Bias Adjustment/Calibration of multiple datasets

@vtorralba has detected a need for calibration (and bias adjustment) of multiple datasets.

She expected that the following code worked:

library(CSTools)
mod1 <- 1 : (2 * 3 * 4 * 5 * 6 * 7)
dim(mod1) <- c(dataset = 2, member = 3, sdate = 4, ftime = 5, lat = 6, lon = 7)
obs1 <- 1 : (1 * 1 * 4 * 5 * 6 * 7)
dim(obs1) <- c(dataset = 1, member = 1, sdate = 4, ftime = 5, lat = 6, lon = 7)
lon <- seq(0, 30, 5)
lat <- seq(0, 25, 5)
exp <- list(data = mod1, lat = lat, lon = lon)
obs <- list(data = obs1, lat = lat, lon = lon)
attr(exp, 'class') <- 's2dv_cube'
attr(obs, 'class') <- 's2dv_cube'
a <- Calibration(exp = exp$data, obs = obs$data,
                 cal.method = "mse_min", eval.method = "in-sample",multi.model = T)

I think CST_Calibration and CST_BiasCorrection need to be enhanced to allow this option. Probably, they can follow the s2dv options to declare dat_dim.

What do you think?

Cheers,

Núria