DP.regression {changepoints} R Documentation

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

### Description

Perform dynamic programming algorithm for regression change points localisation.

### Usage

DP.regression(y, X, gamma, lambda, delta, eps = 0.001)


### Arguments

 y A numeric vector of response variable. X A numeric matrix of covariates with vertical axis being time. gamma A positive numeric scalar stands for tuning parameter associated with l_0 penalty. lambda A positive numeric scalar stands for tuning parameter associated with the lasso penalty. delta A positive integer scalar stands for minimum spacing. 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.

### Author(s)

Daren Wang & Haotian Xu

### References

Rinaldo, Wang, Wen, Willett and Yu (2020) <arxiv:2010.10410>

### 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 = DP.regression(y = data$y, X = data$X, gamma = 2, lambda = 1, delta = 5)
cpt_hat = temp\$cpt


[Package changepoints version 1.1.0 Index]