# False discovery rate estimation for massively parallel restricted likelihood ratio tests

### Description

Given a set of RLRT results and a threshold, this function outputs an estimate of the FDR (in the empirical Bayes sense of Efron, 2010) when the given threshold is used to determine which null hypotheses to reject.

### Usage

1 | ```
Fdr.rlrt(rlrt.obj, threshold)
``` |

### Arguments

`rlrt.obj` |
an RLRT object obtained from |

`threshold` |
threshold at which the null hypothesis is rejected. |

### Value

A list with elements

`MoM` |
FDR based on method of moments estimator of RLRT parameters (Greven et al., 2008). |

`ML` |
FDR based on maximum likelihood estimation of RLRT parameters, as described in Greven et al. (2008). |

### Author(s)

Philip Reiss phil.reiss@nyumc.org

### References

Efron, B. (2010). *Large-Scale Inference: Empirical Bayes
Methods for Estimation, Testing, and Prediction*. New York: Cambridge
University Press.

Greven, S., Crainiceanu, C. M., Kuechenhoff, H., and Peters, A. (2008).
Restricted likelihood ratio testing for zero variance components in linear
mixed models. *Journal of Computational and Graphical Statistics*,
17(4), 870–891.

### See Also

`rlrt.mp`

, `rlrt4d`

### Examples

1 | ```
# See example for rlrt.mp
``` |

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