Returns a bootstraped sample of the time-series "data" of length "sampleLength.
- StationaryBootstrap(data: ndarray, m, sampleLength) ndarray #
Returns a bootstraped sample of the time-series “data” of length “sampleLength.
The algorithm used is stationary bootstrap from 1994 Politis & Romano.
data – ndarray array. A single vector of numbers containing the time-series.
m – floating number. Parameter to stationary bootstrap indicating the average length of each block in the sample.
sampleLength – integer. Length of the bootstrapped sample returned as output.
ndarray array containing the final bootstraped sample.
- Return type:
>>> import numpy as np >>> data = np.array([1,2,3,4,5,6,7,8,9,10]) >>> m = 4 >>> sampleLength = 12 >>> StationaryBootstrap(data, m, sampleLength) array([[9.], [3.], [4.], [5.], [6.], [7.], [8.], [7.], [2.], [3.], [4.], [2.]])
Original paper about stationary bootstrap: Dimitris N. Politis & Joseph P. Romano (1994) The Stationary Bootstrap, Journal of the American Statistical Association, 89:428, 1303-1313, DOI: 10.1080/01621459.1994.10476870
Implemented by Gregor Fabjan from Qnity Consultants on 12/11/2021.