sim_data: Simulated data.
In tetokawata/simulater: Simulate prediction and estimation performance
Description
Usage
Arguments
Value
References
Examples
Description
sim_data is used to generate simulate estimated with sparse linear. Assume Y = -5D + 25var1_square + u and D = -5var1_square.
Usage
1
sim_data(nunber_sample, number_covariate)
Arguments
nunber_sample
number of sample in simulated data.
number_covariate
number of covariates.
Value
A dataframe containing follows:
vari
ith control
vari_square
squated ith control
Y
Outcome correlated with var1
D
Treatment correlated with var2
References
No.
Examples
1
sim <- sim_data(nunber_sample = 1000, number_covariate = 5)
tetokawata/simulater documentation built on Dec. 23, 2021, 8:48 a.m.
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Description Usage Arguments Value References Examples
Description
sim_data is used to generate simulate estimated with sparse linear. Assume Y = -5D + 25var1_square + u and D = -5var1_square.
Usage
1 | sim_data(nunber_sample, number_covariate)
|
Arguments
nunber_sample |
number of sample in simulated data. |
number_covariate |
number of covariates. |
Value
A dataframe containing follows:
vari |
ith control |
vari_square |
squated ith control |
Y |
Outcome correlated with var1 |
D |
Treatment correlated with var2 |
References
No.
Examples
1 | sim <- sim_data(nunber_sample = 1000, number_covariate = 5)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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