make_plr_CCDDHNR2018 {DoubleML} | R Documentation |
Generates data from a partially linear regression model used in
Chernozhukov et al. (2018)
Description
Generates data from a partially linear regression model used in
Chernozhukov et al. (2018) for Figure 1.
The data generating process is defined as
di=m0(xi)+s1vi,
yi=αdi+g0(xi)+s2ζi,
with vi∼N(0,1)
and
ζi∼N(0,1),
.
The covariates are distributed as xi∼N(0,Σ)
,
where Σ
is a matrix with entries Σkj=0.7∣j−k∣
.
The nuisance functions are given by
m0(xi)=a0xi,1+a11+exp(xi,3)exp(xi,3),
g0(xi)=b01+exp(xi,1)exp(xi,1)+b1xi,3,
with a0=1
, a1=0.25
, s1=1
, b0=1
, b1=0.25
,
s2=1
.
Usage
make_plr_CCDDHNR2018(
n_obs = 500,
dim_x = 20,
alpha = 0.5,
return_type = "DoubleMLData"
)
Arguments
n_obs |
(integer(1) )
The number of observations to simulate.
|
dim_x |
(integer(1) )
The number of covariates.
|
alpha |
(numeric(1) )
The value of the causal parameter.
|
return_type |
(character(1) )
If "DoubleMLData" , returns a DoubleMLData object.
If "data.frame" returns a data.frame() .
If "data.table" returns a data.table() .
If "matrix" a named list() with entries X , y and d is returned.
Every entry in the list is a matrix() object. Default is "DoubleMLData" .
|
Value
A data object according to the choice of return_type
.
References
Chernozhukov, V., Chetverikov, D., Demirer, M., Duflo, E.,
Hansen, C., Newey, W. and Robins, J. (2018), Double/debiased machine learning
for treatment and structural parameters.
The Econometrics Journal, 21: C1-C68. doi:10.1111/ectj.12097.
[Package
DoubleML version 1.0.1
Index]