Open firmai opened 8 months ago
--------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In[13], line 4 1 import time 3 tic = time.time() ----> 4 result = var_lingam.run(pvalue_thres=0.03, max_lag=max_lag) 5 toc = time.time() 6 print(f'Time taken: {toc-tic:.2f}s\n') in VARLINGAM.run(self, pvalue_thres, max_lag) 76 data_array_ret, = self.data.data_arrays 77 model = lingam.VARLiNGAM(max_lag) ---> 78 model.fit(data_array_ret) 82 all_parents = {} 83 for var_idx in range(model.adjacency_matrices_.shape[1]): VARLiNGAM.fit(self, X) 92 M_taus = self._ar_coefs 94 if M_taus is None: ---> 95 M_taus, lags, residuals = self._estimate_var_coefs(X) 96 else: 97 lags = M_taus.shape[0] VARLiNGAM._estimate_var_coefs(self, X) 277 for lag in range(1, self._lags + 1): 278 var = VAR(X) --> 279 fitted = var.fit(maxlags=lag, ic=None, trend="nc") 281 value = getattr(fitted, self._criterion) 282 if value < min_value: VAR.fit(self, maxlags, method, ic, trend, verbose) 654 lags = maxlags 655 if trend not in ["c", "ct", "ctt", "n"]: --> 656 raise ValueError("trend '{}' not supported for VAR".format(trend)) 658 if ic is not None: 659 selections = self.select_order(maxlags=maxlags)
import time tic = time.time() result = var_lingam.run(pvalue_thres=0.03, max_lag=max_lag) toc = time.time() print(f'Time taken: {toc-tic:.2f}s\n') print(f' The output graph_dict has keys: {result.keys()}')