SpecsVerification (version 0.4-0)

PlotRankhist: Plotting function for rank histograms

Description

Plots a rank histogram in different modes.

Usage

PlotRankhist(rank.hist, mode="raw")

Arguments

rank.hist

A vector or rank counts.

mode

string. One of "raw" (default) or "prob.paper". Whether to draw the raw rank histogram, or the rank histogram on probability paper. See Details.

Value

• none

Details

The plotting modes currently implemented are:

"raw" (default): A simple bar plot of the counts provided by the `rank.hist` argument.

"prob.paper": The individual counts given by `rank.hist` are transformed to their cumulative probabilities under the binomial distribution with parameters `N` and `1/K`, where `N=sum(rank.hist)` and `K=length(rank.hist)`. This transformation makes possible an assessment of the observed rank counts under the hypothesis of equally likely ranks. The y-axis on the left indicates the cumulative probabilities. The intervals on the right of the plot indicate central 90, 95, and 99 percent _simultaneous_ confidence intervals. That is, if all ranks were equally likely on average, approximately 90 percent of all rank histograms would be _completely_ contained in the 90 percent interval and approximately 10 percent of all rank histograms would have _at least_ one bar that falls outside this interval.

References

Anderson J.L. (1996). A Method for Producing and Evaluating Probabilistic Forecasts from Ensemble Model Integrations. J. Climate, 9, 1518--1530. DOI 10.1175/1520-0442(1996)009 Broecker J. (2008). On reliability analysis of multi-categorical forecasts. Nonlin. Processes Geophys., 15, 661-673, DOI 10.5194/npg-15-661-2008.

Examples

# Example:
  ens <- matrix(rnorm(500),100,5)
  obs <- rnorm(100)
  rank.hist <- Rankhist(ens, obs)
  PlotRankhist(rank.hist, mode="prob.paper")