# Field Significance Method of Elmore et al. (2006)

### Description

Apply field significance method of Elmore et al. (2006).

### Usage

1 2 3 4 5 6 7 8 |

### Arguments

`X,Y` |
m by n matrices giving the verification and forecast fields, resp., for each of m time points (rows) and n locations (columns). |

`x,object` |
list object as returned by |

`loc` |
optional (for subsequent plotting) n by 2 matrix giving the lon/lat coordinates for the locations. |

`block.length` |
numeric giving the block length to be used n the block bootstrap algorithm. If NULL, floor(sqrt(n)) is used. |

`alpha.boot` |
numeric between 0 and 1 giving the confidence level desired for the bootstrap algorithm. |

`field.sig` |
numeric between 0 and 1 giving the desired field significance level. |

`bootR` |
numeric integer giving the number of bootstrap replications to use. |

`ntrials` |
numeric integer giving the number of Monte Carol iterations to use. |

`verbose` |
logical, should progress information be printed to the screen? |

`...` |
not used. |

### Details

See Elmore et al. (2006) for details.

### Value

A list object with components:

`data.name` |
character vector giving the name of the verification and forecast spatio-temporal fields used, and the associated location object (if not NULL). |

`block.boot.results ` |
object of class LocSig |

`sig.results` |
list object containing information about the significance of the results. |

`field.significance,alpha.boot` |
field significance level and bootstrap CI level as input by field.sig alpha.boot arguments. |

`bootR,ntrials` |
same as arguments above. |

### Author(s)

Eric Gilleland and Kimberly L. Elmore

### References

Elmore, K. L., Baldwin, M. E. and Schultz, D. M. (2006) Field significance revisited: Spatial bias errors in forecasts as applied to the Eta model. *Mon. Wea. Rev.*, **134**, 519–531.

### See Also

`MCdof`

, `LocSig`

, `tsboot`

### Examples

1 2 3 4 5 6 7 8 9 10 | ```
data(GFSNAMfcstEx)
data(GFSNAMobsEx)
data(GFSNAMlocEx)
id <- GFSNAMlocEx[,"Lon"] >=-95 & GFSNAMlocEx[,"Lon"] <= -75 & GFSNAMlocEx[,"Lat"] <= 32
loc <- GFSNAMlocEx[id,]
GFSobsSub <- GFSNAMobsEx[,id]
GFSfcstSub <- GFSNAMfcstEx[,id]
look <- spatbiasFS(GFSobsSub, GFSfcstSub, loc=loc, bootR=500, ntrials=500)
plot(look)
summary(look)
``` |