Kernel 3D

In this document we compute a three dimension Kernel Density Estimate as by https://www.rdocumentation.org/packages/misc3d/versions/0.8-4/topics/kde3d with a customisation of the DrawDensity3D https://www.rdocumentation.org/packages/VecStatGraphs3D/versions/1.6/topics/DrawDensity3D function.

First of all, we load the needed function (DibujarDensidad3D)

source('DibujarDensidad3D.R', chdir = TRUE)

Then we load the required libraries

require(rgl)
require(VecStatGraphs3D)
require(spatstat)

We’re ready to load the files with coordinates

sh1<-read.csv("suelo_h1.csv",header=FALSE)
sh2<-read.csv("suelo_h2.csv",header=FALSE)
sh3<-read.csv("suelo_h3.csv",header=FALSE)
sh4<-read.csv("suelo_h4.csv",header=FALSE)
suh<-rbind(sh1,sh2,sh3,sh4)

Once libraries are files are in place, we can subset the files.

We begin with the faunal remains and LAYER H1

fauh<-subset(suh,suh[,6]==1)
fauh3d<-pp3(fauh[,2],fauh[,3],fauh[,4],box3(c(999,1004),c(995,999),c(407,408)))
plot.pp3(fauh3d)

FAUNAL REMAINS 3D DENSITY KERNEL FORTEA’S LAYER h

par(mfrow=c(2,2))

K-function of a Three-Dimensional Point Pattern

k3<-K3est(fauh3d)
plot(k3)

Nearest Neighbour Distance Distribution Function of a Three-Dimensional Point Pattern

g3<-G3est(fauh3d)
plot(g3)

Empty Space Function of a Three-Dimensional Point Pattern

j3<-F3est(fauh3d)
plot(j3)

Pair Correlation Function of a Three-Dimensional Point Pattern

p3<-pcf3est(fauh3d)
plot(p3)

POTTERY FORTEA’S LAYER h

fauh<-subset(suh,suh[,6]==2)
fauh3d<-pp3(fauh[,2],fauh[,3],fauh[,4],box3(c(999,1004),c(995,999),c(407,408)))
plot.pp3(fauh3d)

par(mfrow=c(2,2))

K-function of a Three-Dimensional Point Pattern

k3<-K3est(fauh3d)
plot(k3)

Nearest Neighbour Distance Distribution Function of a Three-Dimensional Point Pattern

g3<-G3est(fauh3d)
plot(g3)

Empty Space Function of a Three-Dimensional Point Pattern

j3<-F3est(fauh3d)
plot(j3)

Pair Correlation Function of a Three-Dimensional Point Pattern

p3<-pcf3est(fauh3d)
plot(p3)

FLINT FORTEA’S LAYER h

fauh<-subset(suh,suh[,6]==3)
fauh3d<-pp3(fauh[,2],fauh[,3],fauh[,4],box3(c(999,1004),c(995,999),c(407,408)))
plot.pp3(fauh3d)

par(mfrow=c(2,2))

K-function of a Three-Dimensional Point Pattern

k3<-K3est(fauh3d)
plot(k3)

Nearest Neighbour Distance Distribution Function of a Three-Dimensional Point Pattern

g3<-G3est(fauh3d)
plot(g3)

Empty Space Function of a Three-Dimensional Point Pattern

j3<-F3est(fauh3d)
plot(j3)

Pair Correlation Function of a Three-Dimensional Point Pattern

p3<-pcf3est(fauh3d)
plot(p3)

MOLLUSCS FORTEA’S LAYER h

fauh<-subset(suh,suh[,6]==4)
fauh3d<-pp3(fauh[,2],fauh[,3],fauh[,4],box3(c(999,1004),c(995,999),c(407,408)))
plot.pp3(fauh3d)

par(mfrow=c(2,2))

K-function of a Three-Dimensional Point Pattern

k3<-K3est(fauh3d)
plot(k3)

Nearest Neighbour Distance Distribution Function of a Three-Dimensional Point Pattern

g3<-G3est(fauh3d)
plot(g3)

Empty Space Function of a Three-Dimensional Point Pattern

j3<-F3est(fauh3d)
plot(j3)

Pair Correlation Function of a Three-Dimensional Point Pattern

p3<-pcf3est(fauh3d)
plot(p3)

THAT’S ALL FOLKS