# Generation of Detailed Fields by Level-dependent Thresholding

### Description

This function generates detailed fields based on level-dependent thresholding of SW coefficients.

### Usage

1 2 | ```
mrsfield.comp.thresh.level(grid, coef, site, netlab, eta, K,
policy, Q, type)
``` |

### Arguments

`grid` |
grid points of extrapolation sites in radian |

`coef` |
coefficients of multi-scale SBF's |

`site` |
grid points of observation sites in radian |

`netlab` |
vector of labels representing sub-networks |

`eta` |
bandwidth parameters for Poisson kernel |

`K` |
the number of resolution levels to be thresholded in the decomposition |

`policy` |
threshold technique. At present the possible policies are ‘"universal"’, ‘"fdr"’ and ‘"Lorentz"’. |

`Q` |
parameter for the false discovery rate of ‘"fdr"’ policy. |

`type` |
the type of thresholding. This can be ‘"hard"’, ‘"soft"’ or ‘"Lorentz"’. |

### Details

This function calculates level-dependent thresholded detailed fields.

### Value

`dfield` |
level-dependent thresholded detailed fields |

### References

Oh, H-S. (1999) Spherical wavelets and their statistical analysis with applications to meteorological data. Ph.D. Thesis, Department of Statistics, Texas A\&M University, College Station.

Oh, H-S. and Li, T-H. (2004) Estimation of global temperature fields from scattered observations by
a spherical-wavelet-based spatially adaptive method. *Journal of the Royal Statistical Society
Ser.* B, **66**, 221–238.

### See Also

`sbf`

, `swd`

, `swthresh`

, `swr`