acfmperiod
Python port of the original R package acfMPeriod for classical and robust
autocovariance/autocorrelation estimation using periodogram and M-periodogram
methods.
Features
- Univariate and multivariate ACF/ACOVF from periodogram (
PerACF) - Robust ACF/ACOVF from M-periodogram (
MPerACF) - Periodogram and cross-periodogram estimators
- Covariance/correlation matrix wrappers at lag 0 (
CovCorPer,CovCorMPer) - Plotting support for robust and classical outputs
Installation
pip install acfmperiod
For local development:
pip install -e .[dev]
Quick Start
import numpy as np
from acfmperiod import PerACF, MPerACF, CovCorPer
rng = np.random.default_rng(7)
x = rng.normal(size=(128, 2))
res = PerACF(x, lagmax=20, typevalue="correlation", doplot=False)
print(res.acf.shape) # (20, 2, 2)
rob = MPerACF(x, lagmax=20, doplot=False)
cov0 = CovCorPer(x, typevalue="covariance")
print(cov0)
API
PerioReg,MPerioRegCrossPeriodogram,MCrossPeriodogramPerACF,MPerACFCovCorPer,CovCorMPerplotrobacf
Lowercase aliases are available without underscore naming. ß
1 maintainer
Metadata
1 maintainer
Release files for acfmperiod 0.1.0
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