# Optimal bandwidth for the maximum kernel likelihood estimator

### Description

Estimates the optimal bandwidth for the maximum kernel likelihood estimator using a Gaussian kernel for a given dataset using the bootstrap.

### Usage

1 |

### Arguments

`data` |
the data for which the optimal bandwidth should be found. |

`bws` |
a vector with the upper and lower bound for the bandwidth. |

`B` |
number of resamples used to estimate the mean squared error with 1000 as the default. |

`gridsize` |
the number of points at which the kernel density estimator is to be evaluated with |

### Details

The bandwidth considered fall between one and 4 standard deviations. In addition the mse of the `mkle`

for a bandwidth of zero will also be included.

The estimation of the optimal bandwidth might take several minutes depending on the number of bootstrap resamples and the gridsize used.

### Value

The estimated optimal bandwidth.

### Note

The `optimize`

is used for the optimization.

### Author(s)

Thomas Jaki

### References

Jaki T., West R. W. (2008) Maximum kernel likelihood estimation. Submitted to *Journal of Computational and Graphical Statistics* Vol. 17(No 4), 976-993.

Davison, A. C. and Hinkley, D. V. (1997), Bootstrap Methods and their Applications, Cambridge Series in Statistical and Probabilistic Mathematics, Cambridge University Press.

### See Also

`mkle`

### Examples

1 2 |