137 lines
4.7 KiB
Plaintext
137 lines
4.7 KiB
Plaintext
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{{alias}}( N, c, x, strideX, out, strideOut )
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Computes the mean and variance of a double-precision floating-point strided
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array using a two-pass algorithm.
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The `N` and `stride` parameters determine which elements are accessed at
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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 a mean and variance equal to `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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c: 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 variance according to `N - c` where `c` corresponds to the
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provided degrees of freedom adjustment. When computing the variance of a
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population, setting this parameter to `0` is the standard choice (i.e.,
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the provided array contains data constituting an entire population).
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When computing the unbiased sample variance, setting this parameter to
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`1` is the standard choice (i.e., the provided array contains data
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sampled from a larger population; this is commonly referred to as
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Bessel's correction).
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x: Float64Array
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Input array.
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strideX: integer
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Index increment for `x`.
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out: Float64Array
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Output array.
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strideOut: integer
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Index increment for `out`.
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Returns
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-------
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out: Float64Array
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Output array.
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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/float64}}( [ 1.0, -2.0, 2.0 ] );
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> var out = new {{alias:@stdlib/array/float64}}( 2 );
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> {{alias}}( x.length, 1, x, 1, out, 1 )
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<Float64Array>[ ~0.3333, ~4.3333 ]
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// Using `N` and `stride` parameters:
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> x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );
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> out = new {{alias:@stdlib/array/float64}}( 2 );
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> var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
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> {{alias}}( N, 1, x, 2, out, 1 )
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<Float64Array>[ ~0.3333, ~4.3333 ]
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// Using view offsets:
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> var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );
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> var x1 = new {{alias:@stdlib/array/float64}}( 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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> out = new {{alias:@stdlib/array/float64}}( 2 );
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> {{alias}}( N, 1, x1, 2, out, 1 )
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<Float64Array>[ ~0.3333, ~4.3333 ]
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{{alias}}.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )
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Computes the mean and variance of a double-precision floating-point strided
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array using a two-pass algorithm and 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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c: 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 variance according to `N - c` where `c` corresponds to the
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provided degrees of freedom adjustment. When computing the variance of a
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population, setting this parameter to `0` is the standard choice (i.e.,
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the provided array contains data constituting an entire population).
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When computing the unbiased sample variance, setting this parameter to
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`1` is the standard choice (i.e., the provided array contains data
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sampled from a larger population; this is commonly referred to as
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Bessel's correction).
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x: Float64Array
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Input array.
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strideX: integer
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Index increment for `x`.
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offsetX: integer
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Starting index for `x`.
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out: Float64Array
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Output array.
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strideOut: integer
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Index increment for `out`.
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offsetOut: integer
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Starting index for `out`.
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Returns
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-------
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out: Float64Array
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Output array.
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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/float64}}( [ 1.0, -2.0, 2.0 ] );
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> var out = new {{alias:@stdlib/array/float64}}( 2 );
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> {{alias}}.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )
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<Float64Array>[ ~0.3333, ~4.3333 ]
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// Using offset parameter:
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> var x = new {{alias:@stdlib/array/float64}}( [ 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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> out = new {{alias:@stdlib/array/float64}}( 2 );
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> {{alias}}.ndarray( N, 1, x, 2, 1, out, 1, 0 )
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<Float64Array>[ ~0.3333, ~4.3333 ]
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See Also
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--------
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