cpt_data_types: False positives and power by data type

In ggchangepoint: Combines Changepoint Analysis with 'ggplot2'

False positives and power by data type

Description

Ten replicates of a 400-point series with one change at 200, at comparable effect sizes across four data types: Gaussian (a shift of 1.4 standard deviations), Bernoulli (probability 0.15 to 0.75), Poisson (rate 2 to 10) and a proportion (binomial of 20, 0.25 to 0.6). Each engine is at its default, as a user who does not set family gets it.

Usage

cpt_data_types

Format

A tibble with one row per engine and data type:

method

the engine.

data_type

"gaussian", "bernoulli", "poisson" or "proportion".

reps

replicates that ran.

hit_rate

share of replicates finding the change within 20 positions.

fp

mean number of other reported changepoints.

Source

data-raw/measure_engines.R (part datatype).

See Also

Other measurement tables: cpt_calibration, cpt_invariances, cpt_noise_benchmark, cpt_null_sizes, cpt_runtimes

Examples

b <- subset(cpt_data_types, data_type == "bernoulli")
b[order(-b$fp), ][1:5, ]

ggchangepoint documentation built on Nov. 5, 2026, 9:06 a.m.