bwd {bwd} | R Documentation |
Implements backward procedure for detecting single or multiple change points.
bwd(y, alpha = 0.05, kmin = 3, lastkgroup = floor(0.01 * n),
mu0 = NULL, normal = T, n.permute = 1000, h = 10)
y |
observed data |
alpha |
target level that detemines stopping criterion. Default is 0.05 |
kmin |
minimum length of segements for checking possible change points |
lastkgroup |
We can abvoid chekcing possible change points when we have less groups than "lastkgroup" to improve computational efficiency. Default is 0.01 * n |
mu0 |
Baseline mean value whe detecting epidemic chang points. Defalut is |
normal |
if |
n.permute |
number of permutation when computing the permuted cutoff. Defalut is 1000 |
h |
bandwidth size for variance esitimator |
bwd object that contains information of detected segments and significance levels
Seung Jun Shin, Yicaho Wu, Ning Hao
Shin, Wu, and Hao (2018+) A backward procedure for change-point detection with applications to copy number variation detection, arXiv:1812.10107.
# simulated data
set.seed(1)
n <- 1000
L <- 10
mu0 <- -0.5
mu <- rep(mu0, n)
mu[(n/2 + 1):(n/2 + L)] <- mu0 + 1.6
mu[(n/4 + 1):(n/4 + L)] <- mu0 - 1.6
y <- mu + rnorm(n)
alpha <- c(0.01, 0.05)
# BWD
obj1 <- bwd(y, alpha = alpha)
# Modified for epidemic changes with a known basline mean, mu0.
obj2 <- bwd(y, alpha = alpha, mu0 = 0)
par(mfrow = c(2,1))
plot(obj1, y)
plot(obj2, y)