iqr_milp: Perform inverse quantile regression by solving mixed integer...

In ChenyueLiu/ivqr: Perform inverse quantile regression by solving mixed integer linear programming

Description

This function is an internal function called inside function "ivqr_fit()"

Usage

iqr_milp(Y, D, X, Z, tau = 0.76, O_pos = NULL, O_neg = NULL,
  cuts = NULL, eps = 1e-14, M = 10, TimeLimit = 300,
  FeasibilityTol = 1e-06, lpsolver = NULL)

Arguments

Y	data for dependent variable Y
D	data for endogenous variable D
X	data for exogenous variable X
Z	data for instrumental variable Z
tau	tau in quantile regression
O_pos	index for residuals whose sign are fixed as positive
O_neg	index for residuals whose sign are fixed as negative
eps	a small number
M	a large number
TimeLimit	gurobi parameter
FeasibilityTol	gurobi parameter
lpsolver	"gurobi","cplexapi","lpsolveapi"

Value

A list containing optimal value, B_D, B_X, B_Z, x and dual variables a

Examples

n=50
pD=3
sample_data<-chen_lee(n,pD)
iqr_milp(Y=sample_data$Y, D=sample_data$D, X = matrix(1, n, 1), Z=sample_data$Z,lpsolver="gurobi") 

ChenyueLiu/ivqr documentation built on Aug. 9, 2020, 7:49 p.m.