class_docstr: Results of in-sample and out-of-sample prediction for state space models
  generally
  
  Parameters
  ----------
  results : FilterResults
      Output from filtering, corresponding to the prediction desired
  start : int
      Zero-indexed observation number at which to start forecasting,
      i.e., the first forecast will be at start.
  end : int
      Zero-indexed observation number at which to end forecasting, i.e.,
      the last forecast will be at end.
  nstatic : int
      Number of in-sample static predictions (these are always the first
      elements of the prediction output).
  ndynamic : int
      Number of in-sample dynamic predictions (these always follow the static
      predictions directly, and are directly followed by the forecasts).
  nforecast : int
      Number of in-sample forecasts (these always follow the dynamic
      predictions directly).
  
  Attributes
  ----------
  npredictions : int
      Number of observations in the predicted series; this is not necessarily
      the same as the number of observations in the original model from which
      prediction was performed.
  start : int
      Zero-indexed observation number at which to start prediction,
      i.e., the first predict will be at `start`; this is relative to the
      original model from which prediction was performed.
  end : int
      Zero-indexed observation number at which to end prediction,
      i.e., the last predict will be at `end`; this is relative to the
      original model from which prediction was performed.
  nstatic : int
      Number of in-sample static predictions.
  ndynamic : int
      Number of in-sample dynamic predictions.
  nforecast : int
      Number of in-sample forecasts.
  endog : ndarray
      The observation vector.
  design : ndarray
      The design matrix, :math:`Z`.
  obs_intercept : ndarray
      The intercept for the observation equation, :math:`d`.
  obs_cov : ndarray
      The covariance matrix for the observation equation :math:`H`.
  transition : ndarray
      The transition matrix, :math:`T`.
  state_intercept : ndarray
      The intercept for the transition equation, :math:`c`.
  selection : ndarray
      The selection matrix, :math:`R`.
  state_cov : ndarray
      The covariance matrix for the state equation :math:`Q`.
  filtered_state : ndarray
      The filtered state vector at each time period.
  filtered_state_cov : ndarray
      The filtered state covariance matrix at each time period.
  predicted_state : ndarray
      The predicted state vector at each time period.
  predicted_state_cov : ndarray
      The predicted state covariance matrix at each time period.
  forecasts : ndarray
      The one-step-ahead forecasts of observations at each time period.
  forecasts_error : ndarray
      The forecast errors at each time period.
  forecasts_error_cov : ndarray
      The forecast error covariance matrices at each time period.
  
  Notes
  -----
  The provided ranges must be conformable, meaning that it must be that
  `end - start == nstatic + ndynamic + nforecast`.
  
  This class is essentially a view to the FilterResults object, but
  returning the appropriate ranges for everything.
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code: def clear(self):
      attributes = (
          ["endog"]
          + self.representation_attributes
          + self.filter_attributes
      )
      for attr in attributes:
          _attr = "_" + attr
          if hasattr(self, _attr):
              delattr(self, _attr)
  
imports: import contextlib
  from warnings import warn
  import numpy
  from .representation import OptionWrapper, Representation, FrozenRepresentation
  from .tools import reorder_missing_matrix, reorder_missing_vector
  from .None import tools
  from statsmodels.tools.sm_exceptions import ValueWarning
label_desc: Use image node_id 2 for calling the PredictionResults obj's underlying member method code with example usage: obj.clear() without return types