DTWUMI_1gap_imputation: Imputation of a large gap based on DTW for multivariate...

In DTWUMI: Imputation of Multivariate Time Series Based on Dynamic Time Warping

Description

Fills a gap of size 'gap_size' begining at the position 'begin_gap' within a multivariate signal using DTW.

Usage

DTWUMI_1gap_imputation(data, id_sequence, begin_gap, gap_size,
  DTW_method = "DTW", threshold_cos = 0.995, thresh_cos_stop = 0.8,
  step_threshold = 2, ...)

Arguments

data	a multivariate signals containing gaps
id_sequence	id of the sequence containing the gap to fill (corresponding to the column number)
begin_gap	id of the begining of the gap to fill
gap_size	size of the gap to fill
DTW_method	DTW method used for imputation ("DTW", "DDTW", "AFBDTW"). By default "DTW"
threshold_cos	threshold used to define similar sequences to the query
thresh_cos_stop	Define the lowest cosine threshold acceptable to find a similar window to the query
step_threshold	step used within the loops determining the threshold and the most similar sequence to the query
...	additional arguments from dtw() function

Value

returns a list containing the following elements:

• imputed_values: output vector containing the imputation proposal

• id_imputation: a vector containing the position of the imputed values extracted

• id_sim_win: a vector containing the position of the similar window to the query

• id_gap: a vector containing the position gap considered

• id_query: a vector containing the position of the query

Author(s)

DEZECACHE Camille, PHAN Thi Thu Hong, POISSON-CAILLAULT Emilie

Examples

data(dataDTWUMI)
dataDTWUMI_gap <- dataDTWUMI[["incomplete_signal"]]
t <- 207 ; T <- 40
imputation <- DTWUMI_1gap_imputation(dataDTWUMI_gap, id_sequence=1, t, T)
plot(dataDTWUMI_gap[, 1], type = "l", lwd = 2)
lines(y = imputation$imputed_values, x = imputation$id_gap, col = "red")
lines(y = dataDTWUMI_gap[imputation$id_query, 1], x = imputation$id_query, col = "green")
lines(y = dataDTWUMI_gap[imputation$id_sim_win, 1], x = imputation$id_sim_win, col = "blue")
lines(y = dataDTWUMI_gap[imputation$id_imputation, 1], x = imputation$id_imputation, col = "orange")

DTWUMI documentation built on May 1, 2019, 10:26 p.m.