chore: minor clean-up

Author: Planeshifter

lib/node_modules/@stdlib/_tools/eslint/rules/first-unit-test/README.md

@@ -77,7 +77,7 @@ tape( 'main export is a function', function test( t ) {
 
 ## Examples
 
-<!-- eslint-disable  node/no-unpublished-require -->
+<!-- eslint-disable node/no-unpublished-require -->
 
 <!-- eslint no-undef: "error" -->
 

lib/node_modules/@stdlib/_tools/readme/to-html/README.md

@@ -136,7 +136,7 @@ var fpath = resolve( __dirname, '..', 'README.md' );
 var opts = {
     'title': 'Beep',
     'source': 'https://github.com/stdlib-js/stdlib/develop/tools/readme/to-html/lib/index.js',
-    'append': '<script  type="text/javascript">console.log("Beep!");</script>'
+    'append': '<script type="text/javascript">console.log("Beep!");</script>'
 };
 
 convert( fpath, opts, onFinish );

lib/node_modules/@stdlib/blas/base/idamax/examples/c/example.c

@@ -23,7 +23,7 @@ int main( void ) {
 	// Create strided array:
 	const double x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 };
 
-	// Specify the number of element:
+	// Specify the number of elements:
 	const int N = 8;
 
 	// Specify stride:

lib/node_modules/@stdlib/blas/base/isamax/README.md

@@ -187,7 +187,7 @@ The function accepts the following arguments:
 -   **strideX**: `[in] CBLAS_INT` index increment for `X`.
 
 ```c
-CBLAS_INT c_isamax( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
+CBLAS_INT c_isamax( const CBLAS_INT N, const float *X, const CBLAS_INT strideX );
 ```
 
 #### c_isamax_ndarray( N, \*X, strideX, offsetX )
@@ -209,7 +209,7 @@ The function accepts the following arguments:
 -   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
 
 ```c
-CBLAS_INT c_isamax_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
+CBLAS_INT c_isamax_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
 ```
 
 </section>
@@ -238,7 +238,7 @@ int main( void ) {
     // Create strided array:
     const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f };
 
-    // Specify the number of element:
+    // Specify the number of elements:
     const int N = 8;
 
     // Specify stride:

lib/node_modules/@stdlib/blas/base/isamax/examples/c/example.c

@@ -23,7 +23,7 @@ int main( void ) {
 	// Create strided array:
 	const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f };
 
-	// Specify the number of element:
+	// Specify the number of elements:
 	const int N = 8;
 
 	// Specify stride:

lib/node_modules/@stdlib/blas/ext/base/snansumors/README.md

@@ -55,7 +55,7 @@ The function has the following parameters:
 -   **x**: input [`Float32Array`][@stdlib/array/float32].
 -   **strideX**: stride length for `x`.
 
-The `N` and stride parameters determine which elements in the strided array are  accessed at runtime. For example, to compute the sum of every other element:
+The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of every other element:
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );

lib/node_modules/@stdlib/random/base/README.md

@@ -98,7 +98,7 @@ Attached to each PRNG are the following properties:
 -   **seed**: the value used to seed the PRNG.
 -   **seedLength**: the length of the PRNG seed.
 -   **state**: the PRNG state.
--   **stateLength**: the length  of the PRNG state.
+-   **stateLength**: the length of the PRNG state.
 -   **byteLength**: the size of the PRNG state.
 -   **PRNG**: the underlying pseudorandom number generator.
 

lib/node_modules/@stdlib/stats/base/dists/negative-binomial/cdf/README.md

@@ -39,7 +39,7 @@ F(x;r,p)=1-I_p(x+1,r)
 
 <!-- </equation> -->
 
-where `r` is the number of successes until experiment is stopped, `p` is the success probability in each trial and `I` is the [lower regularized incomplete beta function][incomplete-beta]. The random variable `X` denotes the number of failures until the `r` success is reached. 
+where `r` is the number of successes until experiment is stopped, `p` is the success probability in each trial and `I` is the [lower regularized incomplete beta function][incomplete-beta]. The random variable `X` denotes the number of failures until the `r` success is reached.
 
 </section>
 
@@ -116,7 +116,7 @@ y = cdf( 2.0, 20, 1.5 );
 
 #### cdf.factory( r, p )
 
-Returns a function for evaluating the [cumulative distribution function][cdf] of  a [negative binomial][negative-binomial-distribution] distribution with number of successes until experiment is stopped `r` and success probability `p`.
+Returns a function for evaluating the [cumulative distribution function][cdf] of a [negative binomial][negative-binomial-distribution] distribution with number of successes until experiment is stopped `r` and success probability `p`.
 
 ```javascript
 var mycdf = cdf.factory( 10, 0.5 );

lib/node_modules/@stdlib/stats/base/dists/negative-binomial/mgf/README.md

@@ -121,7 +121,7 @@ y = mgf( 0.2, 20, 1.5 );
 
 #### mgf.factory( r, p )
 
-Returns a function for evaluating the [moment-generating function][mgf] of  a [negative binomial][negative-binomial-distribution] distribution with number of successes until experiment is stopped `r` and success probability `p`.
+Returns a function for evaluating the [moment-generating function][mgf] of a [negative binomial][negative-binomial-distribution] distribution with number of successes until experiment is stopped `r` and success probability `p`.
 
 ```javascript
 var myMGF = mgf.factory( 4.3, 0.4 );

lib/node_modules/@stdlib/stats/base/dists/truncated-normal/pdf/README.md

@@ -40,7 +40,7 @@ f(x;\mu,\sigma,a,b) =  \begin{cases} \frac{\frac{1}{\sigma}\phi(\frac{x - \mu}{\
 
 <!-- </equation> -->
 
-where `Phi` and `phi` denote the [cumulative distribution function][cdf] and [density function][pdf] of the [normal][normal-distribution] distribution, respectively, `mu` is the location  and `sigma > 0` is the scale parameter of the distribution. `a` and `b` are the minimum and maximum support.
+where `Phi` and `phi` denote the [cumulative distribution function][cdf] and [density function][pdf] of the [normal][normal-distribution] distribution, respectively, `mu` is the location and `sigma > 0` is the scale parameter of the distribution. `a` and `b` are the minimum and maximum support.
 
 </section>
 

lib/node_modules/@stdlib/stats/strided/dsmeanpw/README.md

@@ -258,10 +258,10 @@ int main( void ) {
     const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };
 
     // Specify the number of elements:
-    const int  N = 4;
+    const int N = 4;
 
     // Specify the stride length:
-    const int  strideX = 2;
+    const int strideX = 2;
 
     // Compute the arithmetic mean:
     double v = stdlib_strided_dsmeanpw( N, x, strideX );

lib/node_modules/@stdlib/stats/ttest2/README.md

@@ -32,7 +32,7 @@ var ttest2 = require( '@stdlib/stats/ttest2' );
 
 #### ttest2( x, y\[, opts] )
 
-By default, the function performs a two-sample t-test for the null hypothesis that the data in [arrays][mdn-array] or [typed arrays][mdn-typed-array] `x` and `y` is  independently drawn from normal distributions with _equal_ means.
+By default, the function performs a two-sample t-test for the null hypothesis that the data in [arrays][mdn-array] or [typed arrays][mdn-typed-array] `x` and `y` is independently drawn from normal distributions with _equal_ means.
 
 ```javascript
 // Student's sleep data:

lib/node_modules/@stdlib/stats/vartest/README.md

@@ -32,7 +32,7 @@ var vartest = require( '@stdlib/stats/vartest' );
 
 #### vartest( x, y\[, opts] )
 
-By default, the function performs a two-sample F-test for the null hypothesis that the data in [arrays][mdn-array] or [typed arrays][mdn-typed-array] `x` and `y` is  independently drawn from normal distributions with _equal_ variances.
+By default, the function performs a two-sample F-test for the null hypothesis that the data in [arrays][mdn-array] or [typed arrays][mdn-typed-array] `x` and `y` is independently drawn from normal distributions with _equal_ variances.
 
 ```javascript
 var x = [ 610, 610, 550, 590, 565, 570 ];