Compute the root mean square error skill score (RMSSS) between an array of
forecast 'exp' and an array of observation 'obs'. The two arrays should
have the same dimensions except along dat_dim, where the length can be
different, with the number of experiments/models (nexp) and the number of
observational datasets (nobs).
RMSSS computes the root mean square error skill score of each jexp in 1:nexp
against each jobs in 1:nobs which gives nexp * nobs RMSSS for each other
grid point of the array.
The RMSSS are computed along the time_dim dimension which should corresponds
to the startdate dimension.
The p-value is optionally provided by an one-sided Fisher test.
RMSSS(
exp,
obs,
time_dim = "sdate",
dat_dim = "dataset",
pval = TRUE,
ncores = NULL
)
A list containing the numeric arrays with dimension:
c(nexp, nobs, all other dimensions of exp except time_dim).
nexp is the number of experiment (i.e., dat_dim in exp), and nobs is the
number of observation (i.e., dat_dim in obs).
The root mean square error skill score.
The p-value. Only present if pval = TRUE
.
A named numeric array of experimental data which contains at least two dimensions for dat_dim and time_dim. It can also be a vector with the same length as 'obs', then the vector will automatically be 'time_dim' and 'dat_dim' will be 1.
A named numeric array of observational data which contains at least two dimensions for dat_dim and time_dim. The dimensions should be the same as paramter 'exp' except the length of 'dat_dim' dimension. The order of dimension can be different. It can also be a vector with the same length as 'exp', then the vector will automatically be 'time_dim' and 'dat_dim' will be 1.
A character string indicating the name of dimension along which the RMSSS are computed. The default value is 'sdate'.
A character string indicating the name of dataset (nobs/nexp) dimension. The default value is 'dataset'.
A logical value indicating whether to compute or not the p-value of the test Ho: RMSSS = 0. If pval = TRUE, the insignificant RMSSS will return NA. The default value is TRUE.
An integer indicating the number of cores to use for parallel computation. The default value is NULL.
set.seed(1)
exp <- array(rnorm(30), dim = c(dataset = 2, time = 3, memb = 5))
set.seed(2)
obs <- array(rnorm(15), dim = c(time = 3, memb = 5, dataset = 1))
res <- RMSSS(exp, obs, time_dim = 'time')
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