preprocess_iqr_milp: Preprocess and call iqr_milp

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

Description

Preprocess and call iqr_milp

Usage

preprocess_iqr_milp(Y, D, X, Z, tau = 0.5, eps = 1e-14, M = 10,
  TimeLimit = 300, FeasibilityTol = 1e-06, r = 1.1,
  prop_fixed_start = 0.4, lpsolver = NULL)

Arguments

Y	data for dependent variable Y passed into iqr_milp
D	data for endogenous variable D passed into iqr_milp
X	data for exogenous variable X passed into iqr_milp
Z	data for instrumental variable Z passed into iqr_milp
tau	tau in quantile regression passed into iqr_milp
eps	a small number passed into iqr_milp
M	a large number passed into iqr_milp
TimeLimit	gurobi parameter passed into iqr_milp
FeasibilityTol	gurobi parameter passed into iqr_milp
r	the rate at which we increase bandwidth
prop_fixed_start	the starting paramter for bandwidth
lpsolver	"gurobi","cplexapi","lpsolveapi"

Value

A list containing the iqr_milp return, the time consumed, the index of residuals whose signs are fixed

Examples

n=50
pD=3
sample_data<-chen_lee(n,pD)
preprocess_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.