class_docstr: Normal distribution (sktime native).
  
  Parameters
  ----------
  mean : float or array of float (1D or 2D)
      mean of the normal distribution
  sd : float or array of float (1D or 2D), must be positive
      standard deviation of the normal distribution
  index : pd.Index, optional, default = RangeIndex
  columns : pd.Index, optional, default = RangeIndex
  
  Example
  -------
  >>> from sktime.proba.normal import Normal
  
  >>> n = Normal(mu=[[0, 1], [2, 3], [4, 5]], sigma=1)
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docstr: Logarithmic probability density function.
docstr_tok: ["Logarithmic","probability","density","function","."]
code: def log_pdf(self, x):
      """Logarithmic probability density function."""
      d = self.loc[x.index, x.columns]
      lpdf_arr = -0.5 * ((x.values - d.mu) / d.sigma) ** 2
      lpdf_arr = lpdf_arr - np.log(d.sigma * np.sqrt(2 * np.pi))
      return pd.DataFrame(lpdf_arr, index=x.index, columns=x.columns)
  
file_path: sktime/sktime/proba/normal.py
imports: import numpy
  import pandas
  from scipy.special import erf, erfinv
  from sktime.proba.base import BaseDistribution
label_desc: Use image node_id 6 for calling the Normal obj's underlying member method code with example usage: obj.log_pdf(x) and returns: pd