text: Title: ValueError for backtesting_forecaster when interval is provided
  Body: Hi ! 
  
  I'm trying to use your ``backtesting_forecaster``
  
  and when I use and ask for intervals, it leads to ``ValueError``
  
  When no intervals are asked, all works perfectly:
  
  **[in]:**
  
  ```python
  if __name__ == "__main__":
      import pandas as pd
      from skforecast.ForecasterAutoreg import ForecasterAutoreg
      from skforecast.model_selection import backtesting_forecaster
      from sklearn.ensemble import RandomForestRegressor
  
      y_train = pd.Series([479.157, 478.475, 481.205, 492.467, 490.42, 508.166, 523.182,
                           499.634, 495.88, 494.174, 494.174, 490.078, 490.078, 495.539,
                           488.713, 485.3, 493.491, 492.126, 493.832, 485.983, 481.887,
                           474.379, 433.084, 456.633, 477.451, 468.919, 484.959, 471.99,
                           486.324, 498.61, 517.381, 485.3, 480.864, 485.983, 484.276,
                           490.761, 490.078, 494.515, 495.88, 493.15, 491.443, 490.42,
                           485.3, 485.3, 486.665, 467.895, 441.616, 469.601, 477.11,
                           486.324, 485.3, 489.054, 494.856, 513.968, 544.683, 557.31,
                           574.374, 603.383, 617.034, 621.812, 627.273, 612.598, 598.605,
                           610.891, 598.605, 563.112, 542.635, 536.492, 499.634, 456.633,
                           431.037, 453.903, 464.141, 454.244, 456.633, 476.768, 495.88,
                           523.524, 537.516, 577.787, 600.994, 616.693, 631.71, 636.487,
                           621.471, 635.805, 625.908, 616.011, 581.2, 565.842, 553.556,
                           570.279, 514.992, 483.253, 460.046, 469.26, 475.745, 478.816,
                           482.57, 506.801, 510.896])
  
  
  
      backtesting_forecaster(
          forecaster=ForecasterAutoreg(regressor=RandomForestRegressor(random_state=42), lags=10),
          y=y_train,
          steps=24,
          metric="mean_absolute_percentage_error",
          initial_train_size=14,
          n_boot=50,
      )
  ```
  **[out]:**
  ```python
  (array([0.07647964]),
             pred
   14   493.40924
   15   493.17717
   16   492.99968
   17   492.98603
   18   492.69932
   ..         ...
   96   492.98603
   97   492.98603
   98   492.98603
   99   492.98603
   100  492.98603
   
   [87 rows x 1 columns])
  ```
  
  however asking for intervals leads to ``ValueError``
  
  **[in]:**
  
  ```python
  if __name__ == "__main__":
      import pandas as pd
      from skforecast.ForecasterAutoreg import ForecasterAutoreg
      from skforecast.model_selection import backtesting_forecaster
      from sklearn.ensemble import RandomForestRegressor
  
      y_train = pd.Series([479.157, 478.475, 481.205, 492.467, 490.42, 508.166, 523.182,
                           499.634, 495.88, 494.174, 494.174, 490.078, 490.078, 495.539,
                           488.713, 485.3, 493.491, 492.126, 493.832, 485.983, 481.887,
                           474.379, 433.084, 456.633, 477.451, 468.919, 484.959, 471.99,
                           486.324, 498.61, 517.381, 485.3, 480.864, 485.983, 484.276,
                           490.761, 490.078, 494.515, 495.88, 493.15, 491.443, 490.42,
                           485.3, 485.3, 486.665, 467.895, 441.616, 469.601, 477.11,
                           486.324, 485.3, 489.054, 494.856, 513.968, 544.683, 557.31,
                           574.374, 603.383, 617.034, 621.812, 627.273, 612.598, 598.605,
                           610.891, 598.605, 563.112, 542.635, 536.492, 499.634, 456.633,
                           431.037, 453.903, 464.141, 454.244, 456.633, 476.768, 495.88,
                           523.524, 537.516, 577.787, 600.994, 616.693, 631.71, 636.487,
                           621.471, 635.805, 625.908, 616.011, 581.2, 565.842, 553.556,
                           570.279, 514.992, 483.253, 460.046, 469.26, 475.745, 478.816,
                           482.57, 506.801, 510.896])
  
  
  
      backtesting_forecaster(
          forecaster=ForecasterAutoreg(regressor=RandomForestRegressor(random_state=42), lags=10),
          y=y_train,
          steps=24,
          metric="mean_absolute_percentage_error",
          initial_train_size=14,
          interval=[95],
          n_boot=50,
      )
  ```
  
  **[out]:**
  
  ```python
  Traceback (most recent call last):
    File "...\lib\site-packages\IPython\core\interactiveshell.py", line 3398, in run_code
      exec(code_obj, self.user_global_ns, self.user_ns)
    File "<ipython-input-6-9cd2f471a2e7>", line 22, in <cell line: 22>
      backtesting_forecaster(
    File "...\lib\site-packages\skforecast\model_selection\model_selection.py", line 925, in backtesting_forecaster
      metric_value, backtest_predictions = _backtesting_forecaster_no_refit(
    File "...\lib\site-packages\skforecast\model_selection\model_selection.py", line 705, in _backtesting_forecaster_no_refit
      pred = forecaster.predict_interval(
    File "...\lib\site-packages\skforecast\ForecasterAutoreg\ForecasterAutoreg.py", line 757, in predict_interval
      predictions = pd.DataFrame(
    File "...\lib\site-packages\pandas\core\frame.py", line 694, in __init__
      mgr = ndarray_to_mgr(
    File "...\lib\site-packages\pandas\core\internals\construction.py", line 351, in ndarray_to_mgr
      _check_values_indices_shape_match(values, index, columns)
    File "...\dev\lib\site-packages\pandas\core\internals\construction.py", line 422, in _check_values_indices_shape_match
      raise ValueError(f"Shape of passed values is {passed}, indices imply {implied}")
  ValueError: Shape of passed values is (24, 2), indices imply (24, 3)
  ```
  