class_docstr: A class for conducting inference on multivariate means and correlation.
  
  Parameters
  ----------
  endog : ndarray
      Data to be analyzed
  
  Attributes
  ----------
  endog : ndarray
      Data to be analyzed
  
  nobs : float
      Number of observations
class_docstr_tok: ["A","class","for","conducting","inference","on","multivariate","means","and","correlation",".","Parameters","--","--","--","--","--","endog",":","ndarray","Data","to","be","analyzed","Attributes","--","--","--","--","--","endog",":","ndarray","Data","to","be","analyzed","nobs",":","float","Number","of","observations"]
code: def __init__(self, endog):
      self.endog = endog
      self.nobs = endog.shape[0]
  
imports: import numpy
  from scipy import optimize
  from scipy.stats import chi2, skew, kurtosis
  from statsmodels.base.optimizer import _fit_newton
  import itertools
  from statsmodels.graphics import utils
label_desc: Use image node_id 1 to create a new DescStatMV object from inherited base classes: _OptFuncts with example: obj = DescStatMV(endog)