Description Usage Arguments Value Examples
Fit simple nonparametric regression model with cubic B-splines
1 | resmth.Bspl(Y, X, d, AAt, sigma.hat, plot = FALSE, x = NULL, alpha = 0.05)
|
Y |
a response vector |
X |
vector of covariate observations |
d |
the number functions in the cubic B-spline basis |
a list containing the fitted function and a vector containing the values of the fitted function at the design points
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | data <- data_gen(n = 200, q = 50, r = .9)
spadd.presmth.Bspl.out <- spadd.presmth.Bspl(X = data$X,
Y = data$Y,
d.pre = 20,
lambda = 1,
eta = 3,
n.foi = 6)
resmth.Bspl.out <- resmth.Bspl(Y = data$Y.oracle[,1],
X = data$X[,1],
d = 6,
AAt = spadd.presmth.Bspl.out$AAt[[1]],
sigma.hat = spadd.presmth.Bspl.out$sigma.hat[1],
plot = TRUE)
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