# import dependencies
from . import CQER, ICNLS
from pyomo.environ import Constraint
from .constant import CET_ADDI, FUN_PROD, RTS_VRS
[docs]
class ICQR(ICNLS.ICNLS, CQER.CQR):
"""Isotonic convex quantile regression (ICQR)
"""
[docs]
def __init__(self, y, x, tau, z=None, cet=CET_ADDI, fun=FUN_PROD, rts=RTS_VRS):
"""ICQR model
Args:
y (float): output variable.
x (float): input variables.
tau (float): quantile.
z (float, optional): Contextual variable(s). Defaults to None.
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.
"""
CQER.CQR.__init__(self, y, x, tau, z, cet, fun, rts)
self._ICNLS__pmatrix = self._ICNLS__binaryMatrix()
self.__model__.afriat_rule.deactivate()
self.__model__.isotonic_afriat_rule = Constraint(self.__model__.I,
self.__model__.I,
rule=self._ICNLS__isotonic_afriat_rule(),
doc='isotonic afriat inequality')
[docs]
class ICER(ICNLS.ICNLS, CQER.CER):
"""Isotonic convex expectile regression (ICER)"""
[docs]
def __init__(self, y, x, tau, z=None, cet=CET_ADDI, fun=FUN_PROD, rts=RTS_VRS):
"""ICER model
Args:
y (float): output variable.
x (float): input variables.
tau (float): expectile.
z (float, optional): Contextual variable(s). Defaults to None.
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.
"""
CQER.CER.__init__(self, y, x, tau, z, cet, fun, rts)
self._ICNLS__pmatrix = self._ICNLS__binaryMatrix()
self.__model__.afriat_rule.deactivate()
self.__model__.isotonic_afriat_rule = Constraint(self.__model__.I,
self.__model__.I,
rule=self._ICNLS__isotonic_afriat_rule(),
doc='isotonic afriat inequality')