code: def agresti_coull_sem(
      n_numer: Union[pd.Series, np.ndarray, int],
      n_denom: Union[pd.Series, np.ndarray, int],
      prior_successes: int = 2,
      prior_failures: int = 2,
  ) -> Union[np.ndarray, float]:
      """Compute the Agresti-Coull style standard error for a binomial proportion.
  
      Reference:
      *Agresti, Alan, and Brent A. Coull. Approximate Is Better than 'Exact' for
      Interval Estimation of Binomial Proportions." The American Statistician,
      vol. 52, no. 2, 1998, pp. 119-126. JSTOR, www.jstor.org/stable/2685469.*
  
      """
      n_numer = np.array(n_numer)
      n_denom = np.array(n_denom)
      p_for_sem = (n_numer + prior_successes) / (
          n_denom + prior_successes + prior_failures
      )
      sem = np.sqrt(p_for_sem * (1 - p_for_sem) / n_denom)
      return sem
  
file_path: Ax/ax/utils/stats/statstools.py
imports: from logging import Logger
  from typing import List, Tuple, Union
  import numpy
  import pandas
  from ax.core.data import Data
  from ax.utils.common.logger import get_logger
label_desc: Use image node_id 6 for calling a global function with example usage: agresti_coull_sem(n_numer, n_denom, prior_successes, prior_failures) and returns: sem