get.ensemble.samples.RdGet parameter values used in ensemble
get.ensemble.samples(ensemble.size, pft.samples, env.samples, method = "uniform", param.names = NULL, ...)
| ensemble.size | number of runs in model ensemble |
|---|---|
| pft.samples | random samples from parameter distribution, e.g. from a MCMC chain |
| env.samples | env samples |
| method | the method used to generate the ensemble samples. Random generators: uniform, uniform with latin hypercube permutation. Quasi-random generators: halton, sobol, torus. Random generation draws random variates whereas quasi-random generation is deterministic but well equidistributed. Default is uniform. For small ensemble size with relatively large parameter number (e.g ensemble size < 5 and # of traits > 5) use methods other than halton. |
| param.names | a list of parameter names that were fitted either by MA or PDA, important argument, if NULL parameters will be resampled independently |
| ... | Other arguments passed on to the sampling method |
matrix of (quasi-)random samples from trait distributions
Returns a matrix of randomly or quasi-randomly sampled trait values to be assigned to traits over several model runs. given the number of model runs and a list of sample distributions for traits The model run is indexed first by model run, then by trait