BstrapTest {BinSegBstrap} | R Documentation |
Tests whether the underlying signal is smooth or contains at least one change-point. The smooth alternative is estimated by a (crossvalidated) kernel smoother. The single change-point alternative is estimated by estimateSingleCp
. Its estimated jump size is used as a test statistic and the critical value is obtained by bootstrapping. More details can be found in the vignette.
BstrapTest(y, bandwidth, nbandwidth = 30L, B = 500L, alpha = 0.05, kernel = c("epanechnikov", "gaussian", "rectangular", "triangular", "biweight", "silverman"))
y |
a numeric vector containing the data points |
bandwidth |
the bandwidth, i.e. a numeric with values between |
nbandwidth |
a single integer giving the number of bandwidths (see above) if |
B |
a single integer giving the number of bootstrap samples |
alpha |
a probability, i.e. a single numeric between 0 and 1, giving the significance level of the test |
kernel |
the kernel function, i.e. either a string or a function that takes a single numeric vector and returns the values of the kernel at those locations |
a list
with the following components:
- piecewiseSignal: the estimated signal with a single change-point
- cp: the estimated change-point location
- size: the estimated jump size
- bandwidth: the selected bandwidth for the piecewise signal
- bandwidthSmooth: the selected bandwidth for the smooth signal
- smoothSignal: the estimated smooth signal
- critVal: the by bootstrapping obtained critical value
- pValue: the p-Value of the test
- outcome: a boolean saying whether the test rejects the hypothesis of a smooth signal
n <- 100 signal <- sin(2 * pi * 1:n / n) signal[51:100] <- signal[51:100] + 5 y <- rnorm(n) + signal # default bandwidth and kernel test <- BstrapTest(y = y) if (test$outcome) { # null hypothesis of a smooth signal is rejected estimatedSignal <- test$piecewiseSignal } else { # null hypothesis of a smooth signal is accepted estimatedSignal <- test$smoothSignal } plot(y) lines(signal) lines(estimatedSignal, col = "red") # fixed bandwidth test <- BstrapTest(y = y, bandwidth = 0.1) # user specified kernel kernel <- function(x) 1 - abs(x) # triangular kernel test <- BstrapTest(y = y, kernel = kernel)