js/solGS/normalDistribution.js

   1 /**
   2
   3 * given an array of arrays dataset ([[A, 1], [B, 2], [C, 4], [D, 1]]),
   4 it standardizes dependent variable values (calculates z-scores), calculates probabilties
   5 and returns an array of js objects of the form
   6 [{x: xvalue, y: yvalue, z: z-score , p: probability}, ....]
   7
   8 * uses methods from statistics/simple_statistics js library
   9
  10 * Isaak Y Tecle <iyt2@cornell.edu>
  11
  12 **/
  13
  14 var solGS = solGS || function solGS () {};
  15
  16 solGS.normalDistribution =  function () {};
  17
  18
  19 solGS.normalDistribution.prototype.getNormalDistData = function (xy) {
  20
  21         var yValues = this.getYValues(xy);
  22
  23         var mean = ss.mean(yValues);
  24         var std  = ss.standard_deviation(yValues);
  25
  26         var normalDistData = [];
  27
  28         for (var i=0; i < xy.length; i++) {
  29
  30             var x = xy[i][0];
  31             var y = xy[i][1];
  32             y     = d3.format('.2f')(y);
  33             var z = ss.z_score(y, mean, std);
  34             z     = d3.format('.2f')(z);
  35             var p = ss.cumulative_std_normal_probability(z);
  36
  37             if (y > mean) {
  38                 p = 1 - p;
  39             }
  40
  41             normalDistData.push({'x': x, 'y': y, 'z': z, 'p': p});
  42         }
  43
  44     return normalDistData;
  45 }
  46
  47
  48 solGS.normalDistribution.prototype.getPValues = function (normalData) {
  49
  50         var p = [];
  51
  52         for (var i=0; i < normalData.length; i++) {
  53             var pV  = normalData[i].p;
  54             p.push(pV);
  55         }
  56
  57         return p;
  58
  59 }
  60
  61
  62 solGS.normalDistribution.prototype.getXValues = function (xy) {
  63
  64         var xv = [];
  65
  66         for (var i=0; i < xy.length; i++) {
  67             var x = xy[i][0];
  68             x     = x.replace(/^\s+|\s+$/g, '');
  69             x     = Number(x);
  70             xv.push(x);
  71         }
  72
  73         return xv;
  74
  75 }
  76
  77 solGS.normalDistribution.prototype.getYValues = function (xy) {
  78
  79         var yv = [];
  80
  81         for (var i=0; i < xy.length; i++) {
  82             var y = xy[i][1];
  83             y     = Number(y);
  84
  85             yv.push(y);
  86         }
  87
  88         return yv;
  89
  90 }
  91
  92
  93 solGS.normalDistribution.prototype.getYValuesZScores = function (normalData) {
  94
  95         var yz = [];
  96
  97         for (var i=0; i < normalData.length; i++) {
  98             var y = normalData[i].y;
  99             var z  = normalData[i].z;
 100             yz.push([y, z]);
 101
 102         }
 103
 104         return yz;
 105 }
 106
 107
 108 solGS.normalDistribution.prototype.getZScoresP = function (normalData) {
 109
 110         var zp = [];
 111
 112         for (var i=0; i < normalData.length; i++) {
 113             var zV  = normalData[i].z;
 114             var pV  = normalData[i].p;
 115             zp.push([zV, pV]);
 116
 117         }
 118
 119         return zp;
 120 }
 121
 122
 123 solGS.normalDistribution.prototype.getYValuesP = function (normalData) {
 124
 125         var yp = [];
 126
 127         for (var i=0; i < normalData.length; i++) {
 128             var x  = normalData[i].y;
 129             var y  = normalData[i].p;
 130             yp.push([x, y]);
 131
 132         }
 133
 134         return yp;
 135 }
 136
 137
 138 solGS.normalDistribution.prototype.getObsValueZScore = function (obsValuesZScores, zScore) {
 139
 140         var obsValue;
 141         for (var i=0; i < obsValuesZScores.length; i++) {
 142
 143             var j =  obsValuesZScores[i];
 144
 145             if (obsValuesZScores[i][1] == zScore) {
 146                 obsValue = obsValuesZScores[i][0];
 147             }
 148         }
 149
 150     return [obsValue, zScore];
 151 }
 152
 153
 154
 155
 156