(function(jStat, Math) {

var slice = [].slice;
var isNumber = jStat.utils.isNumber;
var isArray = jStat.utils.isArray;

// flag==true denotes use of sample standard deviation
// Z Statistics
jStat.extend({
  // 2 different parameter lists:
  // (value, mean, sd)
  // (value, array, flag)
  zscore: function zscore() {
    var args = slice.call(arguments);
    if (isNumber(args[1])) {
      return (args[0] - args[1]) / args[2];
    }
    return (args[0] - jStat.mean(args[1])) / jStat.stdev(args[1], args[2]);
  },

  // 3 different paramter lists:
  // (value, mean, sd, sides)
  // (zscore, sides)
  // (value, array, sides, flag)
  ztest: function ztest() {
    var args = slice.call(arguments);
    var z;
    if (isArray(args[1])) {
      // (value, array, sides, flag)
      z = jStat.zscore(args[0],args[1],args[3]);
      return (args[2] === 1) ?
        (jStat.normal.cdf(-Math.abs(z), 0, 1)) :
        (jStat.normal.cdf(-Math.abs(z), 0, 1)*2);
    } else {
      if (args.length > 2) {
        // (value, mean, sd, sides)
        z = jStat.zscore(args[0],args[1],args[2]);
        return (args[3] === 1) ?
          (jStat.normal.cdf(-Math.abs(z),0,1)) :
          (jStat.normal.cdf(-Math.abs(z),0,1)* 2);
      } else {
        // (zscore, sides)
        z = args[0];
        return (args[1] === 1) ?
          (jStat.normal.cdf(-Math.abs(z),0,1)) :
          (jStat.normal.cdf(-Math.abs(z),0,1)*2);
      }
    }
  }
});

jStat.extend(jStat.fn, {
  zscore: function zscore(value, flag) {
    return (value - this.mean()) / this.stdev(flag);
  },

  ztest: function ztest(value, sides, flag) {
    var zscore = Math.abs(this.zscore(value, flag));
    return (sides === 1) ?
      (jStat.normal.cdf(-zscore, 0, 1)) :
      (jStat.normal.cdf(-zscore, 0, 1) * 2);
  }
});

// T Statistics
jStat.extend({
  // 2 parameter lists
  // (value, mean, sd, n)
  // (value, array)
  tscore: function tscore() {
    var args = slice.call(arguments);
    return (args.length === 4) ?
      ((args[0] - args[1]) / (args[2] / Math.sqrt(args[3]))) :
      ((args[0] - jStat.mean(args[1])) /
       (jStat.stdev(args[1], true) / Math.sqrt(args[1].length)));
  },

  // 3 different paramter lists:
  // (value, mean, sd, n, sides)
  // (tscore, n, sides)
  // (value, array, sides)
  ttest: function ttest() {
    var args = slice.call(arguments);
    var tscore;
    if (args.length === 5) {
      tscore = Math.abs(jStat.tscore(args[0], args[1], args[2], args[3]));
      return (args[4] === 1) ?
        (jStat.studentt.cdf(-tscore, args[3]-1)) :
        (jStat.studentt.cdf(-tscore, args[3]-1)*2);
    }
    if (isNumber(args[1])) {
      tscore = Math.abs(args[0])
      return (args[2] == 1) ?
        (jStat.studentt.cdf(-tscore, args[1]-1)) :
        (jStat.studentt.cdf(-tscore, args[1]-1) * 2);
    }
    tscore = Math.abs(jStat.tscore(args[0], args[1]))
    return (args[2] == 1) ?
      (jStat.studentt.cdf(-tscore, args[1].length-1)) :
      (jStat.studentt.cdf(-tscore, args[1].length-1) * 2);
  }
});

jStat.extend(jStat.fn, {
  tscore: function tscore(value) {
    return (value - this.mean()) / (this.stdev(true) / Math.sqrt(this.cols()));
  },

  ttest: function ttest(value, sides) {
    return (sides === 1) ?
      (1 - jStat.studentt.cdf(Math.abs(this.tscore(value)), this.cols()-1)) :
      (jStat.studentt.cdf(-Math.abs(this.tscore(value)), this.cols()-1)*2);
  }
});

// F Statistics
jStat.extend({
  // Paramter list is as follows:
  // (array1, array2, array3, ...)
  // or it is an array of arrays
  // array of arrays conversion
  anovafscore: function anovafscore() {
    var args = slice.call(arguments),
    expVar, sample, sampMean, sampSampMean, tmpargs, unexpVar, i, j;
    if (args.length === 1) {
      tmpargs = new Array(args[0].length);
      for (i = 0; i < args[0].length; i++) {
        tmpargs[i] = args[0][i];
      }
      args = tmpargs;
    }
    // Builds sample array
    sample = new Array();
    for (i = 0; i < args.length; i++) {
      sample = sample.concat(args[i]);
    }
    sampMean = jStat.mean(sample);
    // Computes the explained variance
    expVar = 0;
    for (i = 0; i < args.length; i++) {
      expVar = expVar + args[i].length * Math.pow(jStat.mean(args[i]) - sampMean, 2);
    }
    expVar /= (args.length - 1);
    // Computes unexplained variance
    unexpVar = 0;
    for (i = 0; i < args.length; i++) {
      sampSampMean = jStat.mean(args[i]);
      for (j = 0; j < args[i].length; j++) {
        unexpVar += Math.pow(args[i][j] - sampSampMean, 2);
      }
    }
    unexpVar /= (sample.length - args.length);
    return expVar / unexpVar;
  },

  // 2 different paramter setups
  // (array1, array2, array3, ...)
  // (anovafscore, df1, df2)
  anovaftest: function anovaftest() {
    var args = slice.call(arguments),
    df1, df2, n, i;
    if (isNumber(args[0])) {
      return 1 - jStat.centralF.cdf(args[0], args[1], args[2]);
    }
    var anovafscore = jStat.anovafscore(args);
    df1 = args.length - 1;
    n = 0;
    for (i = 0; i < args.length; i++) {
      n = n + args[i].length;
    }
    df2 = n - df1 - 1;
    return 1 - jStat.centralF.cdf(anovafscore, df1, df2);
  },

  ftest: function ftest(fscore, df1, df2) {
    return 1 - jStat.centralF.cdf(fscore, df1, df2);
  }
});

jStat.extend(jStat.fn, {
  anovafscore: function anovafscore() {
    return jStat.anovafscore(this.toArray());
  },

  anovaftes: function anovaftes() {
    var n = 0;
    var i;
    for (i = 0; i < this.length; i++) {
      n = n + this[i].length;
    }
    return jStat.ftest(this.anovafscore(), this.length - 1, n - this.length);
  }
});

// Tukey's range test
jStat.extend({
  // 2 parameter lists
  // (mean1, mean2, n1, n2, sd)
  // (array1, array2, sd)
  qscore: function qscore() {
    var args = slice.call(arguments);
    var mean1, mean2, n1, n2, sd;
    if (isNumber(args[0])) {
        mean1 = args[0];
        mean2 = args[1];
        n1 = args[2];
        n2 = args[3];
        sd = args[4];
    } else {
        mean1 = jStat.mean(args[0]);
        mean2 = jStat.mean(args[1]);
        n1 = args[0].length;
        n2 = args[1].length;
        sd = args[2];
    }
    return Math.abs(mean1 - mean2) / (sd * Math.sqrt((1 / n1 + 1 / n2) / 2));
  },

  // 3 different parameter lists:
  // (qscore, n, k)
  // (mean1, mean2, n1, n2, sd, n, k)
  // (array1, array2, sd, n, k)
  qtest: function qtest() {
    var args = slice.call(arguments);

    var qscore;
    if (args.length === 3) {
      qscore = args[0];
      args = args.slice(1);
    } else if (args.length === 7) {
      qscore = jStat.qscore(args[0], args[1], args[2], args[3], args[4]);
      args = args.slice(5);
    } else {
      qscore = jStat.qscore(args[0], args[1], args[2]);
      args = args.slice(3);
    }

    var n = args[0];
    var k = args[1];

    return 1 - jStat.tukey.cdf(qscore, k, n - k);
  },

  tukeyhsd: function tukeyhsd(arrays) {
    var sd = jStat.pooledstdev(arrays);
    var means = arrays.map(function (arr) {return jStat.mean(arr);});
    var n = arrays.reduce(function (n, arr) {return n + arr.length;}, 0);

    var results = [];
    for (var i = 0; i < arrays.length; ++i) {
        for (var j = i + 1; j < arrays.length; ++j) {
            var p = jStat.qtest(means[i], means[j], arrays[i].length, arrays[j].length, sd, n, arrays.length);
            results.push([[i, j], p]);
        }
    }

    return results;
  }
});

// Error Bounds
jStat.extend({
  // 2 different parameter setups
  // (value, alpha, sd, n)
  // (value, alpha, array)
  normalci: function normalci() {
    var args = slice.call(arguments),
    ans = new Array(2),
    change;
    if (args.length === 4) {
      change = Math.abs(jStat.normal.inv(args[1] / 2, 0, 1) *
                        args[2] / Math.sqrt(args[3]));
    } else {
      change = Math.abs(jStat.normal.inv(args[1] / 2, 0, 1) *
                        jStat.stdev(args[2]) / Math.sqrt(args[2].length));
    }
    ans[0] = args[0] - change;
    ans[1] = args[0] + change;
    return ans;
  },

  // 2 different parameter setups
  // (value, alpha, sd, n)
  // (value, alpha, array)
  tci: function tci() {
    var args = slice.call(arguments),
    ans = new Array(2),
    change;
    if (args.length === 4) {
      change = Math.abs(jStat.studentt.inv(args[1] / 2, args[3] - 1) *
                        args[2] / Math.sqrt(args[3]));
    } else {
      change = Math.abs(jStat.studentt.inv(args[1] / 2, args[2].length - 1) *
                        jStat.stdev(args[2], true) / Math.sqrt(args[2].length));
    }
    ans[0] = args[0] - change;
    ans[1] = args[0] + change;
    return ans;
  },

  significant: function significant(pvalue, alpha) {
    return pvalue < alpha;
  }
});

jStat.extend(jStat.fn, {
  normalci: function normalci(value, alpha) {
    return jStat.normalci(value, alpha, this.toArray());
  },

  tci: function tci(value, alpha) {
    return jStat.tci(value, alpha, this.toArray());
  }
});

// internal method for calculating the z-score for a difference of proportions test
function differenceOfProportions(p1, n1, p2, n2) {
  if (p1 > 1 || p2 > 1 || p1 <= 0 || p2 <= 0) {
    throw new Error("Proportions should be greater than 0 and less than 1")
  }
  var pooled = (p1 * n1 + p2 * n2) / (n1 + n2);
  var se = Math.sqrt(pooled * (1 - pooled) * ((1/n1) + (1/n2)));
  return (p1 - p2) / se;
}

// Difference of Proportions
jStat.extend(jStat.fn, {
  oneSidedDifferenceOfProportions: function oneSidedDifferenceOfProportions(p1, n1, p2, n2) {
    var z = differenceOfProportions(p1, n1, p2, n2);
    return jStat.ztest(z, 1);
  },

  twoSidedDifferenceOfProportions: function twoSidedDifferenceOfProportions(p1, n1, p2, n2) {
    var z = differenceOfProportions(p1, n1, p2, n2);
    return jStat.ztest(z, 2);
  }
});

}(jStat, Math));