DPDU.regression {changepoints} R Documentation

## Dynamic programming with dynamic update algorithm for regression change points localisation with l_0 penalisation.

### Description

Perform DPDU algorithm for regression change points localisation.

### Usage

DPDU.regression(y, X, lambda, zeta, eps = 0.001)


### Arguments

 y A numeric vector of response variable. X A numeric matrix of covariates with vertical axis being time. lambda A positive numeric scalar of tuning parameter for lasso penalty. zeta A positive integer scalar of tuning parameter associated with l_0 penalty (minimum interval size). eps A numeric scalar of precision level for convergence of lasso.

### Value

An object of class "DP", which is a list with the following structure:

 partition A vector of the best partition. cpt A vector of change points estimation.

Haotian Xu

### References

Xu, Wang, Zhao and Yu (2022) <arXiv:2207.12453>.

### Examples

d0 = 10
p = 20
n = 100
cpt_true = c(30, 70)
data = simu.change.regression(d0, cpt_true, p, n, sigma = 1, kappa = 9)
temp = DPDU.regression(y = data$y, X = data$X, lambda = 1, zeta = 20)
cpt_hat = temp\$cpt


[Package changepoints version 1.1.0 Index]