value {verification}R Documentation

Forecast Value Function

Description

Calculates the economic value of a forecast based on a cost/loss ratio.

Usage

value(obs, pred= NULL, baseline = NULL, cl = seq(0.05, 0.95, 0.05), plot = TRUE, all = FALSE, thresholds = seq(0.05, 0.95, 0.05), ylim = c(-0.05, 1), xlim = c(0,1), ...)

Arguments

obs A vector of binary observations or a contingency table summary of values in the form c(n11, n01, n10, n00) where in nab a = obs, b = forecast.
pred A vector of probabilistic predictions.
baseline Baseline or naive forecast. Typically climatology.
cl Cost loss ratio. The relative value of being unprepared and taking a loss to that of un-necessarily preparing. For example, cl = 0.1 indicates it would cost $ 1 to prevent a $10 loss. This defaults to the sequence 0.05 to 0.95 by 0.05.
plot Should a plot be created? Default is TRUE
all In the case of probabilistic forecasts, should value curves for each thresholds be displayed.
thresholds Thresholds considered for a probabilistic forecast.
ylim, xlim Plotting options.
... Options to be passed into the plotting function.

Value

If assigned to an object, the following values are reported.

vmax Maximum value
V Vector of values for each cl value
F Conditional false alarm rate.
H Conditional hit rate
cl Vector of cost lost ratios.
s Base rate

Author(s)

Matt Pocernich <pocernic@rap.ucar.edu>

References

Jolliffe, Ian and David B. Stephensen (2003) Forecast Verification: A Practioner's Guide in Atmospheric Science, Chapter 8. Wiley

Examples

## value as a contingency table
## Finley tornado data
obs<- c(28, 72, 23, 2680) 
value(obs)
aa <- value(obs)
aa$Vmax # max value

## probabilistic forecast example
 obs  <- round(runif(100) )
 pred <-  runif(100)

value(obs, pred, main = "Sample Plot",
             thresholds = seq(0.02, 0.98, 0.02) ) 
##########
data(pop)
pop.convert()

value(obs = d$obs_rain, pred = d$p24_rain, all = TRUE)

 

[Package verification version 1.29 Index]