arcsCS1D {pcds} | R Documentation |
The arcs of Central Similarity Proximity Catch Digraph (CS-PCD) for 1D data - multiple interval case
Description
An object of class "PCDs"
.
Returns arcs of CS-PCD as tails (or sources) and heads (or arrow ends)
and related parameters and the quantities of the digraph.
The vertices of the CS-PCD are the 1D data points in Xp
in the multiple interval case.
Yp
determines the end points of the intervals.
If there are duplicates of Yp
points,
only one point is retained for each duplicate value,
and a warning message is printed.
For this function, CS proximity regions are constructed
data points inside or outside the intervals based
on Yp
points with expansion parameter t>0
and centrality parameter c \in (0,1)
. That is, for this function,
arcs may exist for points in the middle or end-intervals.
It also provides various descriptions and quantities about the arcs of the CS-PCD
such as number of arcs, arc density, etc.
Equivalent to function arcsCS1D
.
See also (Ceyhan (2016)).
Usage
arcsCS1D(Xp, Yp, t, c = 0.5)
Arguments
Xp |
A set or |
Yp |
A set or |
t |
A positive real number which serves as the expansion parameter in CS proximity region. |
c |
A positive real number in |
Value
A list
with the elements
type |
A description of the type of the digraph |
parameters |
Parameters of the digraph, here, they are expansion and centrality parameters. |
tess.points |
Tessellation points, i.e., points on which the tessellation of the study region is performed, here, tessellation
is the intervalization of the real line based on |
tess.name |
Name of the tessellation points |
vertices |
Vertices of the digraph, |
vert.name |
Name of the data set which constitute the vertices of the digraph |
S |
Tails (or sources) of the arcs of CS-PCD for 1D data |
E |
Heads (or arrow ends) of the arcs of CS-PCD for 1D data |
mtitle |
Text for |
quant |
Various quantities for the digraph: number of vertices, number of partition points, number of intervals, number of arcs, and arc density. |
Author(s)
Elvan Ceyhan
References
Ceyhan E (2016). “Density of a Random Interval Catch Digraph Family and its Use for Testing Uniformity.” REVSTAT, 14(4), 349-394.
See Also
arcsCSend.int
, arcsCSmid.int
, arcsCS1D
, and arcsPE1D
Examples
t<-2
c<-.4
a<-0; b<-10;
#nx is number of X points (target) and ny is number of Y points (nontarget)
nx<-20; ny<-4; #try also nx<-40; ny<-10 or nx<-1000; ny<-10;
set.seed(1)
xr<-range(a,b)
xf<-(xr[2]-xr[1])*.1
Xp<-runif(nx,a-xf,b+xf)
Yp<-runif(ny,a,b)
Arcs<-arcsCS1D(Xp,Yp,t,c)
Arcs
summary(Arcs)
plot(Arcs)
S<-Arcs$S
E<-Arcs$E
arcsCS1D(Xp,Yp,t,c)
arcsCS1D(Xp,Yp+10,t,c)
jit<-.1
yjit<-runif(nx,-jit,jit)
Xlim<-range(a,b,Xp,Yp)
xd<-Xlim[2]-Xlim[1]
plot(cbind(a,0),
main="arcs of CS-PCD for points (jittered along y-axis)\n in middle intervals ",
xlab=" ", ylab=" ", xlim=Xlim+xd*c(-.05,.05),ylim=3*c(-jit,jit),pch=".")
abline(h=0,lty=1)
points(Xp, yjit,pch=".",cex=3)
abline(v=Yp,lty=2)
arrows(S, yjit, E, yjit, length = .05, col= 4)
t<-2
c<-.4
a<-0; b<-10;
nx<-20; ny<-4; #try also nx<-40; ny<-10 or nx<-1000; ny<-10;
Xp<-runif(nx,a,b)
Yp<-runif(ny,a,b)
arcsCS1D(Xp,Yp,t,c)