time-to-botec/js/node_modules/@stdlib/stats/incr/mmse/README.md

incrmmse

Compute a moving mean squared error (MSE) incrementally.

For a window of size W, the mean squared error is defined as

Usage

var incrmmse = require( '@stdlib/stats/incr/mmse' );

incrmmse( window )

Returns an accumulator function which incrementally computes a moving mean squared error. The window parameter defines the number of values over which to compute the moving mean squared error.

var accumulator = incrmmse( 3 );

accumulator( [x, y] )

If provided input values x and y, the accumulator function returns an updated mean squared error. If not provided input values x and y, the accumulator function returns the current mean squared error.

var accumulator = incrmmse( 3 );

var m = accumulator();
// returns null

// Fill the window...
m = accumulator( 2.0, 3.0 ); // [(2.0,3.0)]
// returns 1.0

m = accumulator( -1.0, 4.0 ); // [(2.0,3.0), (-1.0,4.0)]
// returns 13.0

m = accumulator( 3.0, 9.0 ); // [(2.0,3.0), (-1.0,4.0), (3.0,9.0)]
// returns ~20.67

// Window begins sliding...
m = accumulator( -7.0, 3.0 ); // [(-1.0,4.0), (3.0,9.0), (-7.0,3.0)]
// returns ~53.67

m = accumulator( -5.0, -3.0 ); // [(3.0,9.0), (-7.0,3.0), (-5.0,-3.0)]
// returns ~46.67

m = accumulator();
// returns ~46.67

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.

Examples

var randu = require( '@stdlib/random/base/randu' );
var incrmmse = require( '@stdlib/stats/incr/mmse' );

var accumulator;
var v1;
var v2;
var i;

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

// For each simulated datum, update the moving mean squared error...
for ( i = 0; i < 100; i++ ) {
    v1 = ( randu()*100.0 ) - 50.0;
    v2 = ( randu()*100.0 ) - 50.0;
    accumulator( v1, v2 );
}
console.log( accumulator() );