linearShrinkEst {cvCovEst} | R Documentation |

## Linear Shrinkage Estimator

### Description

`linearShrinkEst()`

computes the linear shrinkage estimate
of the covariance matrix for a given value of `alpha`

. The linear
shrinkage estimator is defined as the convex combination of the sample
covariance matrix and the identity matrix. The choice of `alpha`

determines the bias-variance tradeoff of the estimators in this class:
values near 1 are more likely to exhibit high variance but low bias, and
values near 0 are more likely to be be very biased but have low variance.

### Usage

```
linearShrinkEst(dat, alpha)
```

### Arguments

`dat` |
A numeric |

`alpha` |
A |

### Value

A `matrix`

corresponding to the estimate of the covariance
matrix.

### Examples

```
linearShrinkEst(dat = mtcars, alpha = 0.1)
```

*cvCovEst*version 1.2.2 Index]