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.
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.
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, ]
#> # A tibble: 5 × 5
#> method data_type reps hit_rate fp
#> <chr> <chr> <int> <dbl> <dbl>
#> 1 decafs bernoulli 10 1 102.
#> 2 nsp bernoulli 10 1 102.
#> 3 smuce bernoulli 10 1 102.
#> 4 wbs2 bernoulli 10 1 102.
#> 5 idetect bernoulli 10 1 96.1