質問編集履歴
1
追記
test
CHANGED
|
File without changes
|
test
CHANGED
|
@@ -216,9 +216,103 @@
|
|
|
216
216
|
|
|
217
217
|
元データの’を消してみたり、したのですが効果はなし。
|
|
218
218
|
|
|
219
|
-
dateがdatetime型なので
|
|
220
|
-
|
|
221
|
-
|
|
219
|
+
dateがdatetime型なので、
|
|
220
|
+
|
|
221
|
+
以下のコードでint型にしたところ、違うエラーが返ってきました。
|
|
222
|
+
|
|
223
|
+
```
|
|
224
|
+
|
|
225
|
+
def to_integer(dt_time):
|
|
226
|
+
|
|
227
|
+
return 10000*dt_time.year + 100*dt_time.month + dt_time.day
|
|
228
|
+
|
|
229
|
+
|
|
230
|
+
|
|
231
|
+
guests['date'] = guests['date'].apply(to_integer)
|
|
232
|
+
|
|
233
|
+
```
|
|
234
|
+
|
|
235
|
+
|
|
236
|
+
|
|
237
|
+
```
|
|
238
|
+
|
|
239
|
+
---------------------------------------------------------------------------
|
|
240
|
+
|
|
241
|
+
ValueError Traceback (most recent call last)
|
|
242
|
+
|
|
243
|
+
<ipython-input-12-d64133e2c242> in <module>
|
|
244
|
+
|
|
245
|
+
3
|
|
246
|
+
|
|
247
|
+
4 #最尤法によるパラメーターの推定
|
|
248
|
+
|
|
249
|
+
----> 5 res_local_level = mod_local_level.fit()
|
|
250
|
+
|
|
251
|
+
6
|
|
252
|
+
|
|
253
|
+
7 #推定されたパラメーター一覧
|
|
254
|
+
|
|
255
|
+
|
|
256
|
+
|
|
257
|
+
c:\users\lib\site-packages\statsmodels\tsa\statespace\mlemodel.py in fit(self, start_params, transformed, includes_fixed, cov_type, cov_kwds, method, maxiter, full_output, disp, callback, return_params, optim_score, optim_complex_step, optim_hessian, flags, low_memory, **kwargs)
|
|
258
|
+
|
|
259
|
+
605 """
|
|
260
|
+
|
|
261
|
+
606 if start_params is None:
|
|
262
|
+
|
|
263
|
+
--> 607 start_params = self.start_params
|
|
264
|
+
|
|
265
|
+
608 transformed = True
|
|
266
|
+
|
|
267
|
+
609 includes_fixed = True
|
|
268
|
+
|
|
269
|
+
|
|
270
|
+
|
|
271
|
+
c:\users\lib\site-packages\statsmodels\tsa\statespace\structural.py in start_params(self)
|
|
272
|
+
|
|
273
|
+
846 _start_params = {}
|
|
274
|
+
|
|
275
|
+
847 if self.level:
|
|
276
|
+
|
|
277
|
+
--> 848 resid, trend1 = hpfilter(endog)
|
|
278
|
+
|
|
279
|
+
849
|
|
280
|
+
|
|
281
|
+
850 if self.stochastic_trend:
|
|
282
|
+
|
|
283
|
+
|
|
284
|
+
|
|
285
|
+
c:\users\lib\site-packages\statsmodels\tsa\filters\hp_filter.py in hpfilter(x, lamb)
|
|
286
|
+
|
|
287
|
+
88 """
|
|
288
|
+
|
|
289
|
+
89 pw = PandasWrapper(x)
|
|
290
|
+
|
|
291
|
+
---> 90 x = array_like(x, 'x', ndim=1)
|
|
292
|
+
|
|
293
|
+
91 nobs = len(x)
|
|
294
|
+
|
|
295
|
+
92 I = sparse.eye(nobs, nobs) # noqa:E741
|
|
296
|
+
|
|
297
|
+
|
|
298
|
+
|
|
299
|
+
c:\users\lib\site-packages\statsmodels\tools\validation\validation.py in array_like(obj, name, dtype, ndim, maxdim, shape, order, contiguous, optional)
|
|
300
|
+
|
|
301
|
+
134 if arr.ndim != ndim:
|
|
302
|
+
|
|
303
|
+
135 msg = '{0} is required to have ndim {1} but has ndim {2}'
|
|
304
|
+
|
|
305
|
+
--> 136 raise ValueError(msg.format(name, ndim, arr.ndim))
|
|
306
|
+
|
|
307
|
+
137 if shape is not None:
|
|
308
|
+
|
|
309
|
+
138 for actual, req in zip(arr.shape, shape):
|
|
310
|
+
|
|
311
|
+
|
|
312
|
+
|
|
313
|
+
ValueError: x is required to have ndim 1 but has ndim 2
|
|
314
|
+
|
|
315
|
+
```
|
|
222
316
|
|
|
223
317
|
|
|
224
318
|
|