fastmath.interpolation.gp — generateme/fastmath 3.0.0-alpha2

Gaussian Processes

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gaussian-process clj

(gaussian-process xss ys)

(gaussian-process xss
                  ys
                  {:keys [kscale kernel noise normalize? L?]
                   :or {kscale 1.0 normalize? false noise 1.0E-8 L? true}})

Return Gaussian Process object, use predict

gp clj

(gp xss ys)

(gp xss ys kernel)

(gp xss ys kernel opts)

Gaussian process interpolator.

L clj

(L gp-object)

(L ys w chol n)

posterior-samples clj

(posterior-samples gp-object xvals)

(posterior-samples gp-object xvals stddev?)

predict clj

(predict gp-object xval)

(predict gp-object xval stddev?)

predict-all clj

(predict-all gp-object xvals)

(predict-all gp-object xvals stddev?)

prior-samples clj

(prior-samples gp-object xvals)