def pearsonr_with_confidence_interval()

in tseval/qats.py [0:0]

• 24 lines of code
• 2 McCabe index (conditional complexity)

def pearsonr_with_confidence_interval(x, y, alpha=0.05):
    ''' calculate Pearson correlation along with the confidence interval using scipy and numpy
    Parameters
    ----------
    x, y : iterable object such as a list or np.array
      Input for correlation calculation
    alpha : float
      Significance level. 0.05 by default
    Returns
    -------
    r : float
      Pearson's correlation coefficient
    pval : float
      The corresponding p value
    lo, hi : float
      The lower and upper bound of confidence intervals
    '''
    r, p = scipy.stats.pearsonr(x, y)
    r_z = np.arctanh(r)
    se = 1/np.sqrt(len(x) - 3)
    z = scipy.stats.norm.ppf(1 - alpha/2)
    lo_z, hi_z = r_z - z*se, r_z + z*se
    lo, hi = np.tanh((lo_z, hi_z))
    return r, p, lo, hi