code: def _median_bias(n: int) -> Array:
      """
      Returns the bias of the median of a set of periodograms relative to
      the mean. See Appendix B from [1]_ for details.
  
      Args:
       n : int
          Numbers of periodograms being averaged.
  
      Returns:
        bias : float
          Calculated bias.
  
      References:
      .. [1] B. Allen, W.G. Anderson, P.R. Brady, D.A. Brown, J.D.E. Creighton.
              "FINDCHIRP: an algorithm for detection of gravitational waves from
              inspiraling compact binaries", Physical Review D 85, 2012,
              :arxiv:`gr-qc/0509116`
      """
      ii_2 = jnp.arange(2.0, n, 2)
      return 1 + jnp.sum(1.0 / (ii_2 + 1) - 1.0 / ii_2)
  
file_path: jax/jax/_src/third_party/scipy/signal_helper.py
imports: from __future__ import annotations
  import scipy.signal
  from typing import Any
  import warnings
  import jax.numpy
  from jax._src.typing import Array, ArrayLike, DTypeLike
label_desc: Use image node_id 2 for calling a global function with example usage: _median_bias(n) and returns: unknown