Nothing
#'@title Anomaly detector using FBIAD
#'@description Anomaly detector using FBIAD
#'@param sw_size Window size for FBIAD
#'@return hanr_fbiad object
#'Forward and Backward Inertial Anomaly Detector (FBIAD) detects anomalies in time series. Anomalies are observations that differ from both forward and backward time series inertia <doi:10.1109/IJCNN55064.2022.9892088>.
#'@examples
#'library(daltoolbox)
#'
#'#loading the example database
#'data(examples_anomalies)
#'
#'#Using simple example
#'dataset <- examples_anomalies$simple
#'head(dataset)
#'
#'# setting up time series regression model
#'model <- hanr_fbiad()
#'
#'# fitting the model
#'model <- fit(model, dataset$serie)
#'
# making detection using hanr_ml
#'detection <- detect(model, dataset$serie)
#'
#'# filtering detected events
#'print(detection[(detection$event),])
#'
#'@export
hanr_fbiad <- function(sw_size = 30) {
obj <- harbinger()
obj$sw_size <- sw_size
class(obj) <- append("hanr_fbiad", class(obj))
return(obj)
}
#'@import daltoolbox
#'@importFrom stats na.omit
#'@export
detect.hanr_fbiad <- function(obj, serie, ...) {
if(is.null(serie)) stop("No data was provided for computation", call. = FALSE)
obj <- obj$har_store_refs(obj, serie)
sx <- daltoolbox::ts_data(obj$serie, obj$sw_size)
ma <- apply(sx, 1, mean)
sxd <- obj$har_residuals(sx[,ncol(sx)] - ma)
iF <- obj$har_outliers_idx(sxd)
iF <- obj$har_outliers_group(iF, length(sxd))
iF <- c(rep(FALSE, obj$sw_size-1), iF)
sx <- ts_data(rev(obj$serie), obj$sw_size)
ma <- apply(sx, 1, mean)
sxd <- obj$har_residuals(sx[,ncol(sx)] - ma)
iB <- obj$har_outliers_idx(sxd)
iB <- obj$har_outliers_group(iB, length(sxd))
iB <- rev(iB)
iB <- c(iB, rep(FALSE, obj$sw_size-1))
anomalies <- iF | iB
detection <- obj$har_restore_refs(obj, anomalies = anomalies)
return(detection)
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.