| application.covariates | Simulation of applying different dimensions of covariates |
| application.lasso | Simulation of using lasso for linear and nonlinear structure... |
| application.samples | Simulation of applying different number of samples |
| application.sd | Simulation of using different standard errors in treatment... |
| bias.evaluation | Bias Evaluation |
| bias.evaluation.wrap | Bias Evaluation Wrap-up |
| covariates.generation | Generation of the covariates dataset |
| data.generation | Data Generation |
| data.generation.wrap | Data Generation wrap-up (short-cut name: dg.w) |
| error1.evaluation | l^1 error evaluation |
| error2.evaluation | l^2 error evaluation |
| error.evaluation.wrap | Error Evaluation Wrap-up |
| g.method.estimation | Regression Method Estimation |
| g.predict | Regression Method Prediction |
| gps.method.estimation | Generalized Propensity Score Estimation |
| gps.predict | Generalize Propensity Score Prediction |
| instrument.generation | Generation of instrument variable dataset |
| noise.generation | Generation of noise dataset |
| plot.alternative.inside | Plot of Alternatives |
| response.generation | Generation of response dataset |
| running.simulation | Running Simulation |
| simulation | Simulation Body Part |
| simulation.alternative | The alternative of running simulation |
| simulation.wrap | Simulation wrap-up (short-cut name: sim.w) |
| treatment.generation | Generation of treatment dataset |
| true.data.generation | True Data Generation |
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