Description Usage Arguments Value See Also
Takes pregenerated simulated GP models as input, and
models both the perturbation and additional perturbation variance as
GP models, that are all combined into a perturbed GP model. We sample
reps
data points from this at timepoints obs
1 2 3 4 | simulategp.perturbed(N = 100, reps = 3, obs = c(0, 5, 10, 15, 20),
gps.ctrl = NULL, filename = NULL, xs = seq(0, 20, 0.2), l.noise = 12,
l.shape = 2, l.scale = 2.5, sigmaf.noise = 0.25, sigmaf.shape = 4,
sigmaf.scale = 0.5)
|
N |
number of gp's |
reps |
replicate observations |
obs |
observation timepoints |
gps.ctrl |
the GPS models to be perturbed |
filename |
file to save the results |
xs |
target timepoints |
l.noise |
Noise model lengthscale |
l.shape |
shape of lengthscale Gamma distribution |
l.scale |
scale of lengthscale Gamma distribution |
sigmaf.noise |
Noise model sigma.f |
sigmaf.shape |
shape of sigma.f Gamma distribution |
sigmaf.scale |
scale of sigma.f Gamma distribution |
List with
simdata |
Simulated datamatrix |
gps |
Simulated GPs |
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