copulas.optimize package¶
Module contents¶
Copulas optimization functions.
-
copulas.optimize.
bisect
(f, xmin, xmax, tol=1e-08, maxiter=50)[source]¶ Bisection method for finding roots.
This method implements a simple vectorized routine for identifying the root (of a monotonically increasing function) given a bracketing interval.
- Parameters
f (Callable) – A function which takes as input a vector x and returns a vector with the same number of dimensions.
xmin (np.ndarray) – The minimum value for x such that f(x) <= 0.
xmax (np.ndarray) – The maximum value for x such that f(x) >= 0.
- Returns
The value of x such that f(x) is close to 0.
- Return type
numpy.ndarray
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copulas.optimize.
chandrupatla
(f, xmin, xmax, eps_m=None, eps_a=None, maxiter=50)[source]¶ Chandrupatla’s algorithm.
This is adapted from [1] which implements Chandrupatla’s algorithm [2] which starts from a bracketing interval and, conditionally, swaps between bisection and inverse quadratic interpolation.
[1] https://github.com/scipy/scipy/issues/7242#issuecomment-290548427 [2] https://books.google.com/books?id=cC-8BAAAQBAJ&pg=PA95
- Parameters
f (Callable) – A function which takes as input a vector x and returns a vector with the same number of dimensions.
xmin (np.ndarray) – The minimum value for x such that f(x) <= 0.
xmax (np.ndarray) – The maximum value for x such that f(x) >= 0.
- Returns
The value of x such that f(x) is close to 0.
- Return type
numpy.ndarray