Changepoint wrapper — cpt_wrapper • ggchangepoint

This function wraps a number of cpt functions from the changepoint package and the cpt.np() function from the changepoint.np package. It is handy that users can use this function to get the same changepoint results as these functions output individually. Moreover, it returns a tibble that inherits the tidyverse style. Functions from the changepoint package do require data normality assumption by default, yet changepoint.np is a non-parametric way to detect changepoints and let data speak by itself. If user sets change_in as np (or cpt_np), a seed should be set before using the function for the sake of reproducibility. For more details on the changepoint and changepoint.np packages, please refer to their documentation.

Usage

cpt_wrapper(data, change_in = "mean_var", cp_method = "PELT", ...)

Arguments

data: A numeric vector.
change_in: Choice of mean_var, mean, var, and np (or cpt_np for backward compatibility). Each choice corresponds to cpt.meanvar(), cpt.mean(), cpt.var() and cpt.np() respectively. The default is mean_var.
cp_method: A wide range of choices (i.e., AMOC, PELT, SegNeigh or BinSeg). Please note when change_in is np or cpt_np, PELT is the only option.
...: Extra arguments for each cpt function mentioned in the change_in section.

Value

A tibble including which point(s) is/are the changepoint along with raw changepoint value corresponding to that changepoint. Changepoint locations follow the convention of the changepoint package: the last index of the left segment.

References

Killick R, Eckley I (2014). “changepoint: An R package for changepoint analysis.” Journal of statistical software, 58(3), 1–19.

Examples

set.seed(2022)
cpt_wrapper(c(rnorm(100,0,1),rnorm(100,0,10)))
#> # A tibble: 1 × 2
#>      cp cp_value
#>   <int>    <dbl>
#> 1   100    0.467
cpt_wrapper(c(rnorm(100,0,1),rnorm(100,10,1)))
#> # A tibble: 1 × 2
#>      cp cp_value
#>   <int>    <dbl>
#> 1   100    0.225