attribute {verification}R Documentation

Attribute plot

Description

An attribute plot illustrates the reliability, resolution and uncertainty of a forecast with respect to the observation. The frequency of binned forecast probabilities are plotted against proportions of binned observations. A perfect forecast would be indicated by a line plotted along the 1:1 line. Uncertainty is described as the vertical distance between this point and the 1:1 line. The relative frequency for each forecast value is displayed in parenthesis.

Usage

## Default S3 method:
attribute(x, obar.i,  prob.y = NULL, obar = NULL, class =
"none", main = NULL, CI = FALSE, n.boot = 100, alpha = 0.05, tck = 0.01, ...)
## S3 method for class 'prob.bin':
attribute(x, ...)
       

Arguments

x A vector of forecast probabilities or a ``prob.bin'' class object produced by the verify function.
obar.i A vector of observed relative frequency of forecast bins.
prob.y Relative frequency of forecasts of forecast bins.
obar Climatological or sample mean of observed events.
class Class of object. If prob.bin, the function will use the data to estimate confidence intervals.
main Plot title.
CI Confidence Intervals. This is only an option if the data is accessible by using the verify command first. Calculated by bootstrapping the observations and prediction, then calculating PODy and PODn values.
n.boot Number of bootstrap samples.
alpha Confidence interval. By default = 0.05
tck Tick width on confidence interval whiskers.
... Graphical parameters

Author(s)

Matt Pocernich <pocernic@rap.ucar.edu>

References

Hsu, W. R., and A.H. Murphy, 1986: The attributes diagram: A geometrical framework for assessing the quality of probability forecasts. Int. J. Forecasting 2, 285-293.

Wilks, D. S. (1995) Statistical Methods in the Atmospheric Sciences Chapter 7, San Diego: Academic Press.

See Also

verify

Examples

## Data from Wilks, table 7.3 page 246.
 y.i   <- c(0,0.05, seq(0.1, 1, 0.1))
 obar.i <- c(0.006, 0.019, 0.059, 0.15, 0.277, 0.377, 0.511, 
             0.587, 0.723, 0.779, 0.934, 0.933)
 prob.y<- c(0.4112, 0.0671, 0.1833, 0.0986, 0.0616, 0.0366,
            0.0303,  0.0275, 0.245, 0.022, 0.017, 0.203) 
 obar<- 0.162
 
attribute(y.i, obar.i, prob.y, obar, main = "Sample Attribute Plot")  

## Function will work with a ``prob.bin'' class objects as well.
## Note this is a random forecast.
obs<- round(runif(100))
pred<- runif(100)

A<- verify(obs, pred, frcst.type = "prob", obs.type = "binary")
attribute(A, main = "Alternative plot", xlab = "Alternate x label" )
## Same with confidence intervals

attribute(A, main = "Alternative plot", xlab = "Alternate x label", CI =
TRUE)

[Package verification version 1.12 Index]