incrmpcorrdist

Compute a moving sample Pearson product-moment correlation distance incrementally.

The sample Pearson product-moment correlation distance is defined as

where r is the sample Pearson product-moment correlation coefficient, cov(x,y) is the sample covariance, and σ corresponds to the sample standard deviation. As r resides on the interval [-1,1], d resides on the interval [0,2].

Usage

var incrmpcorrdist = require( '@stdlib/stats/incr/mpcorrdist' );


incrmpcorrdist( window[, mx, my] )

Returns an accumulator function which incrementally computes a moving sample Pearson product-moment correlation distance. The window parameter defines the number of values over which to compute the moving sample Pearson product-moment correlation distance.

var accumulator = incrmpcorrdist( 3 );


If means are already known, provide mx and my arguments.

var accumulator = incrmpcorrdist( 3, 5.0, -3.14 );


accumulator( [x, y] )

If provided input values x and y, the accumulator function returns an updated sample Pearson product-moment correlation distance. If not provided input values x and y, the accumulator function returns the current sample Pearson product-moment correlation distance.

var accumulator = incrmpcorrdist( 3 );

var r = accumulator();
// returns null

// Fill the window...
r = accumulator( 2.0, 1.0 ); // [(2.0, 1.0)]
// returns 1.0

r = accumulator( -5.0, 3.14 ); // [(2.0, 1.0), (-5.0, 3.14)]
// returns ~2.0

r = accumulator( 3.0, -1.0 ); // [(2.0, 1.0), (-5.0, 3.14), (3.0, -1.0)]
// returns ~1.925

// Window begins sliding...
r = accumulator( 5.0, -9.5 ); // [(-5.0, 3.14), (3.0, -1.0), (5.0, -9.5)]
// returns ~1.863

r = accumulator( -5.0, 1.5 ); // [(3.0, -1.0), (5.0, -9.5), (-5.0, 1.5)]
// returns ~1.803

r = accumulator();
// returns ~1.803


Notes

• Input values are not type checked. If provided NaN or a value which, when used in computations, results in NaN, the accumulated value is NaN for at least W-1 future invocations. If non-numeric inputs are possible, you are advised to type check and handle accordingly before passing the value to the accumulator function.
• As W (x,y) pairs are needed to fill the window buffer, the first W-1 returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values.
• Due to limitations inherent in representing numeric values using floating-point format (i.e., the inability to represent numeric values with infinite precision), the sample correlation distance between perfectly correlated random variables may not be 0 or 2. In fact, the sample correlation distance is not guaranteed to be strictly on the interval [0,2]. Any computed distance should, however, be within floating-point roundoff error.

Examples

var randu = require( '@stdlib/random/base/randu' );
var incrmpcorrdist = require( '@stdlib/stats/incr/mpcorrdist' );

var accumulator;
var x;
var y;
var i;

// Initialize an accumulator:
accumulator = incrmpcorrdist( 5 );

// For each simulated datum, update the moving sample correlation distance...
for ( i = 0; i < 100; i++ ) {
x = randu() * 100.0;
y = randu() * 100.0;
accumulator( x, y );
}
console.log( accumulator() );