BlockCov (version 0.1.1)

slope_change: This function fits to a numerical vector sorted in the non decreasing order two simple linear regressions and returns the index corresponding to the estimated change between the two regression models.

Description

This function fits to a numerical vector sorted in the non decreasing order two simple linear regressions and returns the index corresponding to the estimated change between the two regression models.

Usage

slope_change(Y)

Arguments

Y

numerical vector sorted in the non decreasing order.

Value

K the index corresponding to the estimated change between the two linear regression models.

Examples

# NOT RUN {
n <- 30
q <- 100
Sigma <- Simu_Sigma(q = q, diag = FALSE, equal = TRUE)
Matrix::image(Sigma)
E <- matrix(rnorm(n * q), ncol = q) %*% chol(as.matrix(Sigma))
corE <- cor(as.matrix(E))
vec_up_emp <- corE[upper.tri(corE)]
G <- matrix(0, ncol = (q - 1), nrow = (q - 1))
G[upper.tri(G, diag = TRUE)] <- vec_up_emp
G[lower.tri(G)] <- t(as.matrix(G))[lower.tri(t(as.matrix(G)))]
res_svd <- svd(G)
vp <- res_svd$d
slope_change(vp)
# }