Description Usage Arguments Details Value See Also Examples
Construct a periodic kernel.
1 |
columns |
a string vector giving the names of features on which the kernel acts. These will be used to access columns from a dataframe when the kernel is later used in a GP model. |
p |
a positive scalar parameter giving the periodicity of the kernel, the difference between values of the covariate at which period signal repeats |
l |
a positive scalar or vector parameter giving the characteristic lengthscale
of the kernel (how rapidly the covariance decays with difference in the
value of the covariate). Larger values of |
sigma |
a positive scalar parameter giving (the square-root of) the overall variance of the kernel |
The periodic kernel takes the form:
k_{per}(\mathbf{x}, \mathbf{x}') = σ^2 exp ≤ft(-\frac{2sin^2(π | \mathbf{x} - \mathbf{x}' | /p)}{l^2} \right)
where \mathbf{x} are the covariates on which the kernel is active, p determines the periodicity (distance between successive peaks), l is a characteristic lengthscale, as in the rbf kernel, and σ^2 is the amplitude of the signal
A kernel object for which there are a range of associated functions, see kernel
and access
for details.
Other kernel.constructors: composition
,
expo
, iid
, int
,
lin
, mat32
,
mat52
, rbf
, rq
1 2 3 4 5 6 7 8 9 |
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