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#'@title Generalized Fluctuation Test (GFT)
#'@description GFT detection method focuses on identifying structural changes <doi:10.18637/jss.v007.i02>.
#'It wraps the breakpoints implementation available in the strucchange library.
#A. Zeileis, C. Kleiber, W. Krämer, and K. Hornik, 2003, Testing and dating of structural changes in practice, Computational Statistics & Data Analysis, v. 44, n. 1 (Oct.), p. 109–123.
#A. Zeileis, F. Leisch, K. Hornik, and C. Kleiber 2002. Strucchange: An R package for testing for structural change in linear regression models.
#'@return `hcp_chow` object
#'@examples
#'library(daltoolbox)
#'
#'#loading the example database
#'data(examples_changepoints)
#'
#'#Using simple example
#'dataset <- examples_changepoints$simple
#'head(dataset)
#'
#'# setting up change point method
#'model <- hcp_gft()
#'
#'# fitting the model
#'model <- fit(model, dataset$serie)
#'
#'# execute the detection method
#'detection <- detect(model, dataset$serie)
#'
#'# filtering detected events
#'print(detection[(detection$event),])
#'
#'@export
hcp_gft <- function() {
obj <- harbinger()
class(obj) <- append("hcp_gft", class(obj))
return(obj)
}
#'@importFrom strucchange Fstats
#'@importFrom strucchange breakpoints
#'@export
detect.hcp_gft <- function(obj, serie, ...) {
if(is.null(serie)) stop("No data was provided for computation", call. = FALSE)
obj <- obj$har_store_refs(obj, serie)
y <- obj$serie
x <- 1:length(y)
breaks <- breakpoints(y ~ x)
cp <- rep(FALSE, length(obj$serie))
n <- length(breaks$breakpoints)
if (n > 0)
cp[breaks$breakpoints] <- TRUE
detection <- obj$har_restore_refs(obj, change_points = cp)
return(detection)
}
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