refactor: refactor the lib folder's files to align with existing style

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Author: rahulptl165

lib/node_modules/@stdlib/stats/base/nanvariancech/README.md

@@ -174,7 +174,6 @@ var v = nanvariancech.ndarray( 5, 1, x, 2, 1 );
 -   If `N <= 0`, both functions return `NaN`.
 -   If `n - c` is less than or equal to `0` (where `c` corresponds to the provided degrees of freedom adjustment and `n` corresponds to the number of non-`NaN` indexed elements), both functions return `NaN`.
 -   The underlying algorithm is a specialized case of Neely's two-pass algorithm. As the variance is invariant with respect to changes in the location parameter, the underlying algorithm uses the first non-`NaN` strided array element as a trial mean to shift subsequent data values and thus mitigate catastrophic cancellation. Accordingly, the algorithm's accuracy is best when data is **unordered** (i.e., the data is **not** sorted in either ascending or descending order such that the first value is an "extreme" value).
--   Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]).
 -   Depending on the environment, the typed versions ([`dnanvariancech`][@stdlib/stats/strided/dnanvariancech], [`snanvariancech`][@stdlib/stats/base/snanvariancech], etc.) are likely to be significantly more performant.
 
 </section>
@@ -274,8 +273,6 @@ console.log( v );
 
 [@stdlib/stats/base/variancech]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/variancech
 
-[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor
-
 <!-- </related-links> -->
 
 </section>

lib/node_modules/@stdlib/stats/base/nanvariancech/benchmark/benchmark.js

@@ -27,7 +27,7 @@ var filledarrayBy = require( '@stdlib/array/filled-by' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var pkg = require( './../package.json' ).name;
-var nanvariancech = require( './../lib/nanvariancech.js' );
+var nanvariancech = require( './../lib/main.js' );
 
 
 // FUNCTIONS //

lib/node_modules/@stdlib/stats/base/nanvariancech/lib/index.js

@@ -28,23 +28,28 @@
 *
 * var x = [ 1.0, -2.0, NaN, 2.0 ];
 *
-* var v = nanvariancech( x.length, 1, x, 1 );
+* var v = nanvariancech( 4, 1, x, 1 );
 * // returns ~4.3333
 *
 * @example
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var nanvariancech = require( '@stdlib/stats/base/nanvariancech' );
 *
 * var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ];
-* var N = floor( x.length / 2 );
 *
-* var v = nanvariancech.ndarray( N, 1, x, 2, 1 );
+* var v = nanvariancech.ndarray( 5, 1, x, 2, 1 );
 * // returns 6.25
 */
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
+var ndarray = require( './ndarray.js' );
+
+
+// MAIN //
+
+setReadOnly( main, 'ndarray', ndarray );
 
 
 // EXPORTS //

lib/node_modules/@stdlib/stats/base/nanvariancech/lib/main.js

@@ -20,14 +20,41 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
-var nanvariancech = require( './nanvariancech.js' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
 var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
 
-setReadOnly( nanvariancech, 'ndarray', ndarray );
+/**
+* Computes the variance of a strided array ignoring `NaN` values and using a one-pass trial mean algorithm.
+*
+* ## Method
+*
+* -   This implementation uses a one-pass trial mean approach, as suggested by Chan et al (1983).
+*
+* ## References
+*
+* -   Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958](https://doi.org/10.1145/365719.365958).
+* -   Ling, Robert F. 1974. "Comparison of Several Algorithms for Computing Sample Means and Variances." _Journal of the American Statistical Association_ 69 (348). American Statistical Association, Taylor & Francis, Ltd.: 859–66. doi:[10.2307/2286154](https://doi.org/10.2307/2286154).
+* -   Chan, Tony F., Gene H. Golub, and Randall J. LeVeque. 1983. "Algorithms for Computing the Sample Variance: Analysis and Recommendations." _The American Statistician_ 37 (3). American Statistical Association, Taylor & Francis, Ltd.: 242–47. doi:[10.1080/00031305.1983.10483115](https://doi.org/10.1080/00031305.1983.10483115).
+* -   Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036](https://doi.org/10.1145/3221269.3223036).
+*
+* @param {PositiveInteger} N - number of indexed elements
+* @param {number} correction - degrees of freedom adjustment
+* @param {NumericArray} x - input array
+* @param {integer} strideX - stride length
+* @returns {number} variance
+*
+* @example
+* var x = [ 1.0, -2.0, NaN, 2.0 ];
+*
+* var v = nanvariancech( 4, 1, x, 1 );
+* // returns ~4.3333
+*/
+function nanvariancech( N, correction, x, strideX ) {
+	return ndarray( N, correction, x, strideX, stride2offset( N, strideX) );
+}
 
 
 // EXPORTS //

lib/node_modules/@stdlib/stats/base/nanvariancech/lib/nanvariancech.js

@@ -24,7 +24,7 @@ var tape = require( 'tape' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var Float64Array = require( '@stdlib/array/float64' );
 var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
-var nanvariancech = require( './../lib/nanvariancech.js' );
+var nanvariancech = require( './../lib/main.js' );
 
 
 // TESTS //