match exisiting template for variance docs

Author: shubham220420

lib/node_modules/@stdlib/stats/base/dists/halfnormal/variance/README.md

@@ -31,7 +31,7 @@ The [variance][variance] for a [half-normal][half-normal-distribution] random va
 <!-- <equation class="equation" label="eq:halfnormal_variance" align="center" raw="\operatorname{Var}\left[ X \right] = \sigma^{2} \left(1 - \frac{2}{\pi}\right)" alt="Variance for a half-normal distribution."> -->
 
 ```math
-\operatorname{Var}\left[ X \right] = \sigma^{2} \left(1 - \frac{2}{\pi}\right)
+\mathop{\mathrm{Var}}\left[ X \right] = \sigma^{2} \left(1 - \frac{2}{\pi}\right)
 ```
 
 <!-- <div class="equation" align="center" data-raw-text="\operatorname{Var}\left[ X \right] = \sigma^{2} \left(1 - \frac{2}{\pi}\right)" data-equation="eq:halfnormal_variance">
@@ -61,7 +61,7 @@ Returns the [variance][variance] for a [half-normal][half-normal-distribution] d
 
 ```javascript
 var y = variance( 1.0 );
-// returns ~0.363
+// returns ~0.3633802276
 
 y = variance( 4.0 );
 // returns ~5.814083642118698
@@ -117,7 +117,7 @@ var opts = {
 };
 var sigma = uniform( 10, 0.0, 20.0, opts );
 
-logEachMap( 'σ: %0.4f, Var(X;σ): %0.4f', sigma, variance );
+logEachMap( 'σ: %lf, Var(X;σ): %lf', sigma, variance );
 ```
 
 </section>
@@ -142,6 +142,8 @@ logEachMap( 'σ: %0.4f, Var(X;σ): %0.4f', sigma, variance );
 
 <!-- Section for C API documentation. -->
 
+* * *
+
 <section class="c">
 
 ## C APIs
@@ -168,6 +170,12 @@ logEachMap( 'σ: %0.4f, Var(X;σ): %0.4f', sigma, variance );
 
 Returns the variance for a [half-normal][half-normal-distribution] distribution with scale parameter `sigma`.
 
+```c
+double out = stdlib_base_dists_halfnormal_variance( 1.0 );
+// returns ~0.3633802276
+```
+The function accepts the following arguments:
+
 -   **sigma**: `[in] double` scale parameter.
 -   **return**: `[out] double` variance.
 
@@ -211,7 +219,7 @@ int main( void ) {
     for ( i = 0; i < 10; i++ ) {
         sigma = random_uniform( 0.1, 20.0 );
         y = stdlib_base_dists_halfnormal_variance( sigma );
-        printf( "σ: %.4f, Var(X;σ): %.4f\n", sigma, y );
+        printf( "σ: %lf, Var(X;σ): %lf\n", sigma, y );
     }
 }
 ```

lib/node_modules/@stdlib/stats/base/dists/halfnormal/variance/benchmark/benchmark.js

@@ -21,6 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
+var Float64Array = require( '@stdlib/array/float64' );
 var randu = require( '@stdlib/random/base/randu' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var EPS = require( '@stdlib/constants/float64/eps' );
@@ -32,13 +33,19 @@ var variance = require( './../lib' );
 
 bench( pkg, function benchmark( b ) {
 	var sigma;
+	var len;
 	var y;
 	var i;
 
+	len = 100;
+	sigma = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		sigma[ i ] = ( randu() * 20.0 ) + EPS;
+	}
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		sigma = ( randu()*20.0 ) + EPS;
-		y = variance( sigma );
+		y = variance( sigma[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}