function nanvariancetk( N, correction, x, strideX, offsetX ) {
	var xbuf;
	var get;
	var S2;
	var ix;
	var nc;
	var S;
	var v;
	var n;
	var i;

	// Cache reference to array data:
	xbuf = x.data;

	// Cache a reference to the element accessor:
	get = x.accessors[ 0 ];

	if ( N === 1 || strideX === 0 ) {
		v = get( xbuf, offsetX );
		if ( v === v && N-correction > 0.0 ) {
			return 0.0;
		}
		return NaN;
	}

	ix = offsetX;
	S2 = 0.0;
	S = 0.0;
	n = 0;
	for ( i = 0; i < N; i++ ) {
		v = get( xbuf, ix );
		if ( v === v ) {
			S2 += v * v;
			S += v;
			n += 1;
		}
		ix += strideX;
	}
	nc = n - correction;
	if ( nc <= 0.0 ) {
		return NaN;
	}
	return (S2 - ((S/n)*S)) / nc;
}
Computes the variance of a strided array ignoring `NaN` values and using a one-pass textbook algorithm.

@private
@param {PositiveInteger} N - number of indexed elements
@param {number} correction - degrees of freedom adjustment
@param {Object} x - input array object
@param {Collection} x.data - input array data
@param {Array<Function>} x.accessors - array element accessors
@param {integer} strideX - stride length
@param {NonNegativeInteger} offsetX - starting index
@returns {number} variance

@example
var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
var arraylike2object = require( '@stdlib/array/base/arraylike2object' );

var x = toAccessorArray( [ 1.0, -2.0, NaN, 2.0 ] );

var v = nanvariancetk(x.length, 1, arraylike2object( x ), 1, 0 );
// returns ~4.3333