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Merge branch 'develop' of https://github.com/stdlib-js/stdlib into develop
2 parents e6f9e64 + 6fd416a commit 307f6ce

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‎lib/node_modules/@stdlib/math/base/dist/betaprime/stdev/README.md‎

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@@ -9,9 +9,9 @@
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The [standard deviation][stdev] for a [beta prime][betaprime] random variable with first shape parameter `α` and second shape parameter `β` is
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12-
<!-- <equation class="equation" label="eq:betaprime_variance" align="center" raw="\sigma = \sqrt{ \tfrac{\alpha(\alpha +\beta -1)}{(\beta-2)(\beta-1)^{2}} }" alt="Standard deviation for a beta prime distribution."> -->
12+
<!-- <equation class="equation" label="eq:betaprime_stdev" align="center" raw="\sigma = \sqrt{ \tfrac{\alpha(\alpha +\beta -1)}{(\beta-2)(\beta-1)^{2}} }" alt="Standard deviation for a beta prime distribution."> -->
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<div class="equation" align="center" data-raw-text="\sigma = \sqrt{ \tfrac{\alpha(\alpha +\beta -1)}{(\beta-2)(\beta-1)^{2}} }" data-equation="eq:betaprime_variance">
14+
<div class="equation" align="center" data-raw-text="\sigma = \sqrt{ \tfrac{\alpha(\alpha +\beta -1)}{(\beta-2)(\beta-1)^{2}} }" data-equation="eq:betaprime_stdev">
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<img src="" alt="Standard deviation for a beta prime distribution.">
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<br>
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</div>

‎lib/node_modules/@stdlib/math/base/dist/chisquare/kurtosis/benchmark/benchmark.js‎

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@@ -7,7 +7,7 @@ var randu = require( '@stdlib/math/base/random/randu' );
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var isnan = require( '@stdlib/math/base/assert/is-nan' );
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var EPS = require( '@stdlib/math/constants/float64-eps' );
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var pkg = require( './../package.json' ).name;
10-
var skewness = require( './../lib' );
10+
var kurtosis = require( './../lib' );
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// MAIN //
@@ -20,7 +20,7 @@ bench( pkg, function benchmark( b ) {
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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k = ( randu()*20.0 ) + EPS;
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y = skewness( k );
23+
y = kurtosis( k );
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if ( isnan( y ) ) {
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b.fail( 'should not return NaN' );
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}

‎lib/node_modules/@stdlib/math/base/dist/gamma/ctor/README.md‎

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@@ -140,6 +140,17 @@ var skewness = gamma.skewness;
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// returns 1.0
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```
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#### Gamma.prototype.stdev
144+
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Returns the [standard deviation][standard-deviation].
146+
147+
``` javascript
148+
var gamma = new Gamma( 4.0, 12.0 );
149+
150+
var s = gamma.stdev;
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// returns ~0.167
152+
```
153+
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#### Gamma.prototype.variance
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145156
Returns the [variance][variance].
@@ -279,6 +290,7 @@ var y = gamma.cdf( 0.8 );
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[kurtosis]: https://en.wikipedia.org/wiki/Kurtosis
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[mode]: https://en.wikipedia.org/wiki/Mode_%28statistics%29
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[skewness]: https://en.wikipedia.org/wiki/Skewness
293+
[standard-deviation]: https://en.wikipedia.org/wiki/Standard_deviation
282294
[variance]: https://en.wikipedia.org/wiki/Variance
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</section>

‎lib/node_modules/@stdlib/math/base/dist/gamma/ctor/benchmark/benchmark.js‎

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@@ -303,6 +303,33 @@ bench( pkg+':skewness', function benchmark( b ) {
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b.end();
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});
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bench( pkg+':stdev', function benchmark( b ) {
307+
var alpha;
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var beta;
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var dist;
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var y;
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var i;
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alpha = 100.56789;
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beta = 55.54321;
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dist = new Gamma( alpha, beta );
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b.tic();
318+
for ( i = 0; i < b.iterations; i++ ) {
319+
dist.alpha = ( 100.0*randu() ) + EPS;
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y = dist.stdev;
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if ( isnan( y ) ) {
322+
b.fail( 'should not return NaN' );
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}
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}
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b.toc();
326+
if ( isnan( y ) ) {
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b.fail( 'should not return NaN' );
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}
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b.pass( 'benchmark finished' );
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b.end();
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});
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bench( pkg+':variance', function benchmark( b ) {
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var alpha;
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var beta;

‎lib/node_modules/@stdlib/math/base/dist/gamma/ctor/benchmark/python/benchmark.scipy.py‎

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@@ -115,6 +115,12 @@ def main():
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iterations = 1000
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benchmark(name, setup, stmt, iterations)
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name = "gamma:stdev"
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setup = "from scipy.stats import gamma; from random import random; rv = gamma(100.56789, 55.54321);"
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stmt = "y = rv.std()"
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iterations = 1000
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benchmark(name, setup, stmt, iterations)
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name = "gamma:variance"
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setup = "from scipy.stats import gamma; from random import random; rv = gamma(100.56789, 55.54321);"
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stmt = "y = rv.var()"

‎lib/node_modules/@stdlib/math/base/dist/gamma/ctor/docs/repl.txt‎

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gamma.skewness: number
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Read-only property which returns the skewness.
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gamma.stdev: number
40+
Read-only property which returns the standard deviation.
41+
3942
gamma.variance: number
4043
Read-only property which returns the variance.
4144

@@ -72,6 +75,8 @@
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1.0
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> gamma.skewness
7477
~0.816
78+
> gamma.stdev
79+
0.49
7580
> gamma.variance
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0.24
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> gamma.cdf( 0.8 )

‎lib/node_modules/@stdlib/math/base/dist/gamma/ctor/lib/ctor.js‎

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@@ -11,6 +11,7 @@ var mean = require( '@stdlib/math/base/dist/gamma/mean' );
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var mode = require( '@stdlib/math/base/dist/gamma/mode' );
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var quantile = require( '@stdlib/math/base/dist/gamma/quantile' );
1313
var skewness = require( '@stdlib/math/base/dist/gamma/skewness' );
14+
var stdev = require( '@stdlib/math/base/dist/gamma/stdev' );
1415
var variance = require( '@stdlib/math/base/dist/gamma/variance' );
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var cdf = require( '@stdlib/math/base/dist/gamma/cdf' );
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var logpdf = require( '@stdlib/math/base/dist/gamma/logpdf' );
@@ -258,12 +259,34 @@ Object.defineProperty( Gamma.prototype, 'skewness', {
258259
}
259260
});
260261

262+
/**
263+
* Gamma distribution standard deviation.
264+
*
265+
* @memberof Gamma.prototype
266+
* @name stdev
267+
* @type {PositiveNumber}
268+
* @see [standard deviation]{@link https://en.wikipedia.org/wiki/Standard_deviation}
269+
*
270+
* @example
271+
* var gamma = new Gamma( 4.0, 12.0 );
272+
*
273+
* var v = gamma.stdev;
274+
* // returns ~0.028
275+
*/
276+
Object.defineProperty( Gamma.prototype, 'stdev', {
277+
'configurable': false,
278+
'enumerable': true,
279+
'get': function get() {
280+
return stdev( this.alpha, this.beta );
281+
}
282+
});
283+
261284
/**
262285
* Gamma distribution variance.
263286
*
264287
* @memberof Gamma.prototype
265288
* @name variance
266-
* @type {number}
289+
* @type {PositiveNumber}
267290
* @see [variance]{@link https://en.wikipedia.org/wiki/Variance}
268291
*
269292
* @example

‎lib/node_modules/@stdlib/math/base/dist/gamma/ctor/test/test.js‎

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@@ -14,6 +14,7 @@ var entropy = require( '@stdlib/math/base/dist/gamma/entropy' );
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var kurtosis = require( '@stdlib/math/base/dist/gamma/kurtosis' );
1515
var skewness = require( '@stdlib/math/base/dist/gamma/skewness' );
1616
var variance = require( '@stdlib/math/base/dist/gamma/variance' );
17+
var stdev = require( '@stdlib/math/base/dist/gamma/stdev' );
1718
var mode = require( '@stdlib/math/base/dist/gamma/mode' );
1819
var mean = require( '@stdlib/math/base/dist/gamma/mean' );
1920
var Gamma = require( './../lib' );
@@ -266,6 +267,17 @@ tape( 'the distribution prototype has a property for retrieving the distribution
266267
t.end();
267268
});
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270+
tape( 'the distribution prototype has a property for retrieving the distribution standard deviation', function test( t ) {
271+
var gamma;
272+
273+
t.strictEqual( hasOwnProp( Gamma.prototype, 'stdev' ), true, 'has property' );
274+
275+
gamma = new Gamma( 3.0, 5.0 );
276+
t.strictEqual( gamma.stdev, stdev( 3.0, 5.0 ), 'returns expected value' );
277+
278+
t.end();
279+
});
280+
269281
tape( 'the distribution prototype has a property for retrieving the distribution variance', function test( t ) {
270282
var gamma;
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‎lib/node_modules/@stdlib/math/base/dist/geometric/ctor/README.md‎

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@@ -135,6 +135,17 @@ var skewness = geometric.skewness;
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// returns ~2.066
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```
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#### Geometric.prototype.stdev
139+
140+
Returns the [standard deviation][standard-deviation].
141+
142+
``` javascript
143+
var geometric = new Geometric( 0.4 );
144+
145+
var s = geometric.stdev;
146+
// returns ~1.936
147+
```
148+
138149
#### Geometric.prototype.variance
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140151
Returns the [variance][variance].
@@ -292,6 +303,7 @@ var y = geometric.cdf( 2.0 );
292303
[median]: https://en.wikipedia.org/wiki/Median
293304
[mode]: https://en.wikipedia.org/wiki/Mode_%28statistics%29
294305
[skewness]: https://en.wikipedia.org/wiki/Skewness
306+
[standard-deviation]: https://en.wikipedia.org/wiki/Standard_deviation
295307
[variance]: https://en.wikipedia.org/wiki/Variance
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</section>

‎lib/node_modules/@stdlib/math/base/dist/geometric/ctor/benchmark/benchmark.js‎

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@@ -233,6 +233,31 @@ bench( pkg+':skewness', function benchmark( b ) {
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b.end();
234234
});
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236+
bench( pkg+':stdev', function benchmark( b ) {
237+
var dist;
238+
var p;
239+
var y;
240+
var i;
241+
242+
p = 0.54;
243+
dist = new Geometric( p );
244+
245+
b.tic();
246+
for ( i = 0; i < b.iterations; i++ ) {
247+
dist.p = randu();
248+
y = dist.stdev;
249+
if ( isnan( y ) ) {
250+
b.fail( 'should not return NaN' );
251+
}
252+
}
253+
b.toc();
254+
if ( isnan( y ) ) {
255+
b.fail( 'should not return NaN' );
256+
}
257+
b.pass( 'benchmark finished' );
258+
b.end();
259+
});
260+
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bench( pkg+':variance', function benchmark( b ) {
237262
var dist;
238263
var p;

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