diff --git a/inst/boot1way.m b/inst/boot1way.m
index 57afd651..61411f81 100755
--- a/inst/boot1way.m
+++ b/inst/boot1way.m
@@ -259,7 +259,7 @@
   end
   if ((nboot(2) == 0) && (~ strcmp (func2str (bootfun), 'mean')))
     if (~ exist ('jackknife','file'))
-      if (ISOCTAVE); 
+      if (ISOCTAVE)
         warning ('boot1way:jackfail', cat (2, '''jackknife'' function from', ...
                  ' statistics package not found. nboot(2) set to 100.'))
       else
@@ -434,7 +434,7 @@
         theta(j) = mean (data(g == gk(j), :));
         % Quick analytical calculation for the standard error of the mean
         SE(j) = std (data(g == gk(j), :), 0) / sqrt (nk(j));
-        if (j == 1); se_method = 'Calculated without resampling'; end;
+        if (j == 1); se_method = 'Calculated without resampling'; end
       else
         theta(j) = bootfun (data(g == gk(j), :));
         % If requested, compute unbiased estimates of the standard error using
@@ -442,7 +442,7 @@
         jackstat = jackknife (bootfun, data(g == gk(j), :));
         SE(j) = sqrt ((nk(j) - 1) / nk(j) * ...
                 sum (((mean (jackstat) - jackstat)).^2));
-        if (j == 1); se_method = 'Leave-one-out jackknife'; end;
+        if (j == 1); se_method = 'Leave-one-out jackknife'; end
       end
     else
       % Compute unbiased estimate of the standard error by balanced bootknife
@@ -453,7 +453,7 @@
       bootout = bootknife (data(g == gk(j), :), [nboot(2), 0], bootfun, ...
                            NaN, [], 0, [], [], ISOCTAVE, false, true);
       SE(j) = bootout.std_error;
-      if (j==1); se_method = 'Balanced, bootknife resampling'; end;
+      if (j==1); se_method = 'Balanced, bootknife resampling'; end
     end
     Var(j) = ((nk(j) - 1) / (N - k)) * SE(j)^2;
   end
diff --git a/inst/bootlm.m b/inst/bootlm.m
index 32fb61f0..262b7e50 100755
--- a/inst/bootlm.m
+++ b/inst/bootlm.m
@@ -545,7 +545,7 @@
         case 'seed'
           SEED = value;
         otherwise
-          error (sprintf ('bootlm: parameter %s is not supported', name))
+          error ('bootlm: parameter %s is not supported', name)
       end
     end
 
@@ -681,8 +681,7 @@
             % Check whether all the columns sum to 0
             if (any (abs (sum (CONTRASTS{i})) > eps ('single')))
               contr_sum_to_zero (i) = false;
-              warning (sprintf ( ...
-              'Note that the CONTRASTS for predictor %u do not sum to zero', i))
+              warning ('Note that the CONTRASTS for predictor %u do not sum to zero', i)
             else
               contr_sum_to_zero (i) = true;
             end
@@ -690,8 +689,7 @@
             if (any (abs (reshape (cov2corr (cov (CONTRASTS{i})) - ...
                                      eye (size (CONTRASTS{i}, 2)), [], 1)) ...
                                      > eps ('single')))
-              warning (sprintf ( ...
-              'Note that the CONTRASTS for predictor %u are not orthogonal', i))
+              warning ('Note that the CONTRASTS for predictor %u are not orthogonal', i)
             end
           else
             if (~ ismember (lower (CONTRASTS{i}), ...
@@ -715,8 +713,7 @@
     if (~ isempty (DIM))
       for i = 1:K
         if (~ contr_sum_to_zero (i))
-          warning (sprintf ( ...
-                    'CONTRASTS for predictor %u have been set to ''anova''', i))
+          warning ('CONTRASTS for predictor %u have been set to ''anova''', i)
         end
       end
       CONTRASTS(~ contr_sum_to_zero) = {'anova'};
@@ -1332,7 +1329,7 @@
         plot (ax4_xlim, ones (1, 2), 'k--');
         hold off;
         arrayfun (@(i) text (DI(i), D(DI(i)), ...
-                             sprintf ('  %u', DI(i))), [1:min(nk,n)]);
+                             sprintf ('  %u', DI(i))), 1:min(nk,n));
         xlim (ax4_xlim); ylim (ax4_ylim);
 
         set (findall ( gcf, '-property', 'FontSize'), 'FontSize', 7)
@@ -1486,7 +1483,7 @@
       df(Nm+i) = prod (df(I-1));
       termcols(1+Nm+i) = prod (df(I-1) + 1);
       tmp = ones (n,1);
-      for j = 1:numel(I);
+      for j = 1:numel(I)
         tmp = num2cell (tmp, 1);
         for k = 1:numel(tmp)
           tmp{k} = bsxfun (@times, tmp{k}, X{I(j)});
diff --git a/matlab/statistics-resampling.mltbx b/matlab/statistics-resampling.mltbx
index b4e91901..232f33a5 100644
Binary files a/matlab/statistics-resampling.mltbx and b/matlab/statistics-resampling.mltbx differ
diff --git a/matlab/statistics-resampling.prj b/matlab/statistics-resampling.prj
index ef146b86..a17adbe1 100644
--- a/matlab/statistics-resampling.prj
+++ b/matlab/statistics-resampling.prj
@@ -1,5 +1,5 @@
 <deployment-project plugin="plugin.toolbox" plugin-version="1.0">
-  <configuration build-checksum="2451036051" file="Y:\Documents\GitHub\statistics-resampling\matlab\statistics-resampling.prj" location="Y:\Documents\GitHub\statistics-resampling\matlab" name="statistics-resampling" target="target.toolbox" target-name="Package Toolbox">
+  <configuration build-checksum="2919770292" file="Y:\Documents\GitHub\statistics-resampling\matlab\statistics-resampling.prj" location="Y:\Documents\GitHub\statistics-resampling\matlab" name="statistics-resampling" target="target.toolbox" target-name="Package Toolbox">
     <param.appname>statistics-resampling</param.appname>
     <param.authnamewatermark>Andrew Penn</param.authnamewatermark>
     <param.email>andy.c.penn@gmail.com</param.email>
@@ -53,6 +53,10 @@
     </fileset.rootdir>
     <fileset.rootfiles>
       <file>Y:\Documents\GitHub\statistics-resampling\inst\boot.m</file>
+      <file>Y:\Documents\GitHub\statistics-resampling\inst\boot.mexa64</file>
+      <file>Y:\Documents\GitHub\statistics-resampling\inst\boot.mexmaci64</file>
+      <file>Y:\Documents\GitHub\statistics-resampling\inst\boot.mexw32</file>
+      <file>Y:\Documents\GitHub\statistics-resampling\inst\boot.mexw64</file>
       <file>Y:\Documents\GitHub\statistics-resampling\inst\boot1way.m</file>
       <file>Y:\Documents\GitHub\statistics-resampling\inst\bootbayes.m</file>
       <file>Y:\Documents\GitHub\statistics-resampling\inst\bootcdf.m</file>
@@ -70,6 +74,10 @@
       <file>Y:\Documents\GitHub\statistics-resampling\inst\sampszcalc.m</file>
       <file>Y:\Documents\GitHub\statistics-resampling\inst\smoothmad.m</file>
       <file>Y:\Documents\GitHub\statistics-resampling\inst\smoothmedian.m</file>
+      <file>Y:\Documents\GitHub\statistics-resampling\inst\smoothmedian.mexa64</file>
+      <file>Y:\Documents\GitHub\statistics-resampling\inst\smoothmedian.mexmaci64</file>
+      <file>Y:\Documents\GitHub\statistics-resampling\inst\smoothmedian.mexw32</file>
+      <file>Y:\Documents\GitHub\statistics-resampling\inst\smoothmedian.mexw64</file>
     </fileset.rootfiles>
     <fileset.depfun.included />
     <fileset.depfun.excluded />