bri.smoothband: Smoothness bands for Gaussian Process Regression

In julianfaraway/brinla: Bayesian Regression with INLA

Smoothness bands for Gaussian Process Regression

Description

Smoothness bands for Gaussian Process Regression

Usage

bri.smoothband(x, y, nbasis = 25, degree = 2, alpha = 2, xout = x,
  sigma0 = sd(y), rho0 = 0.25 * (max(x) - min(x)))

Arguments

x	the predictor vector
y	the response vector
nbasis	- number of basis functions for the spline (default is 25)
degree	- degree for splines (default is 2) - allowable possibilities are 0, 1 or 2.
alpha	- controls shape of the GP kernel (default is 2) - 0 < alpha <=2 is possible
xout	- grid on which posterior will be calculated (default is x)
sigma0	- prior mean for the signal SD (default is SD(y))
rho0	- prior mean for the range

Value

list consisting of xout, the posterior mean, the smoother 95% credibility band, the rougher 95% credibility band

Author(s)

Julian Faraway, [e-mail]

julianfaraway/brinla documentation built on April 6, 2023, 2:33 p.m.