Description Usage Arguments Value

A function used to estimate the reduced dimension regressions for Q. The regression
can be computed using a user specified function, passed through `SL.Qr`

or using
`SuperLearner`

when `length(SL.Qr) == 1`

or `is.list(SL.Qr)`

. There is
an error proofing of the `SuperLearner`

implementation that deals with situations where
the `NNLS`

procedure in the Super Learner ensemble fails and so the function returns
zero weights for every coefficient. In this case, the code will default to using the discrete
Super Learner; that is, the learner with lowest CV-risk.

1 2 | ```
estimateQr(rQ1_1, rQ1_2, rQ2, g0n, g1n, A0, A1, SL.Qr, folds, validFold, abar,
return.models, verbose, ...)
``` |

`rQ1_1` |
The "residual" for the first of two reduced-dimension regressions (on g0n). |

`rQ1_2` |
The "residual" for the second of two reduced-dimension regressions (on g0n). |

`rQ2` |
The "residual" for the second reduced dimension regression (on g1n), equal to the EIF at time 2. |

`g0n` |
A |

`g1n` |
A |

`A0` |
A |

`A1` |
A |

`SL.Qr` |
A |

`folds` |
Vector of cross-validation folds |

`validFold` |
Which fold is the validation fold |

`abar` |
A |

`return.models` |
A |

`verbose` |
A |

A list with elements Q2nr.obsa, Q2rn.seta, Q1nr, Q2mod, and Q1mod. Q2nr.obsa corresponds to the predicted value of the reduced dimension regression where A0 is its observed value, while Q2nr.seta is the reduced dimension regression where A0 is set to abar[1].

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