incrkurtosis
Compute a corrected sample excess kurtosis incrementally.
The kurtosis for a random variable X
is defined as
Using a univariate normal distribution as the standard of comparison, the excess kurtosis is the kurtosis minus 3
.
For a sample of n
values, the sample excess kurtosis is
where m_4
is the sample fourth central moment and m_2
is the sample second central moment.
The previous equation is, however, a biased estimator of the population excess kurtosis. An alternative estimator which is unbiased under normality is
Usage
var incrkurtosis = require( '@stdlib/stats/incr/kurtosis' );
incrkurtosis()
Returns an accumulator function
which incrementally computes a corrected sample excess kurtosis.
var accumulator = incrkurtosis();
accumulator( [x] )
If provided an input value x
, the accumulator function returns an updated corrected sample excess kurtosis. If not provided an input value x
, the accumulator function returns the current corrected sample excess kurtosis.
var accumulator = incrkurtosis();
var kurtosis = accumulator( 2.0 );
// returns null
kurtosis = accumulator( 2.0 );
// returns null
kurtosis = accumulator( -4.0 );
// returns null
kurtosis = accumulator( -4.0 );
// returns -6.0
Notes
- Input values are not type checked. If provided
NaN
or a value which, when used in computations, results inNaN
, the accumulated value isNaN
for all 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.
Examples
var randu = require( '@stdlib/random/base/randu' );
var incrkurtosis = require( '@stdlib/stats/incr/kurtosis' );
var accumulator;
var v;
var i;
// Initialize an accumulator:
accumulator = incrkurtosis();
// For each simulated datum, update the corrected sample excess kurtosis...
for ( i = 0; i < 100; i++ ) {
v = randu() * 100.0;
accumulator( v );
}
console.log( accumulator() );
References
- Joanes, D. N., and C. A. Gill. 1998. "Comparing measures of sample skewness and kurtosis." Journal of the Royal Statistical Society: Series D (The Statistician) 47 (1). Blackwell Publishers Ltd: 183–89. doi:10.1111/1467-9884.00122.