Man pages for achambaz/tsml.cara.rct
Targeted Sequential Minimum Loss CARA RCT Design and Inference
| addNewSample.TSMLCARA | Adds the Newly Sampled Observations |
| as.character.TSMLCARA | Returns a Description of a TSMLCARA Object |
| getHistory.TSMLCARA | Retrieves the History of a TSMLCARA Object |
| getObs.TSMLCARA | Retrieves the Current Data Set |
| getOptTm | Computes the Optimal Treatment Mechanism Within a Parametric... |
| getOptVar | Computes the Optimal Variance Given a Parametric Model When... |
| getPsiSd.TSMLCARA | Returns the Current Estimated Standard Deviation of the... |
| getPsi.TSMLCARA | Returns the Current Estimator |
| getRegretSd.TSMLCARA | Returns the Current Estimated Standard Deviation of the... |
| getRegret.TSMLCARA | Returns the Current Estimator of the Empirical Regret |
| getSample | Generates Data |
| makeLearnQ | Builds a Parametric Working Model Based on Sample Size |
| makeLearnQ.piecewise | Builds a Parametric Model Based on Sample Size |
| oneOne | Balanced Treatment Mechanism |
| plot.TSMLCARA | Plots a TSMLCARA Object |
| printHistory | Prints a Summary of an History of a TSMLCARA Object |
| Qbar1 | A Conditional Expectation of Y Given (A,W) |
| Qbar2 | A conditional Expectation of Y Given (A,W) |
| ruleQbar | Computes the Treatment Rule Associated with Qbar |
| setConfLevel.TSMLCARA | Sets a Confidence Level |
| targetPsi.TSMLCARA | Targets a TSMLCARA Object Toward the Parameter Psi |
| tsml.cara.rct | Targeted Minimum Loss Covariate-Adjusted Response-Adaptive... |
| update.TSMLCARA | Updates a TSMLCARA Object |
| Vbar1 | A Conditional Variance of Y Given (A,W) |
| Vbar2 | A Conditional Variance of Y Given (A,W) |
