library(eBsc)
n <- 250
sigma <- 0.05
Basis <- list()
for(i in 1:6) Basis[[i]] <- drbasis(nn = n, qq = i)
coef3 <- c(rep(0,3),(pi*(2:(n-2)))^(-3.1))*(cos(2*(1:n)))
A3 <- Basis[[3]]$eigenvectors
mu <- A3%*%coef3
mu <- (mu-min(mu))/(max(mu)-min(mu))
noise <- rnorm(n)
y <- mu + sigma * noise
#q assumed known and equal to 3, and correlation unknown
fit <- eBsc(y, method = "N", q=3)
#simple plot by
plot(fit, full = FALSE)
Run the code above in your browser using DataLab