spikedSteinShrinkEst {cvCovEst} | R Documentation |

## Stein Loss Shrinkage Estimator, Spiked Covariance Model

### Description

`spikedSteinShrinkEst()`

implements the asymptotically
optimal shrinkage estimator with respect to the Stein loss in a spiked
covariance matrix model. Informally, this model admits Gaussian
data-generating processes whose covariance matrix is a scalar multiple of
the identity, save for a few number of large "spikes". A thorough review of
this estimator, or more generally spiked covariance matrix estimation, is
provided in Donoho et al. (2018).

### Usage

```
spikedSteinShrinkEst(dat, p_n_ratio, num_spikes = NULL, noise = NULL)
```

### Arguments

`dat` |
A numeric |

`p_n_ratio` |
A |

`num_spikes` |
A |

`noise` |
A |

### Value

A `matrix`

corresponding to the covariance matrix estimate.

### References

Donoho D, Gavish M, Johnstone I (2018).
“Optimal shrinkage of eigenvalues in the spiked covariance model.”
*The Annals of Statistics*, **46**(4), 1742 – 1778.

### Examples

```
spikedFrobeniusShrinkEst(dat = mtcars, p_n_ratio = 0.1, num_spikes = 2L)
```

*cvCovEst*version 1.2.2 Index]