fdrseg: Piecewise constant regression with FDRSeg

In FDRSeg: FDR-Control in Multiscale Change-Point Segmentation

Description

Compute the FDRSeg estimator for one-dimensional data with i.i.d. Gaussian noises.

Usage

fdrseg(Y, q, alpha = 0.1, r = round(50/min(alpha, 1-alpha)), sd = stepR::sdrobnorm(Y))

Arguments

Y	a numeric vector containing the noisy data
q	threshold value; a numeric vector of the same length as the data
alpha	significance level; if q is missing, q is chosen as the (1-alpha)-quantile of the null distribution of the multiscale statistic via Monte Carlo simulation, see (Li et al., 2015) for an explanation
r	numer of Monte Carlo simulations
sd	standard deviation of noises

Value

A list with components

value	function values on each segment of the estimator
left	indices of leftmost points within each segment of the estimator
n	number of samples

References

Li, H., Munk, A., and Sieling, H. (2015). FDR-control in multiscale change-point segmentation. arXiv:1412.5844.

See Also

smuce, dfdrseg, simulQuantile, sdrobnorm, evalStepFun, computeFdp, v_measure

Examples

# simulate data
set.seed(123)
u0 <- c(rep(1, 50), rep(5, 50))
Y  <- rnorm(100, u0)

# compute the estimate (q is automatically simulated)
# it might take a while due to simulating quantiles and will
# be faster for later calls on signals of the same length
uh <- fdrseg(Y)

# plot result
plot(Y, pch = 20, col = "grey", ylab = "", main = expression(alpha*" = 0.1"))
lines(u0, type = "s", col = "blue")
lines(evalStepFun(uh), type = "s", col = "red")
legend("topleft", c("Truth", "FDRSeg"), lty = c(1, 1), col = c("blue", "red"))


# other choice of alpha
uh <- fdrseg(Y, alpha = 0.05)
# plot result
plot(Y, pch = 20, col = "grey", ylab = "", main = expression(alpha*" = 0.05"))
lines(u0, type = "s", col = "blue")
lines(evalStepFun(uh), type = "s", col = "red")
legend("topleft", c("Truth", "FDRSeg"), lty = c(1, 1), col = c("blue", "red"))

## Not run: 
# alternatively simulate quantiles first
alpha <- 0.1
q     <- simulQuantile(1 - alpha, 100, type = "fdrseg")

# then compute the estimate
uh <- fdrseg(Y, q)
## End(Not run)

FDRSeg documentation built on May 2, 2019, 9:43 a.m.