Usage

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

#### mean( N, x, stride )

Computes the [arithmetic mean][arithmetic-mean] of a strided array x.

`javascript
var x = [ 1.0, -2.0, 2.0 ];
var N = x.length;

var v = mean( N, x, 1 );
// returns ~0.3333
`

The function has the following parameters:

- N: number of indexed elements.
- x: input [Array][mdn-array] or [typed array][mdn-typed-array].
- stride: index increment for x.

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

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

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

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

#### mean.ndarray( N, x, stride, offset )

Computes the [arithmetic mean][arithmetic-mean] of a strided array using alternative indexing semantics.

`javascript
var x = [ 1.0, -2.0, 2.0 ];
var N = x.length;

var v = mean.ndarray( N, x, 1, 0 );
// returns ~0.33333
`

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 [arithmetic mean][arithmetic-mean] for every other value in x starting from the second value

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

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

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