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# Panel Models
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Fixed effects and random effects panel data models with spatial error and lag specifications for analyzing spatially-correlated panel datasets.
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## Capabilities
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### Fixed Effects Panel Models
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```python { .api }
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class Panel_FE_Error:
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    def __init__(self, y, x, w, epsilon=0.0000001, hard_bound=False, vm=False,
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                 name_y=None, name_x=None, name_w=None, name_ds=None, 
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                 latex=False):
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        """
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        Fixed effects panel spatial error model.
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        Parameters:
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        - y (array): Dependent variable (stacked by time periods)
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        - x (array): Independent variables
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        - w (sparse matrix): Spatial weights matrix
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        """
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class Panel_FE_Lag:
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    def __init__(self, y, x, w, epsilon=0.0000001, hard_bound=False, vm=False,
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                 name_y=None, name_x=None, name_w=None, name_ds=None,
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                 latex=False):
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        """Fixed effects panel spatial lag model."""
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```
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### Random Effects Panel Models
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```python { .api }
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class Panel_RE_Error:
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    def __init__(self, y, x, w, epsilon=0.0000001, hard_bound=False, vm=False,
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                 name_y=None, name_x=None, name_w=None, name_ds=None,
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                 latex=False):
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        """Random effects panel spatial error model."""
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class Panel_RE_Lag:
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    def __init__(self, y, x, w, epsilon=0.0000001, hard_bound=False, vm=False,
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                 name_y=None, name_x=None, name_w=None, name_ds=None,
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                 latex=False):
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        """Random effects panel spatial lag model."""
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```