verification (version 1.09)

multi.cont: 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 Rate
• ts
  Threat score a.k.a. Critical success index (CSI)
• hss
  Heidke Skill Score
• pss
  Pierce Skill Score
• gs
  Gerrity Score

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)