Description Usage Arguments Details

Gaussian process (GP) optimization is used to minimize the MSE of the LNC estimator with respect to the non-uniformity threshold parameter `alpha`

. A normal distribution with compound-symmetric covariance is used as a reference distribution to optimize the MSE of LNC with respect to.

1 2 | ```
optimize_mse(rho, N, M, d, k, lower = -10, upper = -1e-10,
num_iter = 10, init_size = 20, cluster = NULL, verbose = TRUE)
``` |

`rho` |
Reference correlation. |

`N` |
Sample size. |

`M` |
Number of replications. |

`d` |
Dimension. |

`k` |
Neighborhood order. |

`lower` |
Lower bound for optimization. |

`upper` |
Upper bound for optimization. |

`num_iter` |
Number of iterations of GP optimization. |

`init_size` |
Number of initial evaluation to estimating GP. |

`cluster` |
A |

`verbose` |
If |

The package `tgp`

is used to fit a treed-GP to the MSE estimates of LNC. A treed-GP is used because the MSE of LNC with respect to `alpha`

exhibits clear non-stationarity. A treed-GP is able to identify the function's different correlation lengths which improves optimization.

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