class_docstr: Student's t-distribution (sktime native).
  
  Parameters
  ----------
  mean : float or array of float (1D or 2D)
      mean of the t-distribution distribution
  sd : float or array of float (1D or 2D), must be positive
      standard deviation of the t-distribution distribution
  df : float or array of float (1D or 2D), must be positive
      Degrees of freedom of the t-distribution
  index : pd.Index, optional, default = RangeIndex
  columns : pd.Index, optional, default = RangeIndex
  
  Example
  -------
  >>> from sktime.proba.t import TDistribution
  
  >>> n = TDistribution(mu=[[0, 1], [2, 3], [4, 5]], sigma=1, df=10)
class_docstr_tok: ["Student","'s","t-distribution","(","sktime","native",")",".","Parameters","--","--","--","--","--","mean",":","float","or","array","of","float","(","1D","or","2D",")","mean","of","the","t-distribution","distribution","sd",":","float","or","array","of","float","(","1D","or","2D",")",",","must","be","positive","standard","deviation","of","the","t-distribution","distribution","df",":","float","or","array","of","float","(","1D","or","2D",")",",","must","be","positive","Degrees","of","freedom","of","the","t-distribution","index",":","pd.Index",",","optional",",","default","=","RangeIndex","columns",":","pd.Index",",","optional",",","default","=","RangeIndex","Example","--","--","--","-",">",">",">","from","sktime.proba.t","import","TDistribution",">",">",">","n","=","TDistribution","(","mu=","[","[","0",",","1","]",",","[","2",",","3","]",",","[","4",",","5","]","]",",","sigma=1",",","df=10",")"]
code: def __init__(self, mu, sigma, df=1, index=None, columns=None):
      self.mu = mu
      self.sigma = sigma
      self.df = df
      self.index = index
      self.columns = columns
  
      self._mu, self._sigma, self._df = self._get_bc_params(
          self.mu, self.sigma, self.df
      )
      shape = self._mu.shape
  
      if index is None:
          index = pd.RangeIndex(shape[0])
  
      if columns is None:
          columns = pd.RangeIndex(shape[1])
  
      super().__init__(index=index, columns=columns)
  
file_path: sktime/sktime/proba/t.py
imports: import numpy
  import pandas
  from scipy.special import betaincinv, gamma, hyp2f1, loggamma
  from sktime.proba.base import BaseDistribution
label_desc: Use image node_id 1 to create a new TDistribution object from inherited base classes: BaseDistribution with example: obj = TDistribution(mu, sigma, df, index, columns)