sim_tau: Simulated targeting estimation with sparse data.

In tetokawata/simulater: Simulate prediction and estimation performance

Description

sim_tau is used to simulate estimated targeting parameter with sparse linear data given N.

Usage

sim_tau(
  nunber_sample,
  number_covariate,
  number_interation,
  oracle = FALSE,
  LASSO = FALSE,
  RL_forest = FALSE,
  RL = FALSE,
  unpenalty_LASSO = FALSE,
  wrong_simple = FALSE,
  over_parameter = FALSE,
  adaptive_LASSO = FALSE,
  MCP_LASSO = FALSE,
  core = 1
)

Arguments

nunber_sample	number of sample in simulated data.
number_covariate	number of covariates.
core	number of core to use function.

Value

A dataframe containing follows:

est	Out-of-sample MSE.
sample	Sample size in simulation data.
method	Prediction method.

References

No.

Examples

sim <- sim_fix_n(number_sample = 100; number_covariate = 10; core = 1)

tetokawata/simulater documentation built on Dec. 23, 2021, 8:48 a.m.