This session is concerned with summary statistics for spacings and interpoint distances. The lecturer’s R script is available here (right click and save).
For the swedishpines
data:
Calculate the estimate of the nearest neighbour distance distribution function G using Gest
.
Plot the estimate of G(r) against r.
Plot the estimate of G(r) against the theoretical (Poisson) value G_{pois}(r)=1 − exp(−λπr^{2}).
Define Fisher’s variance-stabilising transformation for c.d.f.’s by
Phi <- function(x) asin(sqrt(x))
Plot the G function using the formula Phi(.) ~ Phi(theo)
and interpret it.
For the swedishpines
data:
Calculate the estimate of the nearest neighbour distance distribution function F using Fest
.
Plot the estimate of F(r) against r.
Plot the estimate of F(r) against the theoretical (Poisson) value F_{pois}(r)=1 − exp(−λπr^{2}).
Define Fisher’s variance-stabilising transformation for c.d.f.’s by
Phi <- function(x) asin(sqrt(x))
Plot the F function using the formula Phi(.) ~ Phi(theo)
and interpret it.