R/R-function.R In SGCS: Spatial Graph Based Clustering Summaries for Spatial Point Patterns

Documented in Rfun

```#' Clustering function versio 2
#'
#' Ratio of triplets to pairs^2, motivated by T/K^2.
#'
#' @param x Point pattern
#' @param r Vector of distances
#' @param correction Border correction. "none" or "border" (reduced window) supported.
#' @param scaled Scale with theoretical value?
#' @param ... ignored.
#'
#' @details
#'
#' Reduced border correction available.
#'
#' @return
#'
#' @examples
#' \dontrun{
#' en <- envelope(rcell(nx=15), fun=Rfun)
#' plot(en)
#' }
#' @useDynLib SGCS
#' @import spatstat
#' @export

Rfun <- function(x, r, correction="border", scaled=FALSE, ...) {
### prepare data
x <- internalise_pp(x)
### range
r <- default_r(x, r)

### Distances for speed
x\$pairwise_distances <- pairwise_distances(x)

### Border distances for correction
correction_i <- correction %in% c("border","best")
x\$edgeDistances <- if(correction_i) edge_distance(x) else rep(max(r), x\$n)

### Compute:
res <- .External("SGCS_Rfun_c",
x,
r,
PACKAGE="SGCS"
)

Te <- if(x\$dim==2) 0.5*pi*(pi-3*sqrt(3)/4)*r^4 else 5*pi^2*r^6/12
Ke <- if(x\$dim==2) pi*r^2 else pi*r^3 * 4/3
# div 0
i <- which(Ke==0)
Ke[i] <- 1e-9
#
lam <- x\$n/x\$area
lpr <- lam * Ke
p  <- 1 - exp(-lpr) * (lpr+1) # p(K>0)
theo <- (lam^2*Te / (lam*Ke*(lam*Ke+1))) * p
# if we scale away the Poisson value
if(scaled){
res <- res/theo
res[r==0] <- Inf
theo <- theo/theo
theo[r==0] <- Inf
}
# make fv suitable
c.final<-fv( data.frame(r=r, theo=theo, R=res),
argu = "r",
alim = range(r),
ylab = substitute(R(r), NULL),
desc = c("distance argument r", "Theoretical values unknown", "Ratio Function"),
valu = "R",
fmla = ".~r",
fname="R"
)

c.final
}
```

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SGCS documentation built on May 1, 2019, 8:20 p.m.