Simulate diagnostic circular-linear data
Source:R/directional-diagnostics.R
simulate_cyl_diagnostic.RdSimulate diagnostic circular-linear data
Usage
simulate_cyl_diagnostic(
n = 800,
scenario = c("independent", "smooth", "heteroscedastic", "multimodal", "seam"),
seed = NULL
)See also
Other directional diagnostics:
autoplot.diagnostic_atlas_data(),
diagnostic_atlas_data(),
diagnostic_scenarios(),
plot_classical_comparison(),
plot_diagnostic_atlas(),
simulate_tor_diagnostic()
Examples
simulate_cyl_diagnostic(n = 40, scenario = "smooth", seed = 1)
#> theta x scenario
#> 1 1.66824013 3.270595 smooth
#> 2 2.33812342 2.520929 smooth
#> 3 3.59934384 2.422176 smooth
#> 4 5.70643784 2.800610 smooth
#> 5 1.26720495 3.788633 smooth
#> 6 5.64474887 3.261412 smooth
#> 7 5.93556977 3.616537 smooth
#> 8 4.15191498 2.041517 smooth
#> 9 3.95284012 2.313467 smooth
#> 10 0.38821459 4.401275 smooth
#> 11 1.29417642 3.956145 smooth
#> 12 1.10933879 3.803893 smooth
#> 13 4.31669186 2.564539 smooth
#> 14 2.41339484 2.249672 smooth
#> 15 4.83705630 2.163761 smooth
#> 16 3.12713657 2.155049 smooth
#> 17 4.50893007 2.357716 smooth
#> 18 6.23232980 3.993828 smooth
#> 19 2.38783146 2.584349 smooth
#> 20 4.88483239 2.784132 smooth
#> 21 5.87292617 3.532088 smooth
#> 22 1.33293077 3.447422 smooth
#> 23 4.09458703 2.647553 smooth
#> 24 0.78888593 4.321806 smooth
#> 25 1.67899698 2.804790 smooth
#> 26 2.42602639 2.061289 smooth
#> 27 0.08413394 4.235575 smooth
#> 28 2.40261439 2.484693 smooth
#> 29 5.46442874 3.022617 smooth
#> 30 2.13847582 2.692273 smooth
#> 31 3.02899870 2.356295 smooth
#> 32 3.76718318 2.258802 smooth
#> 33 3.10101149 2.359405 smooth
#> 34 1.17003970 3.435799 smooth
#> 35 5.19853988 3.181887 smooth
#> 36 4.20010039 3.008441 smooth
#> 37 4.99035622 2.524180 smooth
#> 38 0.67822980 3.942742 smooth
#> 39 4.54720998 2.632375 smooth
#> 40 2.58411345 2.175314 smooth