content: # -*- coding: utf-8 -*-
  """
  
  Created on Sun May 26 13:23:40 2013
  
  Author: Josef Perktold, based on Enrico Giampieri's multiOLS
  """
  
  #import numpy as np
  import pandas as pd
  
  import statsmodels.api as sm
  from statsmodels.sandbox.multilinear import multiOLS, multigroup
  
  data = sm.datasets.longley.load_pandas()
  df = data.exog
  df['TOTEMP'] = data.endog
  
  #This will perform the specified linear model on all the
  #other columns of the dataframe
  res0 = multiOLS('GNP + 1', df)
  
  #This select only a certain subset of the columns
  res = multiOLS('GNP + 0', df, ['GNPDEFL', 'TOTEMP', 'POP'])
  print(res.to_string())
  
  
  url = "http://vincentarelbundock.github.com/"
  url = url + "Rdatasets/csv/HistData/Guerry.csv"
  df = pd.read_csv(url, index_col=1) #'dept')
  
  #evaluate the relationship between the various parameters whith the Wealth
  pvals = multiOLS('Wealth', df)['adj_pvals', '_f_test']
  
  #define the groups
  groups = {}
  groups['crime'] = ['Crime_prop', 'Infanticide',
                     'Crime_parents', 'Desertion', 'Crime_pers']
  groups['religion'] = ['Donation_clergy', 'Clergy', 'Donations']
  groups['wealth'] = ['Commerce', 'Lottery', 'Instruction', 'Literacy']
  
  #do the analysis of the significance
  res3 = multigroup(pvals < 0.05, groups)
  print(res3)
  