A mini-package for computing the running mean, variance, kurtosis and skew
No dependencies ... not even numpy.
No classes ... unless you want them.
State is a dict, for trivial serialization.
Tested against scipy, creme, statistics
Install
%pip install momentum
Usage: running mean, var
from momentum import var_init, var_update
from pprint import pprint
m = var_init()
for x in [5,3,2.4,1.0,5.0]:
m = var_update(m,x)
pprint(m)
Usage: running mean, var, kurtosis and skew
from momentum import kurtosis_init, kurtosis_update
m = kurtosis_init()
for x in [5,3,2.4,1.0,5.0]:
m = kurtosis_update(m,x)
pprint(m)
File an issue if you need more help using this.
Usage: running recency-weighted mean, var
from momentum import forgettingvar_init, forgettingvar_update
from pprint import pprint
m = rvar_init(rho=0.01,n=15)
for x in [5,3,2.4,1.0,5.0]:
m = rvar_update(m,x)
pprint(m)
This will switch from running variance to a weighted variance after 15 data points.
