minor bug fix

- fixed broadcast warning in smoothmedian
- fixed MarkerFace warning in Octave

Author: acp29

inst/bootnhst.m

@@ -452,18 +452,18 @@
 
     % Plot graph of the difference in bootfun for each comparison with 95% confidence intervals
     figure;
-    nc = size(c,1);                             % Calculate number of comparisons to plot
-    plot([0;0],[0;nc+1]','k:');                 % Plot vertical dashed line at 0 effect
-    set(gca,'Ydir','reverse')                   % Flip y-axis direction
-    ylim([0.5,nc+0.5]);                             % Set y-axis limits
-    hold on                                     % Enable plotting new data on the same axis
+    nc = size(c,1);                               % Calculate number of comparisons to plot
+    plot([0;0],[0;nc+1]','k:');                   % Plot vertical dashed line at 0 effect
+    set(gca,'Ydir','reverse')                     % Flip y-axis direction
+    ylim([0.5,nc+0.5]);                           % Set y-axis limits
+    hold on                                       % Enable plotting new data on the same axis
     for i=1:nc
       if c(i,7) < 0.05
-        plot(c(i,5),i,'or','MarkerFace','r')    % Plot marker for the difference in bootfun 
-        plot([c(i,8),c(i,9)],i*ones(2,1),'r-')  % Plot line for each confidence interval 
+        plot(c(i,5),i,'or','MarkerFaceColor','r') % Plot marker for the difference in bootfun 
+        plot([c(i,8),c(i,9)],i*ones(2,1),'r-')    % Plot line for each confidence interval 
       else
-        plot(c(i,5),i,'ob','MarkerFace','b')    % Plot marker for the difference in bootfun 
-        plot([c(i,8),c(i,9)],i*ones(2,1),'b-')  % Plot line for each confidence interval 
+        plot(c(i,5),i,'ob','MarkerFaceColor','b') % Plot marker for the difference in bootfun 
+        plot([c(i,8),c(i,9)],i*ones(2,1),'b-')    % Plot line for each confidence interval 
       end
     end
     hold off

inst/param/smoothmedian.m

@@ -254,9 +254,10 @@
     xj = (x(j(q),:) - h) .*... 
              midrange(ones(1,l),:) +...
              centre(ones(1,l),:);   % backtransform data when recreating xj
+    tmp = p(ones(l,1),:);
     % Calculate standard error(s) for the computed value(s) of the smoothed median
-    v0 = (1/(m*(m-1))) * sum((((xi-p).^2+(xj-p).^2).^(-3/2) .* (xi-xj).^2));
-    v  = (1/(m*(m-1))) * sum(((xi+xj-2*p)./(((xi-p).^2+(xj-p).^2).^(0.5))).^2);
+    v0 = (1/(m*(m-1))) * sum((((xi-tmp).^2+(xj-tmp).^2).^(-3/2) .* (xi-xj).^2));
+    v  = (1/(m*(m-1))) * sum(((xi+xj-2*tmp)./(((xi-tmp).^2+(xj-tmp).^2).^(0.5))).^2);
     stderr = sqrt((v0.^(-2)) .* v / m);
     % Assign 0 to stderr for x columns with 0 variance 
     stderr(midrange==0) = 0;