jstat - npm Package Compare versions

Comparing version 1.8.1 to 1.8.2

package.json

 {
   "name": "jstat",
-  "version": "1.8.1",
+  "version": "1.8.2",
   "description": "Statistical Library for JavaScript",
@@ -5,0 +5,0 @@ "homepage": "http://github.com/jstat/jstat",

src/core.js

@@ -51,4 +51,2 @@ var jStat = (function(Math, undefined) {
 jStat._init = function _init(args) {
-  var i;
-
   // If first argument is an array, must be vector or matrix.
@@ -107,2 +105,10 @@ if (isArray(args[0])) {
 
+jStat._random_fn = Math.random;
+jStat.setRandom = function setRandom(fn) {
+  if (typeof fn !== 'function')
+    throw new TypeError('fn is not a function');
+  jStat._random_fn = fn;
+};
+
+
 // Easily extend the jStat object.
@@ -119,3 +125,3 @@ // TODO: is this seriously necessary?
 
-  for (var i = 1; i < arguments.length; i++) {
+  for (i = 1; i < arguments.length; i++) {
     for (j in arguments[i])
@@ -172,3 +178,3 @@ obj[j] = arguments[i][j];
   if (isArray(index)) {
-    var submat = jStat.arange(arr.length).map(function(i) {
+    var submat = jStat.arange(arr.length).map(function() {
       return new Array(index.length);
@@ -228,3 +234,3 @@ });
 
-  for (var i = 0; i < cols; i++) {
+  for (i = 0; i < cols; i++) {
     objArr = new Array(rows);
@@ -305,3 +311,3 @@ for (j = 0; j < rows; j++)
 
-  for (var i = 0; i < rows; i++) {
+  for (i = 0; i < rows; i++) {
     res[i] = new Array(cols);
@@ -342,3 +348,3 @@ for (j = 0; j < cols; j++)
     cols = rows;
-  return jStat.create(rows, cols, Math.random);
+  return jStat.create(rows, cols, jStat._random_fn);
 };
@@ -360,3 +366,2 @@
 jStat.symmetric = function symmetric(arr) {
-  var issymmetric = true;
   var size = arr.length;
@@ -481,2 +486,3 @@ var row, col;
   function slice(list, rcSlice) {
+    var colSlice, rowSlice;
     rcSlice = rcSlice || {};
@@ -487,3 +493,3 @@ if (isNumber(rcSlice.row)) {
       var row = jStat.rowa(list, rcSlice.row);
-      var colSlice = rcSlice.col || {};
+      colSlice = rcSlice.col || {};
       return _slice(row, colSlice.start, colSlice.end, colSlice.step);
@@ -494,8 +500,8 @@ }
       var col = jStat.cola(list, rcSlice.col);
-      var rowSlice = rcSlice.row || {};
+      rowSlice = rcSlice.row || {};
       return _slice(col, rowSlice.start, rowSlice.end, rowSlice.step);
     }
 
-    var rowSlice = rcSlice.row || {};
-    var colSlice = rcSlice.col || {};
+    rowSlice = rcSlice.row || {};
+    colSlice = rcSlice.col || {};
     var rows = _slice(list, rowSlice.start, rowSlice.end, rowSlice.step);
@@ -515,2 +521,3 @@ return rows.map(function(row) {
 jStat.sliceAssign = function sliceAssign(A, rcSlice, B) {
+  var nl, ml;
   if (isNumber(rcSlice.row)) {
@@ -523,3 +530,3 @@ if (isNumber(rcSlice.col))
     rcSlice.col.step = rcSlice.col.step || 1;
-    var nl = jStat.arange(rcSlice.col.start,
+    nl = jStat.arange(rcSlice.col.start,
                           Math.min(A.length, rcSlice.col.end),
@@ -539,3 +546,3 @@ rcSlice.col.step);
     rcSlice.row.step = rcSlice.row.step || 1;
-    var ml = jStat.arange(rcSlice.row.start,
+    ml = jStat.arange(rcSlice.row.start,
                           Math.min(A[0].length, rcSlice.row.end),
@@ -559,6 +566,6 @@ rcSlice.row.step);
   rcSlice.col.step = rcSlice.col.step || 1;
-  var ml = jStat.arange(rcSlice.row.start,
+  ml = jStat.arange(rcSlice.row.start,
                         Math.min(A.length, rcSlice.row.end),
                         rcSlice.row.step);
-  var nl = jStat.arange(rcSlice.col.start,
+  nl = jStat.arange(rcSlice.col.start,
                         Math.min(A[0].length, rcSlice.col.end),
@@ -565,0 +572,0 @@ rcSlice.col.step);

src/distribution.js

@@ -199,7 +199,7 @@ (function(jStat, Math) {
 
-  median: function median(local, scale) {
+  median: function median(local/*, scale*/) {
     return local;
   },
 
-  mode: function mode(local, scale) {
+  mode: function mode(local/*, scale*/) {
     return local;
@@ -282,3 +282,3 @@ },
 
-  mode: function mode(rate) {
+  mode: function mode(/*rate*/) {
     return 0;
@@ -288,3 +288,3 @@ },
   sample: function sample(rate) {
-    return -1 / rate * Math.log(Math.random());
+    return -1 / rate * Math.log(jStat._random_fn());
   },
@@ -415,3 +415,3 @@
 
-  variance: function variance(alpha, beta) {
+  variance: function variance(/*alpha, beta*/) {
     throw new Error('variance not yet implemented');
@@ -449,3 +449,3 @@ // TODO: complete this
 
-  median: function median(mu, sigma) {
+  median: function median(mu/*, sigma*/) {
     return Math.exp(mu);
@@ -542,11 +542,11 @@ },
 
-  mean : function(mean, std) {
+  mean : function(mean/*, std*/) {
     return mean;
   },
 
-  median: function median(mean, std) {
+  median: function median(mean/*, std*/) {
     return mean;
   },
 
-  mode: function (mean, std) {
+  mode: function (mean/*, std*/) {
     return mean;
@@ -594,3 +594,3 @@ },
 
-  mode: function mode(scale, shape) {
+  mode: function mode(scale/*, shape*/) {
     return scale;
@@ -632,7 +632,7 @@ },
 
-  median: function median(dof) {
+  median: function median(/*dof*/) {
     return 0;
   },
 
-  mode: function mode(dof) {
+  mode: function mode(/*dof*/) {
     return 0;
@@ -684,3 +684,3 @@ },
   sample: function sample(scale, shape) {
-    return scale * Math.pow(-Math.log(Math.random()), 1 / shape);
+    return scale * Math.pow(-Math.log(jStat._random_fn()), 1 / shape);
   },
@@ -722,3 +722,3 @@
 
-  mode: function mode(a, b) {
+  mode: function mode(/*a, b*/) {
     throw new Error('mode is not yet implemented');
@@ -728,3 +728,3 @@ },
   sample: function sample(a, b) {
-    return (a / 2 + b / 2) + (b / 2 - a / 2) * (2 * Math.random() - 1);
+    return (a / 2 + b / 2) + (b / 2 - a / 2) * (2 * jStat._random_fn() - 1);
   },
@@ -1005,3 +1005,3 @@
       k++;
-      p *= Math.random();
+      p *= jStat._random_fn();
     } while (p > L);
@@ -1072,3 +1072,3 @@ return k - 1;
   sample: function sample(a, b, c) {
-    var u = Math.random();
+    var u = jStat._random_fn();
     if (u < ((c - a) / (b - a)))
@@ -1118,3 +1118,3 @@ return a + Math.sqrt(u * (b - a) * (c - a))
 
-  mode: function mode(a, b) {
+  mode: function mode(/*a, b*/) {
     throw new Error('mode is not yet implemented');
@@ -1152,11 +1152,11 @@ },
 
-  mean: function(mu, b) {
+  mean: function(mu/*, b*/) {
     return mu;
   },
 
-  median: function(mu, b) {
+  median: function(mu/*, b*/) {
     return mu;
   },
 
-  mode: function(mu, b) {
+  mode: function(mu/*, b*/) {
     return mu;
@@ -1170,3 +1170,3 @@ },
   sample: function sample(mu, b) {
-    var u = Math.random() - 0.5;
+    var u = jStat._random_fn() - 0.5;
 
@@ -1173,0 +1173,0 @@ return mu - (b * laplaceSign(u) * Math.log(1 - (2 * Math.abs(u))));

src/linearalgebra.js

@@ -151,6 +151,7 @@ /* Provides functions for the solution of linear system of equations, integration, extrapolation,
     var newarr = [];
-    for (var i = 0; i < a.length; i++) {
+    var i;
+    for (i = 0; i < a.length; i++) {
       newarr.push(a[i].slice());
     }
-    for (var i = 0; i < newarr.length; i++) {
+    for (i = 0; i < newarr.length; i++) {
       push.apply(newarr[i], b[i]);
@@ -201,3 +202,3 @@ }
     }
-    for (var i = 0; i < alen; i++) {
+    for (i = 0; i < alen; i++) {
       for (j = 0; j < alen; j++) {
@@ -212,3 +213,3 @@ vals[(mrow < 0) ? mrow + alen : mrow ] *= a[i][j];
     }
-    for (var i = 0; i < alen; i++) {
+    for (i = 0; i < alen; i++) {
       result += vals[i];
@@ -233,3 +234,3 @@ }
     maug = a[0].length;
-    for(var i = 0; i < n; i++) {
+    for(i = 0; i < n; i++) {
       pivot = a[i][i];
@@ -257,3 +258,3 @@ j = i;
     }
-    for (var i = n - 1; i >= 0; i--) {
+    for (i = n - 1; i >= 0; i--) {
       sum = 0;
@@ -269,10 +270,11 @@ for (j = i + 1; j<= n - 1; j++) {
   gauss_jordan: function gauss_jordan(a, b) {
-    var m = jStat.aug(a, b),
-    h = m.length,
-    w = m[0].length;
+    var m = jStat.aug(a, b);
+    var h = m.length;
+    var w = m[0].length;
     var c = 0;
+    var x, y, y2;
     // find max pivot
-    for (var y = 0; y < h; y++) {
+    for (y = 0; y < h; y++) {
       var maxrow = y;
-      for (var y2 = y+1; y2 < h; y2++) {
+      for (y2 = y+1; y2 < h; y2++) {
         if (Math.abs(m[y2][y]) > Math.abs(m[maxrow][y]))
@@ -284,5 +286,5 @@ maxrow = y2;
       m[maxrow] = tmp
-      for (var y2 = y+1; y2 < h; y2++) {
+      for (y2 = y+1; y2 < h; y2++) {
         c = m[y2][y] / m[y][y];
-        for (var x = y; x < w; x++) {
+        for (x = y; x < w; x++) {
           m[y2][x] -= m[y][x] * c;
@@ -293,6 +295,6 @@ }
     // backsubstitute
-    for (var y = h-1; y >= 0; y--) {
+    for (y = h-1; y >= 0; y--) {
       c = m[y][y];
-      for (var y2 = 0; y2 < y; y2++) {
-        for (var x = w-1; x > y-1; x--) {
+      for (y2 = 0; y2 < y; y2++) {
+        for (x = w-1; x > y-1; x--) {
           m[y2][x] -= m[y][x] * m[y2][y] / c;
@@ -302,3 +304,3 @@ }
       m[y][y] /= c;
-      for (var x = h; x < w; x++) {
+      for (x = h; x < w; x++) {
         m[y][x] /= c;
@@ -392,3 +394,3 @@ }
         });
-        R[l][j] = A[i][j] - jStat.sum(parts);
+        R[l][j] = A[parts.length][j] - jStat.sum(parts);
       });
@@ -574,31 +576,2 @@ });
 
-    function get_Q1(x) {
-      var size = x.length;
-      var norm_x = jStat.norm(x, 2);
-      var e1 = jStat.zeros(1, size)[0];
-      e1[0] = 1;
-      var u = jStat.add(jStat.multiply(jStat.multiply(e1, norm_x), -1), x);
-      var norm_u = jStat.norm(u, 2);
-      var v = jStat.divide(u, norm_u);
-      var Q = jStat.subtract(jStat.identity(size),
-                             jStat.multiply(jStat.outer(v, v), 2));
-      return Q;
-    }
-
-    function qr(A) {
-      var size = A[0].length;
-      var QList = [];
-      jStat.arange(size).forEach(function(i) {
-        var x = jStat.slice(A, { row: { start: i }, col: i });
-        var Q = get_Q1(x);
-        var Qn = jStat.identity(A.length);
-        Qn = jStat.sliceAssign(Qn, { row: { start: i }, col: { start: i }}, Q);
-        A = jStat.multiply(Qn, A);
-        QList.push(Qn);
-      });
-      var Q = QList.reduce(function(x, y){ return jStat.multiply(x,y) });
-      var R = A;
-      return [Q, R];
-    }
-
     function qr2(x) {
@@ -611,4 +584,4 @@ // quick impletation
 
+      var r = jStat.zeros(p, p);
       x = jStat.copy(x);
-      r = jStat.zeros(p, p);
 
@@ -638,3 +611,3 @@ var i,j,k;
 
-  lstsq: (function(A, b) {
+  lstsq: (function() {
     // solve least squard problem for Ax=b as QR decomposition way if b is
@@ -679,13 +652,13 @@ // [[b1],[b2],[b3]] form will return [[x1],[x2],[x3]] array form solution
       var RI = R_I(R1);
-	  var Q2 = jStat.transpose(Q1);
+      var Q2 = jStat.transpose(Q1);
 
-	  if(Q2[0].length === undefined){
-		  Q2 = [Q2]; // The confusing jStat.multifly implementation threat nature process again.
-	  }
+      if(Q2[0].length === undefined){
+        Q2 = [Q2]; // The confusing jStat.multifly implementation threat nature process again.
+      }
 
       var x = jStat.multiply(jStat.multiply(RI, Q2), b);
 
-	  if(x.length === undefined){
-		  x = [[x]]; // The confusing jStat.multifly implementation threat nature process again.
-	  }
+      if(x.length === undefined){
+        x = [[x]]; // The confusing jStat.multifly implementation threat nature process again.
+      }
 
@@ -703,3 +676,2 @@
     var condition = 1;
-    var count = 0;
     var n = a.length;
@@ -711,7 +683,6 @@ var e = jStat.identity(n, n);
     while (condition === 1) {
-      count++;
       maxim = a[0][1];
       p = 0;
       q = 1;
-      for (var i = 0; i < n; i++) {
+      for (i = 0; i < n; i++) {
         for (j = 0; j < n; j++) {
@@ -741,3 +712,3 @@ if (i != j) {
       condition = 0;
-      for (var i = 1; i < n; i++) {
+      for (i = 1; i < n; i++) {
         for (j = 1; j < n; j++) {
@@ -750,3 +721,3 @@ if (i != j && Math.abs(a[i][j]) > 0.001) {
     }
-    for (var i = 0; i < n; i++) ev.push(a[i][i]);
+    for (i = 0; i < n; i++) ev.push(a[i][i]);
     //returns both the eigenvalue and eigenmatrix
@@ -787,3 +758,3 @@ return [e, ev];
     var g = [];
-    var m, a1, j, k, I, d;
+    var m, a1, j, k, I;
     while (i < order / 2) {
@@ -823,8 +794,7 @@ I = f(a);
     }
-    var n = X.length,
-    h_min = Math.abs(x - X[pos(X, x) + 1]),
-    i = 0,
-    g = [],
-    h1 = [],
-    y1, y2, m, a, j;
+    var h_min = Math.abs(x - X[pos(X, x) + 1]);
+    var i = 0;
+    var g = [];
+    var h1 = [];
+    var y1, y2, m, a, j;
     while (h >= h_min) {
@@ -841,3 +811,3 @@ y1 = pos(X, x + h);
       for (j = 0; j < a - 1; j++)
-      h1[j] = ((Math.pow(4, m)) * g[j + 1] - g[j]) / (Math.pow(4, m) - 1);
+        h1[j] = ((Math.pow(4, m)) * g[j + 1] - g[j]) / (Math.pow(4, m) - 1);
       a = h1.length;
@@ -923,7 +893,7 @@ g = h1;
     alpha[0] = 0;
-    for (var i = 1; i < n - 1; i++) {
+    for (i = 1; i < n - 1; i++) {
       alpha[i] = (3 / h[i]) * (F[i + 1] - F[i]) -
           (3 / h[i-1]) * (F[i] - F[i-1]);
     }
-    for (var i = 1; i < n - 1; i++) {
+    for (i = 1; i < n - 1; i++) {
       A[i] = [];
@@ -956,3 +926,2 @@ B[i] = [];
     var n = X[0].length;
-    var flag = false;
     var i = 0;
@@ -970,6 +939,6 @@ var j, temp1;
     var Vt = [];
-    for (var i = 0; i < m; i++) {
+    for (i = 0; i < m; i++) {
       u[i] = jStat.sum(X[i]) / n;
     }
-    for (var i = 0; i < n; i++) {
+    for (i = 0; i < n; i++) {
       B[i] = [];
@@ -981,3 +950,3 @@ for(j = 0; j < m; j++) {
     B = jStat.transpose(B);
-    for (var i = 0; i < m; i++) {
+    for (i = 0; i < m; i++) {
       C[i] = [];
@@ -992,3 +961,3 @@ for (j = 0; j < m; j++) {
     Vt = jStat.transpose(V);
-    for (var i = 0; i < D.length; i++) {
+    for (i = 0; i < D.length; i++) {
       for (j = i; j < D.length; j++) {
@@ -1006,3 +975,3 @@ if(D[i] < D[j])  {
     Bt = jStat.transpose(B);
-    for (var i = 0; i < m; i++) {
+    for (i = 0; i < m; i++) {
       Y[i] = [];
@@ -1009,0 +978,0 @@ for (j = 0; j < Bt.length; j++) {

src/models.js

 jStat.models = (function(){
-
-  function sub_regress(endog, exog) {
-    return ols(endog, exog);
-  }
-
   function sub_regress(exog) {
@@ -8,0 +3,0 @@ var var_count = exog[0].length;

src/regression.js

@@ -58,10 +58,11 @@ //To regress, simply build X matrix
   matrixmult: function matrixmult(A,B){
+    var i, j, k, result, sum;
     if (A.cols() == B.rows()) {
       if(B.rows()>1){
-        var result = [];
-        for (var i = 0; i < A.rows(); i++) {
+        result = [];
+        for (i = 0; i < A.rows(); i++) {
           result[i] = [];
-          for (var j = 0; j < B.cols(); j++) {
-            var sum = 0;
-            for (var k = 0; k < A.cols(); k++) {
+          for (j = 0; j < B.cols(); j++) {
+            sum = 0;
+            for (k = 0; k < A.cols(); k++) {
               sum += A.toArray()[i][k] * B.toArray()[k][j];
@@ -74,8 +75,8 @@ }
       }
-      var result = [];
-      for (var i = 0; i < A.rows(); i++) {
+      result = [];
+      for (i = 0; i < A.rows(); i++) {
         result[i] = [];
-        for (var j = 0; j < B.cols(); j++) {
-          var sum = 0;
-          for (var k = 0; k < A.cols(); k++) {
+        for (j = 0; j < B.cols(); j++) {
+          sum = 0;
+          for (k = 0; k < A.cols(); k++) {
             sum += A.toArray()[i][k] * B.toArray()[j];
@@ -82,0 +83,0 @@ }

src/special.js

@@ -35,3 +35,3 @@ // Special functions //
   var y = x;
-  var i, z, yi, res, sum, ysq;
+  var i, z, yi, res;
   if (y <= 0) {
@@ -52,3 +52,3 @@ res = y % 1 + 3.6e-16;
   }
-  for (var i = 0; i < 8; ++i) {
+  for (i = 0; i < 8; ++i) {
     xnum = (xnum + p[i]) * z;
@@ -61,3 +61,3 @@ xden = xden * z + q[i];
   } else if (yi > y) {
-    for (var i = 0; i < n; ++i) {
+    for (i = 0; i < n; ++i) {
       res *= y;
@@ -94,3 +94,3 @@ y++;
   var ITMAX = -~(Math.log((a >= 1) ? a : 1 / a) * 8.5 + a * 0.4 + 17);
-  var an, endval;
+  var an;
 
@@ -400,3 +400,3 @@ if (x < 0 || a <= 0) {
 jStat.randn = function randn(n, m) {
-  var u, v, x, y, q, mat;
+  var u, v, x, y, q;
   if (!m)
@@ -407,4 +407,4 @@ m = n;
   do {
-    u = Math.random();
-    v = 1.7156 * (Math.random() - 0.5);
+    u = jStat._random_fn();
+    v = 1.7156 * (jStat._random_fn() - 0.5);
     x = u - 0.449871;
@@ -441,3 +441,3 @@ y = Math.abs(v) + 0.386595;
     v = v * v * v;
-    u = Math.random();
+    u = jStat._random_fn();
   } while(u > 1 - 0.331 * Math.pow(x, 4) &&
@@ -450,3 +450,3 @@ Math.log(u) > 0.5 * x*x + a1 * (1 - v + Math.log(v)));
   do {
-    u = Math.random();
+    u = jStat._random_fn();
   } while(u === 0);
@@ -453,0 +453,0 @@ return Math.pow(u, 1 / oalph) * a1 * v;

src/test.js

@@ -127,3 +127,3 @@ (function(jStat, Math) {
       tmpargs = new Array(args[0].length);
-      for (var i = 0; i < args[0].length; i++) {
+      for (i = 0; i < args[0].length; i++) {
         tmpargs[i] = args[0][i];
@@ -135,3 +135,3 @@ }
     sample = new Array();
-    for (var i = 0; i < args.length; i++) {
+    for (i = 0; i < args.length; i++) {
       sample = sample.concat(args[i]);
@@ -142,3 +142,3 @@ }
     expVar = 0;
-    for (var i = 0; i < args.length; i++) {
+    for (i = 0; i < args.length; i++) {
       expVar = expVar + args[i].length * Math.pow(jStat.mean(args[i]) - sampMean, 2);
@@ -149,3 +149,3 @@ }
     unexpVar = 0;
-    for (var i = 0; i < args.length; i++) {
+    for (i = 0; i < args.length; i++) {
       sampSampMean = jStat.mean(args[i]);
@@ -169,6 +169,6 @@ for (j = 0; j < args[i].length; j++) {
     }
-    anovafscore = jStat.anovafscore(args);
+    var anovafscore = jStat.anovafscore(args);
     df1 = args.length - 1;
     n = 0;
-    for (var i = 0; i < args.length; i++) {
+    for (i = 0; i < args.length; i++) {
       n = n + args[i].length;
@@ -193,3 +193,3 @@ }
     var i;
-    for (var i = 0; i < this.length; i++) {
+    for (i = 0; i < this.length; i++) {
       n = n + this[i].length;
@@ -196,0 +196,0 @@ }

src/vector.js

@@ -146,3 +146,3 @@ (function(jStat, Math) {
   var i;
-  for (var i = 1; i < arrLen; i++)
+  for (i = 1; i < arrLen; i++)
     diffs.push(arr[i] - arr[i - 1]);
@@ -158,2 +158,3 @@ return diffs;
   var ranks = new Array(arrlen);
+  var val;
   for (var i = 0; i < arrlen; i++) {
@@ -163,5 +164,5 @@ var first = sorted.indexOf(arr[i]);
     if (first === last) {
-      var val = first;
+      val = first;
     } else {
-      var val = (first + last) / 2;
+      val = (first + last) / 2;
     }
@@ -186,3 +187,3 @@ ranks[i] = val + 1;
 
-  for (var i = 0; i < arrLen; i++) {
+  for (i = 0; i < arrLen; i++) {
     if (_arr[i] === _arr[i + 1]) {
@@ -303,3 +304,3 @@ count++;
 
-  for (var i = 0; i < quantilesArray.length; i++) {
+  for (i = 0; i < quantilesArray.length; i++) {
     p = quantilesArray[i];
@@ -342,3 +343,3 @@ m = alphap + p * (1 - alphap - betap);
 
-  for (var i = 0; i < len; i++) {
+  for (i = 0; i < len; i++) {
     value = arr[i];
@@ -356,5 +357,5 @@ if ((strict && value < score) ||
 // Histogram (bin count) data
-jStat.histogram = function histogram(arr, bins) {
+jStat.histogram = function histogram(arr, binCnt) {
+  binCnt = binCnt || 4;
   var first = jStat.min(arr);
-  var binCnt = bins || 4;
   var binWidth = (jStat.max(arr) - first) / binCnt;
@@ -365,5 +366,5 @@ var len = arr.length;
 
-  for (var i = 0; i < binCnt; i++)
+  for (i = 0; i < binCnt; i++)
     bins[i] = 0;
-  for (var i = 0; i < len; i++)
+  for (i = 0; i < len; i++)
     bins[Math.min(Math.floor(((arr[i] - first) / binWidth)), binCnt - 1)] += 1;
@@ -383,3 +384,3 @@
 
-  for (var i = 0; i < arr1Len; i++)
+  for (i = 0; i < arr1Len; i++)
     sq_dev[i] = (arr1[i] - u) * (arr2[i] - v);
@@ -522,2 +523,3 @@
       var args = Array.prototype.slice.call(arguments);
+      var callbackFunction;
 
@@ -527,3 +529,3 @@ // If the last argument is a function, we assume it's a callback; we
       if (isFunction(args[args.length - 1])) {
-        var callbackFunction = args[args.length - 1];
+        callbackFunction = args[args.length - 1];
         var argsToPass = args.slice(0, args.length - 1);
@@ -539,3 +541,3 @@
       } else {
-        var callbackFunction = undefined;
+        callbackFunction = undefined;
         var curriedFunction = function curriedFunction(vector) {
@@ -542,0 +544,0 @@ return jStat[passfunc].apply(tmpthis, [vector].concat(args));

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Worsened metrics

Total package byte prevSize

694667

decreased by-0.38%

Lines of code

15171

decreased by-0.32%

No dependency changes