from arch.compat.numba import jit
from arch.typing import NDArray
def stationary_bootstrap_sample_python(
indices: NDArray, u: NDArray, p: float
) -> NDArray:
"""
Generate indices for sampling from the stationary bootstrap.
Parameters
-------
indices: ndarray
Single-dimensional array containing draws from randint with the same
size as the data in the range of [0,nobs).
u : ndarray
Single-dimensional Array of standard uniforms.
p : float
Probability that a new block is started in the stationary bootstrap.
The multiplicative reciprocal of the window length.
Returns
-------
ndarray
Indices for an iteration of the stationary bootstrap.
"""
num_items = indices.shape[0]
for i in range(1, num_items):
if u[i] > p:
indices[i] = indices[i - 1] + 1
if indices[i] == num_items:
indices[i] = 0
return indices
stationary_bootstrap_sample = jit(stationary_bootstrap_sample_python)