In a particular empirical process setting, estimates the
bandwidth parameter controlling the serial dependence when
generating dependent multiplier sequences using the 'moving average
approach'; see Section 5 of the third reference. This
function is called in the functions `cpTestFn()`

and
`cpTestCn()`

if `b`

is set to `NULL`

.

1 2 | ```
bOptEmpProc(x, m=5, weights = c("parzen", "bartlett"),
L.method=c("max","median","mean","min"))
``` |

`x` |
a data matrix whose rows are continuous observations. |

`weights` |
a string specifying the kernel for creating the weights used in the generation of dependent multiplier sequences within the 'moving average approach'; see Section 5 of the third reference. |

`m` |
a strictly positive integer specifying the number of points of the
uniform grid on |

`L.method` |
a string specifying how the parameter |

The implemented approach results from an adaptation of the procedure described in the first two references (see also the references therein). The use of this function in a context different from that considered in the third reference may not be meaningful.

Acknowledgment: Part of the code of the function results from an adaptation of R code of C. Parmeter and J. Racine, itself an adaptation of Matlab code by A. Patton.

A strictly positive integer.

D.N. Politis and H. White (2004), Automatic block-length selection for the
dependent bootstrap, *Econometric Reviews* 23(1):53–70.

D.N. Politis, H. White and A.J. Patton (2004), Correction: Automatic
block-length selection for the dependent bootstrap,
*Econometric Reviews* 28(4):372-375.

A. Bücher and I. Kojadinovic (2014), A dependent multiplier
bootstrap for the sequential empirical copula process under strong
mixing, *Bernoulli*, in press, http://arxiv.org/abs/1306.3930.

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