Usage

`javascript
var dsem = require( '@stdlib/stats-base-dsem' );
`

#### dsem( N, correction, x, stride )

Computes the [standard error of the mean][standard-error] of a double-precision floating-point strided array x.

`javascript
var Float64Array = require( '@stdlib/array-float64' );

var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
var N = x.length;

var v = dsem( N, 1, x, 1 );
// returns ~1.20185
`

The function has the following parameters:

- N: number of indexed elements.
- correction: degrees of freedom adjustment. Setting this parameter to a value other than 0 has the effect of adjusting the divisor during the calculation of the [standard deviation][standard-deviation] according to N-c where c corresponds to the provided degrees of freedom adjustment. When computing the [standard deviation][standard-deviation] of a population, setting this parameter to 0 is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample [standard deviation][standard-deviation], setting this parameter to 1 is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction).
- x: input [Float64Array][@stdlib/array/float64].
- stride: index increment for x.

The N and stride parameters determine which elements in x are accessed at runtime. For example, to compute the [standard error of the mean][standard-error] of every other element in x,

`javascript
var Float64Array = require( '@stdlib/array-float64' );
var floor = require( '@stdlib/math-base-special-floor' );

var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
var N = floor( x.length / 2 );

var v = dsem( N, 1, x, 2 );
// returns 1.25
`

Note that indexing is relative to the first index. To introduce an offset, use [typed array][mdn-typed-array] views.

`javascript
var Float64Array = require( '@stdlib/array-float64' );
var floor = require( '@stdlib/math-base-special-floor' );

var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

var N = floor( x0.length / 2 );

var v = dsem( N, 1, x1, 2 );
// returns 1.25
`

#### dsem.ndarray( N, correction, x, stride, offset )

Computes the [standard error of the mean][standard-error] of a double-precision floating-point strided array using alternative indexing semantics.

`javascript
var Float64Array = require( '@stdlib/array-float64' );

var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
var N = x.length;

var v = dsem.ndarray( N, 1, x, 1, 0 );
// returns ~1.20185
`

The function has the following additional parameters:

- offset: starting index for x.

While [typed array][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [standard error of the mean][standard-error] for every other value in x starting from the second value

`javascript
var Float64Array = require( '@stdlib/array-float64' );
var floor = require( '@stdlib/math-base-special-floor' );

var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var N = floor( x.length / 2 );

var v = dsem.ndarray( N, 1, x, 2, 1 );
// returns 1.25
`