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Plots a layered model and summarizes the statistics for each layer from a Changepoint result

Source: R/cp_layers.R
cp_layers.Rd

Given a number of breakpoints, plots a layered model of one variable against distance, plots the confidence intervals for each layer, and gives a summary table.

Usage

cp_layers(x, breaks, conf.level = 0.95)

Arguments

x

The resulting object from cp_aic_eta()

breaks

An integer giving the number of breakpoints to use (from 'Changepoint')

conf.level

Confidence level to use for plot and summary statistics (Default is 0.95)

Value

A ggplot and plotly objects showing the layered model, another showing the confidence intervals, and a summary table

See also

Other layer detection: RI(), T2_stat(), T_stat(), cp_aic_eta(), layers_window(), sc_bic(), sc_layers()

Examples

cp = cp_aic_eta(DPM_data, m = 10, nl = 3)
cp_layers(cp, breaks = 2)
#> $LayersGG

#> 
#> $LayersLY
#> 
#> $StatsGG

#> 
#> $StatsLY
#> 
#> $Summary
#>      Layers Obs  Mean    SD Min Max CI.lwr CI.upr   MoE
#> 1   [0,2.7]  28  4.96 2.190   0  10   4.12   5.81 0.849
#> 2 (2.7,8.7]  60  8.08 1.150   6  11   7.79   8.38 0.297
#> 3  (8.7,10]  13 10.70 0.855  10  12  10.20  11.20 0.517
#> 
#> $ES
#> [1] 0.606
#>