time-to-botec/squiggle/node_modules/@stdlib/stats/base/sstdevch/docs/repl.txt
NunoSempere b6addc7f05 feat: add the node modules
Necessary in order to clearly see the squiggle hotwiring.
2022-12-03 12:44:49 +00:00

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{{alias}}( N, correction, x, stride )
Computes the standard deviation of a single-precision floating-point strided
array using a one-pass trial mean algorithm.
The `N` and `stride` parameters determine which elements in `x` are accessed
at runtime.
Indexing is relative to the first index. To introduce an offset, use a typed
array view.
If `N <= 0`, the function returns `NaN`.
Parameters
----------
N: integer
Number of indexed elements.
correction: number
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 according to `N - c` where `c` corresponds to
the provided degrees of freedom adjustment. When computing the 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,
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: Float32Array
Input array.
stride: integer
Index increment.
Returns
-------
out: number
The standard deviation.
Examples
--------
// Standard Usage:
> var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 2.0 ] );
> {{alias}}( x.length, 1, x, 1 )
~2.0817
// Using `N` and `stride` parameters:
> x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );
> var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
> var stride = 2;
> {{alias}}( N, 1, x, stride )
~2.0817
// Using view offsets:
> var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
> var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
> N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
> stride = 2;
> {{alias}}( N, 1, x1, stride )
~2.0817
{{alias}}.ndarray( N, correction, x, stride, offset )
Computes the standard deviation of a single-precision floating-point strided
array using a one-pass trial mean algorithm and alternative indexing
semantics.
While typed array views mandate a view offset based on the underlying
buffer, the `offset` parameter supports indexing semantics based on a
starting index.
Parameters
----------
N: integer
Number of indexed elements.
correction: number
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 according to `N - c` where `c` corresponds to
the provided degrees of freedom adjustment. When computing the 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,
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: Float32Array
Input array.
stride: integer
Index increment.
offset: integer
Starting index.
Returns
-------
out: number
The standard deviation.
Examples
--------
// Standard Usage:
> var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 2.0 ] );
> {{alias}}.ndarray( x.length, 1, x, 1, 0 )
~2.0817
// Using offset parameter:
> var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
> var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
> {{alias}}.ndarray( N, 1, x, 2, 1 )
~2.0817
See Also
--------