Source code for tailestim.estimators.smooth_hill

"""Smooth Hill estimator implementation for tail index estimation."""

from typing import Any, Dict, Tuple

import numpy as np

from .base import BaseTailEstimator
from .result import TailEstimatorResult
from .tail_methods import smooth_hill_estimator as smooth_hill_estimate




class SmoothHillEstimator(BaseTailEstimator):
    """Smooth Hill estimator for tail index estimation.

    This class implements the Smooth Hill estimator, which applies smoothing
    to the classical Hill estimator. It does not use bootstrap procedures.

    Parameters
    ----------
    r_smooth : int, default=2
        Integer parameter controlling the width of smoothing window.
        Typically small value such as 2 or 3.
    **kwargs : dict
        Additional parameters (not used by this estimator).

    """



    def __init__(self, r_smooth: int = 2, **kwargs):
        # Smooth Hill estimator doesn't use bootstrap
        super().__init__(bootstrap=False, **kwargs)
        self.r_smooth = r_smooth


    def _estimate(self, ordered_data: np.ndarray) -> Tuple:
        """Estimate the tail index using the Smooth Hill method.

        Parameters
        ----------
        ordered_data : np.ndarray
            Data array in decreasing order.

        Returns
        -------
        Tuple
            Contains estimation results from smooth_hill_estimator.
        """
        return smooth_hill_estimate(ordered_data, r_smooth=self.r_smooth)



    def get_params(self) -> Dict[str, Any]:
        """Get the parameters of the estimator.

        Returns
        -------
        dict
            Dictionary containing the parameters of the estimator.
        """
        return {"r_smooth": self.r_smooth, **self.kwargs}




    def get_result(self) -> TailEstimatorResult:
        """Get the estimated parameters.

        Attributes
        ----------
        estimator : BaseTailEstimator
            The estimator instance (e.g., HillEstimator, PickandsEstimator, etc.) used for estimation.
        k_arr : np.ndarray
            Array of order statistics.
        xi_arr : np.ndarray
            Array of tail index estimates.

        Returns
        -------
        TailEstimatorResult
        """
        if self.results is None:
            raise ValueError("Model not fitted yet. Call fit() first.")

        k_arr, xi_arr = self.results

        res = {"estimator": self, "k_arr_": k_arr, "xi_arr_": xi_arr}

        return TailEstimatorResult(res)