Manually segment a time series — segment

Segment a time series by manually inputting the changepoint set

Usage

segment_manual(x, tau, ...)

Arguments

x: A time series
tau: a set of indices representing a changepoint set
...: arguments passed to seg_cpt

Value

A seg_cpt object

Details

Sometimes you want to see how a manually input set of changepoints performs. This function takes a time series and a changepoint detection set as inputs and returns a seg_cpt object representing the segmenter. Note that by default fit_meanshift_norm() is used to fit the model and BIC() is used as the penalized objective function.

Examples

# Segment a time series manually
segment_manual(CET, tau = c(84, 330))
#> List of 8
#>  $ data        : Time-Series [1:362] from 1 to 362: 8.87 9.1 9.78 9.52 8.63 9.34 8.29 9.86 8.52 9.51 ...
#>  $ pkg         : chr "tidychangepoint"
#>  $ algorithm   : chr "manual"
#>  $ changepoints: num [1:2] 84 330
#>  $ fitness     : Named num 688
#>   ..- attr(*, "names")= chr "BIC"
#>  $ seg_params  : list()
#>  $ model_name  : chr "meanshift_norm"
#>  $ penalty     : chr "BIC"
#>  - attr(*, "class")= chr "seg_cpt"
segment_manual(CET, tau = NULL)
#> List of 8
#>  $ data        : Time-Series [1:362] from 1 to 362: 8.87 9.1 9.78 9.52 8.63 9.34 8.29 9.86 8.52 9.51 ...
#>  $ pkg         : chr "tidychangepoint"
#>  $ algorithm   : chr "manual"
#>  $ changepoints: NULL
#>  $ fitness     : Named num 759
#>   ..- attr(*, "names")= chr "BIC"
#>  $ seg_params  : list()
#>  $ model_name  : chr "meanshift_norm"
#>  $ penalty     : chr "BIC"
#>  - attr(*, "class")= chr "seg_cpt"