ruspy.estimation.mpec.mpec_loglike_cost_params

ruspy.estimation.mpec.mpec_loglike_cost_params(maint_func, maint_func_dev, num_states, num_params, state_mat, decision_mat, disc_fac, scale, gradient, mpec_params, grad)

Calculate the negative partial log likelihood for MPEC depending on cost parameters as well as the discretized expected values.

Parameters

maint_func: func

see Maintenance cost function

maint_func_dev: func

see Maintenance cost function

num_statespython:int

The size of the state space.

num_paramspython:int

Length of cost parameter vector.

state_matnumpy.array

see State matrix

decision_matnumpy.array

see Decision Matrix

disc_facnumpy.float

see Discount factor

scalenumpy.float

see Scale

gradientpython:str

Indicates whether analytical or numerical gradient should be used.

mpec_paramsnumpy.array

see MPEC

gradnumpy.array, optional

The gradient of the function. The default is np.array([]).

Returns

log_like: python:float

Contains the negative partial log likelihood for the given parameters.