sweq_eval: Compute diagnostics of SWEQ cycling experiment

In robertsy/assimilr: Local Ensemble Kalman Particle Filters

Description

compute error measures (bias, mse, rmse, crps) per time and per ensemble type (analysis, forecast)

Usage

sweq_eval(sweq_run, model_run)

Arguments

sweq_run	reference run as returned from l**_simulate
model_run	as returned from a cycling experiment

Value

tbl object with bias, mse, rmse, nobs, crps for background/analysis ensembles

Examples

set.seed(1)
sweq_run <- sweq_simulate(5*60, 60, 300)
k <- 20
ens0 <- sweq_ens0(k, sweq_run, klag=1000)
l <- 5
block_run <- da_cycle(ens0, sweq_run, block_LEnKPF, l=l, block_size=l/2, 
                      taper=sweq_GC(sweq_run$ndim, l, 0.9), ndim=sweq_run$ndim,
                      get_partition = sweq_partition,
                      manifold_proj = sweq_proj)
block_df <- sweq_eval(sweq_run, block_run)

robertsy/assimilr documentation built on May 27, 2019, 10:33 a.m.