MICE NaN error

[sam.as...@gmail.com]

Hi All,

I'm relatively new to Python and trying to use MICE to impute values for a dataset I am using.

I have managed succesfully with a subset of the matrix. However when processing the entire matrix I get the following error and can't work out why:

ValueError: array must not contain infs or NaNs

Below is a section of my code and the full stack. Any help would be much appreciated!

C:\Users\Sammy\Anaconda3\lib\site-packages\statsmodels\regression\linear_model.py:1353: RuntimeWarning: divide by zero encountered in double_scalars
  return np.dot(wresid, wresid) / self.df_resid

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-14-623fc0308b79> in <module>()
      1 mi = mice.MICE("cost_A ~ PH_T + DAM + Free + Frgn + TIME + MW + Hd + GEN_n + Ht + Lt + R_VOL + CAP + C_VOL + T_KV + T_KM + PH_A + PEN_n + PEN_l + PEN_d + EXc + MT_t + Fl + Rset + GDP_AVG + GDP_CAGR + PPI + CPI + CoC + RoL + RegQ + GvmE + PolS + VcAcc + Free_PR + Free_CL + MUV_CAGR + MUV_avg + SAR_CAGR + USD_CAGR + EDU", sm.OLS, imp)
----> 2 result = mi.fit(20, 5)
      3 print(result.summary())

C:\Users\Sammy\Anaconda3\lib\site-packages\statsmodels\imputation\mice.py in fit(self, n_burnin, n_imputations)
   1226 
   1227         # Run without fitting the analysis model
-> 1228         self.data.update_all(n_burnin)
   1229 
   1230         for j in range(n_imputations):

C:\Users\Sammy\Anaconda3\lib\site-packages\statsmodels\imputation\mice.py in update_all(self, n_iter)
    413         for k in range(n_iter):
    414             for vname in self._cycle_order:
--> 415                 self.update(vname)
    416 
    417         if self.history_callback is not None:

C:\Users\Sammy\Anaconda3\lib\site-packages\statsmodels\imputation\mice.py in update(self, vname)
   1002         """
   1003 
-> 1004         self.perturb_params(vname)
   1005         self.impute(vname)
   1006 

C:\Users\Sammy\Anaconda3\lib\site-packages\statsmodels\imputation\mice.py in perturb_params(self, vname)
    976 
    977         if self.perturbation_method[vname] == "gaussian":
--> 978             self._perturb_gaussian(vname)
    979         elif self.perturbation_method[vname] == "boot":
    980             self._perturb_bootstrap(vname)

C:\Users\Sammy\Anaconda3\lib\site-packages\statsmodels\imputation\mice.py in _perturb_gaussian(self, vname)
    970         cov = self.results[vname].cov_params()
    971         mu = self.results[vname].params
--> 972         self.params[vname] = np.random.multivariate_normal(mean=mu, cov=cov)
    973 
    974 

mtrand.pyx in mtrand.RandomState.multivariate_normal (numpy\random\mtrand\mtrand.c:36911)()

C:\Users\Sammy\Anaconda3\lib\site-packages\scipy\linalg\decomp_svd.py in svd(a, full_matrices, compute_uv, overwrite_a, check_finite, lapack_driver)
     94 
     95     """
---> 96     a1 = _asarray_validated(a, check_finite=check_finite)
     97     if len(a1.shape) != 2:
     98         raise ValueError('expected matrix')

C:\Users\Sammy\Anaconda3\lib\site-packages\scipy\_lib\_util.py in _asarray_validated(a, check_finite, sparse_ok, objects_ok, mask_ok, as_inexact)
    236             raise ValueError('masked arrays are not supported')
    237     toarray = np.asarray_chkfinite if check_finite else np.asarray
--> 238     a = toarray(a)
    239     if not objects_ok:
    240         if a.dtype is np.dtype('O'):

C:\Users\Sammy\Anaconda3\lib\site-packages\numpy\lib\function_base.py in asarray_chkfinite(a, dtype, order)
   1213     if a.dtype.char in typecodes['AllFloat'] and not np.isfinite(a).all():
   1214         raise ValueError(
-> 1215             "array must not contain infs or NaNs")
   1216     return a
   1217 

ValueError: array must not contain infs or NaNs