drafting AIC/BIC function

skgstat/util/cross_validation.py

@@ -1,7 +1,12 @@
+from typing import Callable, List
 import numpy as np
 from itertools import cycle
+from scipy.spatial.distance import squareform
+from numpy.linalg import inv, det
 
 from skgstat.Kriging import OrdinaryKriging
+from skgstat.Variogram import Variogram
+from skgstat.util.likelihood import get_likelihood
 
 
 def _interpolate(idx: int, variogram) -> float:
@@ -70,3 +75,35 @@ def jacknife(
  else:
  # MAE
  return np.nansum(np.abs(deviations)) / len(deviations)
+
+
+def aic(variogram: Variogram) -> float:
+ like = get_likelihood(variogram)
+
+ # get parameters
+ params = variogram.parameters
+ k = len(params)
+ if params[-1] < 1e-6:
+ k -= 1
+
+ # get maximum log-likelihood
+ log_like = like(params)
+
+ # return AIC
+ return 2 * k - 2 * log_like
+
+
+def bic(variogram: Variogram) -> float:
+ like = get_likelihood(variogram)
+
+ # get parameters
+ params = variogram.parameters
+ k = len(params)
+ if params[-1] < 1e-6:
+ k -= 1
+
+ # get maximum log-likelihood
+ log_like = like(params)
+
+ # return BIC
+ return 2 * np.log(k) - 2 * log_like