s2dv (version 1.3.0)

RandomWalkTest: Random walk test for skill differences

Description

Forecast comparison of the skill obtained with 2 forecasts (with respect to a common reference) based on Random Walks, with significance estimate at the 95 confidence level, as in DelSole and Tippett (2016).

Usage

RandomWalkTest(skill_A, skill_B, time_dim = "sdate", ncores = NULL)

Value

A list of 2:

$score

A numerical array with the same dimensions as the input arrays except 'time_dim'. The number of times that forecaster A has been better than forecaster B minus the number of times that forecaster B has been better than forecaster A (for skill positively oriented). If $score is positive forecaster A is better than forecaster B, and if $score is negative forecaster B is better than forecaster B.

$signif

A logical array with the same dimensions as the input arrays except 'time_dim'. Whether the difference is significant or not at the 5 significance level.

Arguments

skill_A

A numerical array of the time series of the skill with the forecaster A's.

skill_B

A numerical array of the time series of the skill with the forecaster B's. The dimensions should be identical as parameter 'skill_A'.

time_dim

A character string indicating the name of the dimension along which the tests are computed. The default value is 'sdate'.

ncores

An integer indicating the number of cores to use for parallel computation. The default value is NULL.

Examples

fcst_A <- array(c(11:50), dim = c(sdate = 10, lat = 2, lon = 2))
fcst_B <- array(c(21:60), dim = c(sdate = 10, lat = 2, lon = 2))
reference <- array(1:40, dim = c(sdate = 10, lat = 2, lon = 2))
skill_A <- abs(fcst_A - reference)
skill_B <- abs(fcst_B - reference)
RandomWalkTest(skill_A = skill_A, skill_B = skill_B, time_dim = 'sdate', ncores = 1)