simple-statistics - npm Package Compare versions

Comparing version 7.0.0 to 7.0.1

CHANGELOG.md

@@ -5,2 +5,13 @@ # Change Log
 
+<a name="7.0.1"></a>
+## [7.0.1](https://github.com/simple-statistics/simple-statistics/compare/v7.0.0...v7.0.1) (2019-02-07)
+
+
+### Bug Fixes
+
+* code format error ([a1b9f15](https://github.com/simple-statistics/simple-statistics/commit/a1b9f15))
+* plus minus sign error ([f0b047d](https://github.com/simple-statistics/simple-statistics/commit/f0b047d))
+
+
+
 <a name="7.0.0"></a>
@@ -7,0 +18,0 @@ # [7.0.0](https://github.com/simple-statistics/simple-statistics/compare/v6.1.1...v7.0.0) (2018-12-30)

dist/simple-statistics.js

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n=t[0].length,o=r[Math.floor(n/2)],a=[],i=[],h=0,u=void 0;h<n;++h)u=r[h]-o,0===h?(a.push(u),i.push(u*u)):(a.push(a[h-1]+u),i.push(i[h-1]+u*u)),t[0][h]=E(0,h,a,i),e[0][h]=0;for(var f=1;f<t.length;++f)I(f<t.length-1?f:n-1,n-1,f,t,e,a,i)}(e,n,o);for(var a=[],h=o[0].length-1,u=o.length-1;u>=0;u--){var f=o[u][h];a[u]=e.slice(f,h+1),u>0&&(h=f-1)}return a},exports.uniqueCountSorted=b,exports.sumNthPowerDeviations=e,exports.equalIntervalBreaks=function(r,t){if(r.length<2)return r;for(var e=h(r),n=u(r),o=[e],a=(n-e)/t,i=1;i<t;i++)o.push(o[0]+a*i);return o.push(n),o},exports.sampleCovariance=P,exports.sampleCorrelation=function(r,t){return P(r,t)/N(r)/N(t)},exports.sampleVariance=C,exports.sampleStandardDeviation=N,exports.sampleSkewness=function(r){if(r.length<3)throw new Error("sampleSkewness requires at least three data points");for(var e,n=t(r),o=0,a=0,i=0;i<r.length;i++)o+=(e=r[i]-n)*e,a+=e*e*e;var h=Math.sqrt(o/(r.length-1)),u=r.length;return u*a/((u-1)*(u-2)*Math.pow(h,3))},exports.sampleKurtosis=function(r){var e=r.length;if(e<4)throw new Error("sampleKurtosis requires at least four data points");for(var n,o=t(r),a=0,i=0,h=0;h<e;h++)a+=(n=r[h]-o)*n,i+=n*n*n*n;return(e-1)/((e-2)*(e-3))*(e*(e+1)*i/(a*a)-3*(e-1))},exports.permutationsHeap=function(r){for(var t=new Array(r.length),e=[r.slice()],n=0;n<r.length;n++)t[n]=0;for(var o=0;o<r.length;)if(t[o]<o){var a=0;o%2!=0&&(a=t[o]);var i=r[a];r[a]=r[o],r[o]=i,e.push(r.slice()),t[o]++,o=0}else t[o]=0,o++;return e},exports.combinations=function r(t,e){var n,o,a,i,h=[];for(n=0;n<t.length;n++)if(1===e)h.push([t[n]]);else for(a=r(t.slice(n+1,t.length),e-1),o=0;o<a.length;o++)(i=a[o]).unshift(t[n]),h.push(i);return h},exports.combinationsReplacement=function r(t,e){for(var n=[],o=0;o<t.length;o++)if(1===e)n.push([t[o]]);else for(var a=r(t.slice(o,t.length),e-1),i=0;i<a.length;i++)n.push([t[o]].concat(a[i]));return n},exports.addToMean=function(r,t,e){return r+(e-r)/(t+1)},exports.combineMeans=R,exports.combineVariances=function(r,t,e,n,o,a){var i=R(t,e,o,a);return(e*(r+Math.pow(t-i,2))+a*(n+Math.pow(o-i,2)))/(e+a)},exports.geometricMean=function(r){if(0===r.length)throw new Error("geometricMean requires at least one data point");for(var t=1,e=0;e<r.length;e++){if(r[e]<=0)throw new Error("geometricMean requires only positive numbers as input");t*=r[e]}return Math.pow(t,1/r.length)},exports.harmonicMean=function(r){if(0===r.length)throw new Error("harmonicMean requires at least one data point");for(var t=0,e=0;e<r.length;e++){if(r[e]<=0)throw new Error("harmonicMean requires only positive numbers as input");t+=1/r[e]}return r.length/t},exports.average=t,exports.mean=t,exports.median=x,exports.medianSorted=function(r){return f(r,.5)},exports.subtractFromMean=function(r,t,e){return(r*t-e)/(t-1)},exports.rootMeanSquare=D,exports.rms=D,exports.variance=n,exports.tTest=function(r,e){return(t(r)-e)/(o(r)/Math.sqrt(r.length))},exports.tTestTwoSample=function(r,e,n){var o=r.length,a=e.length;if(!o||!a)return null;n||(n=0);var i=t(r),h=t(e),u=C(r),f=C(e);return"number"==typeof i&&"number"==typeof h&&"number"==typeof u&&"number"==typeof f?(i-h-n)/Math.sqrt(((o-1)*u+(a-1)*f)/(o+a-2)*(1/o+1/a)):void 0},exports.BayesianClassifier=A,exports.bayesian=A,exports.PerceptronModel=S,exports.perceptron=S,exports.epsilon=T,exports.factorial=_,exports.gamma=function r(t){if(Number.isInteger(t))return t<=0?NaN:_(t-1);if(--t<0)return Math.PI/(Math.sin(Math.PI*-t)*r(-t));var e=t+.25;return Math.pow(t/Math.E,t)*Math.sqrt(2*Math.PI*(t+1/6))*(1+1/144/Math.pow(e,2)-1/12960/Math.pow(e,3)-257/207360/Math.pow(e,4)-52/2612736/Math.pow(e,5)+5741173/9405849600/Math.pow(e,6)+37529/18811699200/Math.pow(e,7))},exports.gammaln=function(r){if(r<=0)return Infinity;r--;for(var t=z[0],e=1;e<15;e++)t+=z[e]/(r+e);var n=B+.5+r;return K+Math.log(t)-n+(r+.5)*Math.log(n)},exports.bernoulliDistribution=function(r){if(r<0||r>1)throw new Error("bernoulliDistribution requires probability to be between 0 and 1 inclusive");return[1-r,r]},exports.binomialDistribution=function(r,t){if(!(t<0||t>1||r<=0||r%1!=0)){var e=0,n=0,o=[],a=1;do{o[e]=a*Math.pow(t,e)*Math.pow(1-t,r-e),n+=o[e],a=a*(r-++e+1)/e}while(n<1-T);return o}},exports.poissonDistribution=function(r){if(!(r<=0)){var t=0,e=0,n=[],o=1;do{n[t]=Math.exp(-r)*Math.pow(r,t)/o,e+=n[t],o*=++t}while(e<1-T);return n}},exports.chiSquaredDistributionTable=U,exports.chiSquaredGoodnessOfFit=function(r,e,n){for(var o=0,a=e(t(r)),i=[],h=[],u=0;u<r.length;u++)void 0===i[r[u]]&&(i[r[u]]=0),i[r[u]]++;for(var f=0;f<i.length;f++)void 0===i[f]&&(i[f]=0);for(var s in a)s in i&&(h[+s]=a[s]*r.length);for(var l=h.length-1;l>=0;l--)h[l]<3&&(h[l-1]+=h[l],h.pop(),i[l-1]+=i[l],i.pop());for(var p=0;p<i.length;p++)o+=Math.pow(i[p]-h[p],2)/h[p];return U[i.length-1-1][n]<o},exports.kernelDensityEstimation=J,exports.kde=J,exports.zScore=function(r,t,e){return(r-t)/e},exports.cumulativeStdNormalProbability=function(r){var t=Math.abs(r),e=Math.min(Math.round(100*t),Z.length-1);return r>=0?Z[e]:+(1-Z[e]).toFixed(4)},exports.standardNormalTable=Z,exports.errorFunction=O,exports.erf=O,exports.inverseErrorFunction=V,exports.probit=function(r){return 0===r?r=T:r>=1&&(r=1-T),Math.sqrt(2)*V(2*r-1)},exports.permutationTest=function(r,e,n,o){if(void 0===o&&(o=1e4),void 0===n&&(n="two_side"),"two_side"!==n&&"greater"!==n&&"less"!==n)throw new Error("`alternative` must be either 'two_side', 'greater', or 'less'");for(var a=t(r)-t(e),i=new Array(o),h=r.concat(e),u=Math.floor(h.length/2),f=0;f<o;f++){d(h);var s=h.slice(0,u),l=h.slice(u,h.length),p=t(s)-t(l);i[f]=p}var c=0;if("two_side"===n)for(var g=0;g<=o;g++)Math.abs(i[g])>=Math.abs(a)&&(c+=1);else if("greater"===n)for(var v=0;v<=o;v++)i[v]>=a&&(c+=1);else for(var M=0;M<=o;M++)i[M]<=a&&(c+=1);return c/o},exports.bisect=function(r,t,e,n,o){if("function"!=typeof r)throw new TypeError("func must be a function");for(var a=0;a<n;a++){var i=(t+e)/2;if(0===r(i)||Math.abs((e-t)/2)<o)return i;X(r(i))===X(r(t))?t=i:e=i}throw new Error("maximum number of iterations exceeded")},exports.quickselect=s,exports.sign=X,exports.numericSort=i;
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package.json

 {
   "name": "simple-statistics",
-  "version": "7.0.0",
+  "version": "7.0.1",
   "description": "Simple Statistics",
@@ -5,0 +5,0 @@ "author": "Tom MacWright <[e-mail]> (http://macwright.org/)",

README.md

@@ -39,4 +39,4 @@ # Simple Statistics
       available globally as the variable `ss`. You can reassign this variable to
-      another name if you want to, but doing so is optional. <pre><script src='https://unpkg.com/simple-statistics@7.0.0/dist/simple-statistics.min.js' /></pre>
-      * `https://unpkg.com/simple-statistics@7.0.0/dist/simple-statistics.min.js`
+      another name if you want to, but doing so is optional. <pre><script src='https://unpkg.com/simple-statistics@7.0.1/dist/simple-statistics.min.js' /></pre>
+      * `https://unpkg.com/simple-statistics@7.0.1/dist/simple-statistics.min.js`
   * **I want to use ES6 modules in a browser and I'm [willing to only support new browsers](https://caniuse.com/#feat=es6-module) to do it**
@@ -48,3 +48,3 @@ * This module works great with the [`?module`](https://unpkg.com/#/query-parameters) query parameter of unpkg. If you
       <script type='module'>
-      import {min} from "https://unpkg.com/simple-statistics@7.0.0/index.js?module"
+      import {min} from "https://unpkg.com/simple-statistics@7.0.1/index.js?module"
       console.log(min([1, 2, 3]))
@@ -51,0 +51,0 @@ </script>

src/error_function.js

@@ -8,2 +8,3 @@ /**
  * This function returns a numerical approximation to the exact value.
+ * It uses Horner's method to evaluate the polynomial of τ (tau).
  *
@@ -20,13 +21,17 @@ * @param {number} x input
         Math.exp(
-            -Math.pow(x, 2) -
-                1.26551223 +
-                1.00002368 * t +
-                0.37409196 * Math.pow(t, 2) +
-                0.09678418 * Math.pow(t, 3) -
-                0.18628806 * Math.pow(t, 4) +
-                0.27886807 * Math.pow(t, 5) -
-                1.13520398 * Math.pow(t, 6) +
-                1.48851587 * Math.pow(t, 7) -
-                0.82215223 * Math.pow(t, 8) +
-                0.17087277 * Math.pow(t, 9)
+            -x * x +
+                ((((((((0.17087277 * t - 0.82215223) * t + 1.48851587) * t -
+                    1.13520398) *
+                    t +
+                    0.27886807) *
+                    t -
+                    0.18628806) *
+                    t +
+                    0.09678418) *
+                    t +
+                    0.37409196) *
+                    t +
+                    1.00002368) *
+                    t -
+                1.26551223
         );
@@ -33,0 +38,0 @@ if (x >= 0) {

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Improved metrics

Lines of code

4623

increased by0.09%

Worsened metrics

Total package byte prevSize

707355

decreased by-0.01%

No dependency changes