elastic_amp_change_ff {fdasrvf} | R Documentation |
Elastic Amplitude Changepoint Detection
Description
This function identifies a amplitude changepoint using a fully functional approach
Usage
elastic_amp_change_ff(
f,
time,
d = 1000,
h = 0,
smooth_data = FALSE,
sparam = 25,
showplot = TRUE
)
Arguments
f |
matrix ( |
time |
vector of size |
d |
number of monte carlo iterations of Brownian Bridge (default = 1000) |
h |
window selection of long range covariance function (default = 0) |
smooth_data |
smooth data using box filter (default = F) |
sparam |
number of times to apply box filter (default = 25) |
showplot |
show results plots (default = T) |
Value
Returns a list object containing
pvalue |
p value |
change |
indice of changepoint |
DataBefore |
functions before changepoint |
DataAfter |
functions after changepoint |
MeanBefore |
mean function before changepoint |
MeanAfter |
mean function after changepoint |
WarpingBefore |
warping functions before changepoint |
WarpingAfter |
warping functions after changepoint |
WarpingMeanBefore |
mean warping function before changepoint |
WarpingMeanAfter |
mean warping function after changepoint |
change_fun |
amplitude change function |
Sn |
test statistic values |
mu |
mean srsfs |
mu_f |
mean functions |
References
J. D. Tucker and D. Yarger, “Elastic Functional Changepoint Detection of Climate Impacts from Localized Sources”, Envirometrics, 10.1002/env.2826, 2023.