Description Usage Arguments Details Value References
This funcion is deprecated, please use LORD
instead with
version = 'dep'
.
1 2 3 4 5 6 7 8 9 |
d |
Either a vector of p-values, or a dataframe with three columns: an identifier (‘id’), date (‘date’) and p-value (‘pval’). If no column of dates is provided, then the p-values are treated as being ordered sequentially with no batches. |
alpha |
Overall significance level of the FDR procedure, the default is 0.05. |
xi |
Optional vector of ξ_i. A default is provided to satisfy the condition given in Javanmard and Montanari (2018), example 3.7. |
w0 |
Initial ‘wealth’ of the procedure. Defaults to α/10. |
b0 |
The ‘payout’ for rejecting a hypothesis. Defaults to α - w_0. |
random |
Logical. If |
date.format |
Optional string giving the format that is used for dates. |
LORDdep implements the LORD procedure for online FDR control for dependent p-values, where LORD stands for (significance) Levels based On Recent Discovery, as presented by Javanmard and Montanari (2018).
The function takes as its input either a vector of p-values or a dataframe with three columns: an identifier (‘id’), date (‘date’) and p-value (‘pval’). The case where p-values arrive in batches corresponds to multiple instances of the same date. If no column of dates is provided, then the p-values are treated as being ordered sequentially with no batches.
This modified LORD procedure controls FDR for dependent p-values. Given an overall significance level α, we choose a sequence of non-negative numbers ξ_i such that they satisfy a condition given in Javanmard and Montanari (2018), example 3.8.
The procedure depends on constants w_0 and b_0, where w_0 ≥ 0 represents the intial ‘wealth’ and b_0 > 0 represents the ‘payout’ for rejecting a hypothesis. We require w_0+b_0 ≤ α for FDR control to hold.
Further details of the modified LORD procedure can be found in Javanmard and Montanari (2018).
d.out |
A dataframe with the original data |
Javanmard, A. and Montanari, A. (2018) Online Rules for Control of False Discovery Rate and False Discovery Exceedance. Annals of Statistics, 46(2):526-554.
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