122 lines
4.2 KiB
Plaintext
122 lines
4.2 KiB
Plaintext
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{{alias}}( N, correction, x, stride )
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Computes the standard deviation of a single-precision floating-point strided
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array ignoring `NaN` values and using a one-pass textbook algorithm.
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The `N` and `stride` parameters determine which elements in `x` are accessed
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at runtime.
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Indexing is relative to the first index. To introduce an offset, use a typed
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array view.
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If `N <= 0`, the function returns `NaN`.
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If every indexed element is `NaN`, the function returns `NaN`.
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Parameters
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----------
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N: integer
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Number of indexed elements.
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correction: number
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Degrees of freedom adjustment. Setting this parameter to a value other
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than `0` has the effect of adjusting the divisor during the calculation
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of the standard deviation according to `N - c` where `c` corresponds to
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the provided degrees of freedom adjustment. When computing the standard
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deviation of a population, setting this parameter to `0` is the standard
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choice (i.e., the provided array contains data constituting an entire
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population). When computing the corrected sample standard deviation,
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setting this parameter to `1` is the standard choice (i.e., the provided
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array contains data sampled from a larger population; this is commonly
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referred to as Bessel's correction).
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x: Float32Array
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Input array.
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stride: integer
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Index increment.
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Returns
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-------
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out: number
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The standard deviation.
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Examples
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--------
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// Standard Usage:
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> var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, NaN, 2.0 ] );
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> {{alias}}( x.length, 1, x, 1 )
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~2.0817
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// Using `N` and `stride` parameters:
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> x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );
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> var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
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> var stride = 2;
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> {{alias}}( N, 1, x, stride )
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~2.0817
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// Using view offsets:
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> var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
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> var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
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> N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
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> stride = 2;
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> {{alias}}( N, 1, x1, stride )
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~2.0817
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{{alias}}.ndarray( N, correction, x, stride, offset )
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Computes the standard deviation of a single-precision floating-point strided
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array ignoring `NaN` values and using a one-pass textbook algorithm and
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alternative indexing semantics.
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While typed array views mandate a view offset based on the underlying
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buffer, the `offset` parameter supports indexing semantics based on a
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starting index.
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Parameters
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----------
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N: integer
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Number of indexed elements.
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correction: number
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Degrees of freedom adjustment. Setting this parameter to a value other
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than `0` has the effect of adjusting the divisor during the calculation
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of the standard deviation according to `N - c` where `c` corresponds to
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the provided degrees of freedom adjustment. When computing the standard
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deviation of a population, setting this parameter to `0` is the standard
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choice (i.e., the provided array contains data constituting an entire
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population). When computing the corrected sample standard deviation,
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setting this parameter to `1` is the standard choice (i.e., the provided
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array contains data sampled from a larger population; this is commonly
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referred to as Bessel's correction).
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x: Float32Array
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Input array.
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stride: integer
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Index increment.
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offset: integer
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Starting index.
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Returns
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-------
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out: number
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The standard deviation.
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Examples
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--------
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// Standard Usage:
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> var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, NaN, 2.0 ] );
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> {{alias}}.ndarray( x.length, 1, x, 1, 0 )
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~2.0817
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// Using offset parameter:
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> var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
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> var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
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> {{alias}}.ndarray( N, 1, x, 2, 1 )
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~2.0817
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See Also
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--------
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