ivqr_fit: IVQR Inference

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

Description

IVQR Inference

Usage

ivqr_fit(Y, D, X, Z, tau = 0.5, M = 10, homoskedastic = FALSE,
  kernel = "Powell", lpsolver = NULL)

Arguments

D	data for endogenous variable D
X	data for exogenous variable X
Z	data for instrumental variable Z
tau	tau in quantile regression
M	a large number
lpsolver	"gurobi","cplexapi","lpsolveapi"

Value

The lower bound and upper bound for B_D and B_X

Examples

n=50
pD=3
sample_data<-chen_lee(n,pD)
Y=sample_data$Y
D=sample_data$D
Z=sample_data$Z
X = matrix(1, n, 1)
ivqr_fit (Y=Y,D=D,X=X,Z=Z,tau = 0.5,M = 10,homoskedastic = FALSE,kernel = "Powell", lpsolver="gurobi")

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