# count2prob: Convert Ensemble Counts to Probabilities In easyVerification: Ensemble Forecast Verification for Large Data Sets

 count2prob R Documentation

## Convert Ensemble Counts to Probabilities

### Description

Using plotting positions as described in Wilks (2011), counts of occurrences per forecast category are converted to probabilities of occurrence. For ensembles of size 1 (e.g. verifying observations), the count vector is returned unaltered (corresponding to occurrence probabilities of 0 or 1).

### Usage

count2prob(x, type = 3)


### Arguments

 x input matrix of counts from convert2prob type selection of plotting positions (default to 3, see Types)

### Value

Matrix of probabilities per category

### Types

The types characterize the plotting positions as specified in Wilks (2011). The plotting positions are computed using the following relationship:

p(x_i) = \frac{i + 1 - a}{n + 1 - a}

where i is the number of ensemble members not exceeding x, and n is the number of ensemble members. The types are characterized as follows:

 type description a 1 Weibull 0 2 Bernard and Bos-Levenbach 0.3 3 Tukey 1/3 4 Gumbel 1 5 Hazen 1/2 6 Cunnane 2/5

### References

Wilks, D.S. (2011). Statistical methods in the atmospheric sciences (Third Edition). Academic press.

convert2prob for conversion of continuous forecasts to ensemble counts

### Examples

tm <- toymodel()

## convert to tercile forecasts (only display first forecast and obs)
count2prob(convert2prob(tm$fcst, prob = 1:2 / 3))[1, ] count2prob(convert2prob(tm$obs, prob = 1:2 / 3))[1, ]



easyVerification documentation built on Aug. 15, 2023, 9:06 a.m.