measurement.error: Skill score with measurement error.

Description Usage Arguments Value Author(s) References Examples

Description

Skill score that incorporates measurement error. This function allows the user to incorporate measurement error in an observation in a skill score.

Usage

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measurement.error( obs, frcs = NULL, theta = 0.5, CI =
          FALSE, t = 1, u = 0, h = NULL, ...)
       

Arguments

obs

Information about a forecast and observation can be done in one of two ways. First, the results of a contingency table can be entered as a vector containing c(n11, n10, n01, n00), where n11 are the number of correctly predicted events and n01 is the number of incorrectly predicted non-events. Actual forecasts and observations can be used. In this case, obs is a vector of binary outcomes [0,1].

frcs

If obs is entered as a contingency table, this argument is null. If obs is a vector of outcomes, this column is a vector of probabilistic forecasts.

theta

Loss value (cost) of making a incorrect forecast by a non-event. Defaults to 0.5.

CI

Calculate confidence intervals for skill score.

t

Probability of forecasting an event, when an event occurs. A perfect value is 1.

u

Probability of forecasting that no event will occur, when and event occurs. A perfect value is 0.

h

Threshold for converting a probabilistic forecast into a binary forecast. By default, this value is NULL and the theta is used as this threshold.

...

Optional arguments.

Value

z

Error code

k

Skill score

G

Likelihood ratio statistic

p

p-value for the null hypothesis that the forecast contains skill.

theta

Loss value. Loss associated with an incorrect forecast of a non-event.

ciLO

Lower confidence interval

ciHI

Upper confidence interval

Author(s)

Matt Pocernich (R - code)

W.M Briggs <wib2004(at)med.cornell.edu> (Method questions)

References

W.M. Briggs, 2004. Incorporating Cost in the Skill Score Technical Report, wm-briggs.com/public/skillocst.pdf.

W.M. Briggs and D. Ruppert, 2004. Assessing the skill of yes/no forecasts. Submitting to Biometrics.

J.P. Finley, 1884. Tornado forecasts. Amer. Meteor. J. 85-88. (Tornado data used in example.)

Examples

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DAT<- data.frame( obs = round(runif(50)), frcs = runif(50))

A<-   measurement.error(DAT$obs, DAT$frcs, CI = TRUE)
A
### Finley Data

measurement.error(c(28, 23, 72, 2680)) ## assuming perfect observation,
                                       
     

verification documentation built on May 2, 2019, 1:24 a.m.