tidychangepoint (version 1.0.0)

segment: Segment a time series using a variety of algorithms

Description

A wrapper function that encapsulates various algorithms for detecting changepoint sets in univariate time series.

Usage

segment(x, method = "null", ...)
# S3 method for tbl_ts
segment(x, method = "null", ...)
# S3 method for xts
segment(x, method = "null", ...)
# S3 method for numeric
segment(x, method = "null", ...)
# S3 method for ts
segment(x, method = "null", ...)

Value

An object of class tidycpt.

Arguments

x

a numeric vector coercible into a stats::ts object

method

a character string indicating the algorithm to use. See Details.

...

arguments passed to methods

Details

Currently, segment() can use the following algorithms, depending on the value of the method argument:

• pelt: Uses the PELT algorithm as implemented in segment_pelt(), which wraps either changepoint::cpt.mean() or changepoint::cpt.meanvar(). The segmenter is of class cpt.

• binseg: Uses the Binary Segmentation algorithm as implemented by changepoint::cpt.meanvar(). The segmenter is of class cpt.

• segneigh: Uses the Segmented Neighborhood algorithm as implemented by changepoint::cpt.meanvar(). The segmenter is of class cpt.

• single-best: Uses the AMOC criteria as implemented by changepoint::cpt.meanvar(). The segmenter is of class cpt.

• wbs: Uses the Wild Binary Segmentation algorithm as implemented by wbs::wbs(). The segmenter is of class wbs.

• ga: Uses the Genetic algorithm implemented by segment_ga(), which wraps GA::ga(). The segmenter is of class tidyga.

• ga-shi: Uses the genetic algorithm implemented by segment_ga_shi(), which wraps segment_ga(). The segmenter is of class tidyga.

• ga-coen: Uses Coen's heuristic as implemented by segment_ga_coen(). The segmenter is of class tidyga. This implementation supersedes the following one.

• coen: Uses Coen's heuristic as implemented by segment_coen(). The segmenter is of class seg_basket(). Note that this function is deprecated.

• random: Uses a random basket of changepoints as implemented by segment_ga_random(). The segmenter is of class tidyga.

• manual: Uses the vector of changepoints in the tau argument. The segmenter is of class seg_cpt`.

• null: The default. Uses no changepoints. The segmenter is of class seg_cpt.

See Also

changepoint::cpt.meanvar(), wbs::wbs(), GA::ga(), segment_ga()

Examples

# Segment a time series using PELT
segment(DataCPSim, method = "pelt")

# Segment a time series using PELT and the BIC penalty
segment(DataCPSim, method = "pelt", penalty = "BIC")

# Segment a time series using Binary Segmentation
segment(DataCPSim, method = "binseg", penalty = "BIC")

# Segment a time series using a random changepoint set
segment(DataCPSim, method = "random")

# Segment a time series using a manually-specified changepoint set
segment(DataCPSim, method = "manual", tau = c(826))

# Segment a time series using a null changepoint set
segment(DataCPSim)