multi.cont {verification} | R Documentation

## Multiple Contingency Table Statistics

### Description

Provides a variety of statistics for a data summarized in a contingency table. This will work for a 2 by 2 table, but is more useful for tables of greater dimensions.

### Usage

    multi.cont(DAT)

### Arguments

`DAT` | A contingency table in the form of a matrix. It is assumed that columns represent observation, rows represent forecasts.

### Value

`pc` | Percent correct - events along the diagonal.
`bias` | Bias
`pod` | Probability of detecting an event.
`far` | False Alarm Ratio
`ts` | Threat score a.k.a. Critical success index (CSI)
`hss` | Heidke Skill Score
`pss` | Peirce Skill Score
`gs` | Gerrity Score

### Author(s)

Matt Pocernich <pocernic@rap.ucar.edu>

### References

Gerrity, J.P. Jr (1992). A note on Gandin and Murphy's equitable skill score. Mon. Weather Rev., 120, 2707-2712.

Jolliffe, I.T. and D.B. Stephenson (2003). Forecast verification: a practitioner's guide in atmospheric science. John Wiley and Sons. See chapter 4 concerning categorical events, written by R. E. Livezey.

### Examples

    DAT<- matrix(c(7,4,4,14,9,8,14,16,24), nrow = 3) # from p. 80 - Jolliffe
    multi.cont(DAT)

    DAT<- matrix(c(3,8,7,8,13,14,4,18,25), ncol = 3) ## Jolliffe JJA
    multi.cont(DAT)

    DAT<- matrix(c(50,47,54,91,2364,205,71,170,3288), ncol = 3) # Wilks p. 245
    multi.cont(DAT)

    DAT<- matrix(c(28, 23, 72, 2680 ), ncol = 2) ## Finley
    multi.cont(DAT)
    ## Finnish clouds
    DAT<- matrix(c(65, 10, 21, 29,17,48, 18, 10, 128), nrow = 3, ncol = 3, byrow = TRUE)
    multi.cont(DAT)

[Package verification version 1.20 Index]