Compares observed and simulated path structure using the straightness index, defined as net displacement divided by total path length. Low values indicate more tortuous trajectories.
Arguments
- observed
Observed track-like object.
- simulated
A list of simulated track-like objects or a data frame with a simulation identifier column.
- ...
Passed to
as_gmov_simulations().
Value
A list with observed and simulated straightness indices, discrepancy statistics, and a Monte Carlo rank test.
References
Benhamou, S. (2004). How to reliably estimate the tortuosity of an animal's path. Journal of Theoretical Biology, 229(2), 209-220. https://doi.org/10.1016/j.jtbi.2004.03.016
Nicosia, A. (2026). Beyond the next step: A multi-criteria generative validation framework for step selection functions. Methods in Ecology and Evolution. https://doi.org/10.1111/2041-210x.70313
Examples
observed <- data.frame(x = c(0, 1, 1), y = c(0, 0, 1))
simulated <- list(
data.frame(x = c(0, 1, 2), y = c(0, 0, 0)),
data.frame(x = c(0, 0, 1), y = c(0, 1, 1))
)
validate_sinuosity(observed, simulated)
#> gmov sinuosity diagnostic
#> Measure: straightness_index
#> Simulated tracks: 2
#> Observed value: 0.7071
#> Discrepancy statistic: 0.1464
#> Monte Carlo p-value: 1.000
#> Alternative: greater