Description Usage Arguments Value
a simple GPR posterior distribution, no parameter learning
1 | gpr_posterior(x, y, x.targets, noise, kernelfunc, derivatives = FALSE)
|
x |
obs timepoints |
y |
obs values |
x.targets |
target timepoints |
noise |
noise std, a single value or a vector |
kernelfunc |
a kernel function of (x1,x2) (returns a matrix) |
derivatives |
compute also derivatives |
a gpsimple
-object with fields
x |
timepoints |
mean |
GP mean |
cov |
covariance matrix |
noisestd |
vector of noise std's |
mll |
marginal log likelihood |
x.obs |
original observation times |
y.obs |
original observation values |
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