<- reproduce.track.3d(niclas, DEM = dem) cerw
The simulated trajectories result should be tested statistically. The
first argument of the test.verification.3d()
function is
the original track to be tested against. The second argument is either a
single track or a list of multiple tracks.
By setting test = "ks"
a two-sample Kolmogorov-Smirnov
test is carried out on the distributions of turn angles, lift angles and
step lengths of the two tracks.
<- test.verification.3d(niclas, cerw, test = "ks", plot = FALSE)
tests #> |*** Two-sample Kolmogorov-Smirnov test ***
#> |H0: Probability distributions do not differ significantly
#> |H1: Probability distributions differ significantly
#> |Turn angle - p-value: 0.958 > 0.05, *H0*, autodifferences - p-value: 0.951 > 0.05, *H0*
#> |Lift angle - p-value: 0.239 > 0.05, *H0*, autodifferences - p-value: 0.03 < 0.05, *H1*
#> |Step length - p-value: 0.958 > 0.05, *H0*, autodifferences - p-value: 0.998 > 0.05, *H0*
By choosing test = "ttest"
a random sample, without
replacement is taken from the longer track, to shorten it to the length
of the longer track. The order of the shorter track is also sampled
randomly. Then the two randomly ordered vectors of turn angles, lift
angles and step lengths are substracted from each other. If the both
tracks stem from the same distributions the the mean deviatio should
tend to towards zero, therefore the difference is tested two-sided
against mu = 0 with a one-sample t-test.
<- test.verification.3d(niclas, cerw, test = "ttest", plot = FALSE)
tests #> |*** One Sample t-test ***
#> |H0: Difference between tracks does not differ significantly from 0
#> |H1: Difference between tracks differs significantly from 0
#> |Turn angle - p-value: 0.527 > 0.05, *H0*
#> |Lift angle - p-value: 0.898 > 0.05, *H0*
#> |Step length - p-value: 0.704 > 0.05, *H0*