CNLSZG2

class pystoned.utils.CNLSZG2.CNLSZG2(y, x, z, cutactive, active, cet='addi', fun='prod', rts='vrs')[source]

CNLSZ+G in iterative loop

__init__(y, x, z, cutactive, active, cet='addi', fun='prod', rts='vrs')[source]

CNLSZ+G model

Parameters:

  • y (float) – output variable.

  • x (float) – input variables.

  • z (float, optional) – Contextual variable(s). Defaults to None.

  • cutactive (float) – active concavity constraint.

  • active (float) – violated concavity constraint.

  • cet (String, optional) – CET_ADDI (additive composite error term) or CET_MULT (multiplicative composite error term). Defaults to CET_ADDI.

  • fun (String, optional) – FUN_PROD (production frontier) or FUN_COST (cost frontier). Defaults to FUN_PROD.

  • rts (String, optional) – RTS_VRS (variable returns to scale) or RTS_CRS (constant returns to scale). Defaults to RTS_VRS.

get_alpha()[source]

Return alpha value by array

get_beta()[source]

Return beta value by array

optimize(email='local', solver=None)[source]

Optimize the function by requested method

Parameters:

  • email (string) – The email address for remote optimization. It will optimize locally if OPT_LOCAL is given.

  • solver (string) – The solver chosen for optimization. It will optimize with default solver if OPT_DEFAULT is given.