tensorflow_probability/python/internal/special_math.py
def _log_ndtr_lower(x, series_order):
  """Asymptotic expansion version of `Log[cdf(x)]`, appropriate for `x<<-1`."""
  x_2 = tf.square(x)
  # Log of the term multiplying (1 + sum)
  log_scale = -0.5 * x_2 - tf.math.log(-x) - 0.5 * np.log(2. * np.pi)
  return log_scale + tf.math.log(_log_ndtr_asymptotic_series(x, series_order))
def _log_ndtr_lower(x, series_order):
  """Asymptotic expansion version of `Log[cdf(x)]`, appropriate for `x<<-1`."""
  x_2 = tf.square(x)
  # Log of the term multiplying (1 + sum)
  log_scale = -0.5 * x_2 - tf.math.log(-x) - 0.5 * np.log(2. * np.pi)
  return log_scale + tf.math.log(_log_ndtr_asymptotic_series(x, series_order))
def _log_ndtr_lower ( x , series_order ) : x_2 = tf . square ( x ) # Log of the term multiplying (1 + sum) log_scale = - 0.5 * x_2 - tf . math . log ( - x ) - 0.5 * np . log ( 2. * np . pi ) return log_scale + tf . math . log ( _log_ndtr_asymptotic_series ( x , series_order ) )
Asymptotic expansion version of `Log[cdf(x)]`, appropriate for `x<<-1`.
Asymptotic expansion version of Log [ cdf ( x ) ] appropriate for x<< - 1 .