def fit(self, x, y):
x1 = Accumulation.ago(y, None, True)
z1 = ModelMethods.based(x1)
ones_array = np.diff(x).astype(np.float64)
ones_array = ones_array.reshape([-1, 1])
B = ModelMethods.construct_matrix(-z1, ones_array)
self.x_orig = y
self.params = ModelMethods.get_params(B, x1)
return self
def fit(self, x, y):
x1 = NewInformationPriorityAccumulation.nipago(y, self.r)
z1 = ModelMethods.based(x1)
ones_array = np.diff(x).astype(np.float64)
ones_array = ones_array.reshape([-1, 1])
range_array = np.arange(len(x) - 1)
range_array = range_array.reshape([-1, 1])
B1 = ModelMethods.construct_matrix(-z1, range_array)
B = ModelMethods.construct_matrix(-B1, ones_array)
self.x_orig = y
self.params = ModelMethods.get_params(B, x1)
self.x1 = x1
return self
def fit(self, x, y):
x1 = Accumulation.ago(y, None, True)
z1 = ModelMethods.based(x1)
ones_array = np.diff(x).astype(np.float64)
ones_array = ones_array.reshape([-1, 1])
range_array = np.arange(len(x) - 1)
range_array = range_array.reshape([-1, 1])
B1 = ModelMethods.construct_matrix(-z1, range_array)
self.B = ModelMethods.construct_matrix(-B1, ones_array)
self.x_orig = y
self.params = ModelMethods.get_params(self.B, x1)
self.x1 = x1
self.is_fitted = True
return self
