Add fit method to each model

[jason-ash]

Allow stochastic models to be fit with historical data. This seems like a BIG task, but important.

Ideas that may be relevant:

• use MLE where appropriate, or possible
• use the "Exact Algorithm"
• add a _transition_density property to each model, where it exists

pyesg/pyesg/diffusion_process.py

Lines 96 to 113 in ddde7ec

	def fit(self, X: np.ndarray, y: np.ndarray):
	"""
	Fits the parameters of the diffusion process based on historical data.
	The exact method of fitting should be defined at the subclass level, because the
	implementation can vary depending on the model.
	Parameters
	----------
	X : np.ndarray, the indices of times/dates of the observed prices
	y : np.ndarray, the observed prices or values on the given dates. If multiple
	indices, then y will be a matrix, where the columns are the indices.
	Returns
	-------
	self
	"""
	raise NotImplementedError()