def _conf_set(F, alpha=0.05):
 nobs = len(F)
 epsilon = np.sqrt((np.log((2.0 / alpha)) / (2 * nobs)))
 lower = np.clip((F - epsilon), 0, 1)
 upper = np.clip((F + epsilon), 0, 1)
 return (lower, upper)

def _conf_set ( F , alpha = 0.05 ) : nobs = len ( F ) epsilon = np . sqrt ( ( np . log ( ( 2.0 / alpha ) ) / ( 2 * nobs ) ) ) lower = np . clip ( ( F - epsilon ) , 0 , 1 ) upper = np . clip ( ( F + epsilon ) , 0 , 1 ) return ( lower , upper )
constructs a dvoretzky-kiefer-wolfowitz confidence band for the ecdf .