accept_rate |
Estimate the local acceptance rate |

add_oth_pvals |
Add Other p-values |

calc_gam_star |
A helper function for 'mv_pn_test', calculating the test statistic for both the vector of parameter estimates, and the draws from the corresponding estimated limiting distribution. |

est_pows |
A helper function to estimate the power using the generated test statistic, and estimated distribution of the test statistic. |

find_mag |
A helper function to find the multiplicative distance of a specified alternative from the alternative in the same direction that obtains a power of 80%. |

gen_boot_sample |
A helper function to generate a multiplier bootstrap sample |

get_test_stat |
Helper function for the Zhang and Laber test. |

ic.data.examp |
Function for calculating the influence function used for the real data example. |

ic.pearson |
Pearson Correlation IC and estimate |

ic.proj.rr |
Estimate both the parameter, and the influence curves used for estimating the projected risk ratio. The first column of your data should correspond to the variable of interest. |

ic.proj.rr.nolas |
Estimate both the parameter, and or the influence curves used for estimating the projected risk ratio (not using lasso). The first column of your data should correspond to the variable of interest. |

look_IC |
This a function used to look at the IC. |

l_p_norm |
A function used to calculate various L_p norms |

mag_for_pow |
This function is used to estimate the magnitude needed for a certain direction to achieve 80% power for a proposed alternative. |

make_data |
Generate data using one of the four specified models from MCKEAGUE and QIAN paper |

mv_pn_test |
Runs a multivariate point null test. This function returns an approximate p-value for the specified test statistic. |

pval_for_mag |
A helper function that calculates the estimated p-value for a given observed alternative and a given norm. |

rr.msm.ic |
Estimate both the parameter, and the influence curves used for estimating the projected risk ratio from a working marginal structural mean model. |

rr.msm.jn.ic |
Estimate both the parameter, and the influence curves used for estimating the projected risk ratio from a working marginal structural mean model. This function only uses elastic net for the estimation (rather than also using other learners). |

test.control |
Control function for the adaptive norm test |

ZL |
Carry out a simplified version of the Zhang and Laber test. |