like matlab normfit, mean, std, etc.
-                        n=length(x);
-                else
-                        n=size(x,1);
+                        if (size(x,1) == 1)
+                                % operate like matlab normfit, mean, std, etc.
+                                n=length(x);
+                        else
+                                n=size(x,1);
+                        end
+
+                        muci    =zeros(2,length(muhat   ));
+                        sigmaci =zeros(2,length(sigmahat));
+
+                        try
+                                muci(1,:)   =muhat-tinv(prob,n-1)*sigmahat/sqrt(n);
+                                muci(2,:)   =muhat+tinv(prob,n-1)*sigmahat/sqrt(n);
+                                sigmaci(1,:)=sigmahat*sqrt((n-1)/chi2inv(prob   ,n-1));
+                                sigmaci(2,:)=sigmahat*sqrt((n-1)/chi2inv(1.-prob,n-1));
+                        catch me
+                                muci(1,:)   =muhat;
+                                muci(2,:)   =muhat;
+                                sigmaci(1,:)=sigmahat;
+                                sigmaci(2,:)=sigmahat;
+                        end
                 end
 
-                muci    =zeros(2,length(muhat   ));
-                sigmaci =zeros(2,length(sigmahat));
+        else
 
-                try
-                        muci(1,:)   =muhat-tinv(prob,n-1)*sigmahat/sqrt(n);
-                        muci(2,:)   =muhat+tinv(prob,n-1)*sigmahat/sqrt(n);
-                        sigmaci(1,:)=sigmahat*sqrt((n-1)/chi2inv(prob   ,n-1));
-                        sigmaci(2,:)=sigmahat*sqrt((n-1)/chi2inv(1.-prob,n-1));
-                catch me
-                        muci(1,:)   =muhat;
-                        muci(2,:)   =muhat;
-                        sigmaci(1,:)=sigmahat;
-                        sigmaci(2,:)=sigmahat;
+%  must loop over columns, since number of elements could be different
+
+                muhat   =zeros(1,size(x,2));
+                sigmahat=zeros(1,size(x,2));
+                muci    =zeros(2,size(x,2));
+                sigmaci =zeros(2,size(x,2));
+
+%  remove any NaN and recursively call column
+
+                for j=1:size(x,2)
+                        [muhat(j),sigmahat(j),muci(:,j),sigmaci(:,j)]=normfit_issm(x(~isnan(x(:,j)),j),alpha);
                 end
         end