58 lines
1.7 KiB
Plaintext
58 lines
1.7 KiB
Plaintext
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{{alias}}( x, y[, options] )
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Locally-weighted polynomial regression via the LOWESS algorithm.
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Parameters
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----------
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x: Array<number>
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x-axis values (abscissa values).
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y: Array<number>
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Corresponding y-axis values (ordinate values).
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options: Object (optional)
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Function options.
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options.f: number (optional)
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Positive number specifying the smoothing span, i.e., the proportion of
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points which influence smoothing at each value. Larger values
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correspond to more smoothing. Default: `2/3`.
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options.nsteps: number (optional)
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Number of iterations in the robust fit (fewer iterations translates to
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faster function execution). If set to zero, the nonrobust fit is
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returned. Default: `3`.
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options.delta: number (optional)
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Nonnegative number which may be used to reduce the number of
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computations. Default: 1/100th of the range of `x`.
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options.sorted: boolean (optional)
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Boolean indicating if the input array `x` is sorted. Default: `false`.
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Returns
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-------
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out: Object
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Object with ordered x-values and fitted values.
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Examples
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--------
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> var x = new {{alias:@stdlib/array/float64}}( 100 );
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> var y = new {{alias:@stdlib/array/float64}}( x.length );
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> for ( var i = 0; i < x.length; i++ ) {
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... x[ i ] = i;
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... y[ i ] = ( 0.5*i ) + ( 10.0*{{alias:@stdlib/random/base/randn}}() );
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... }
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> var out = {{alias}}( x, y );
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> var yhat = out.y;
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> var h = {{alias:@stdlib/plot/ctor}}( [ x, x ], [ y, yhat ] );
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> h.lineStyle = [ 'none', '-' ];
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> h.symbols = [ 'closed-circle', 'none' ];
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> h.view( 'window' );
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See Also
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--------
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