funsMuVarCS1D {pcds} | R Documentation |
Returning the mean and (asymptotic) variance of arc density of Central Similarity Proximity Catch Digraph (CS-PCD) for 1D data - middle interval case
Description
Two functions: muCS1D
and asy.varCS1D
.
muCS1D
returns the mean of the (arc) density of CS-PCD
and asy.varCS1D
returns the (asymptotic) variance of the arc density of CS-PCD
for a given centrality parameter c \in (0,1)
and an expansion parameter t>0
and 1D uniform data in a
finite interval (a,b)
, i.e., data from U(a,b)
distribution.
See also (Ceyhan (2016)).
Usage
muCS1D(t, c)
asy.varCS1D(t, c)
Arguments
t |
A positive real number which serves as the expansion parameter in CS proximity region. |
c |
A positive real number in |
Value
muCS1D
returns the mean and asy.varCS1D
returns the asymptotic variance of the
arc density of CS-PCD for uniform data in an interval
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
muPE1D
and asy.varPE1D
Examples
#Examples for muCS1D
muCS1D(1.2,.4)
muCS1D(1.2,.6)
tseq<-seq(0.01,5,by=.05)
cseq<-seq(0.01,.99,by=.05)
ltseq<-length(tseq)
lcseq<-length(cseq)
mu.grid<-matrix(0,nrow=ltseq,ncol=lcseq)
for (i in 1:ltseq)
for (j in 1:lcseq)
{
mu.grid[i,j]<-muCS1D(tseq[i],cseq[j])
}
persp(tseq,cseq,mu.grid, xlab="t", ylab="c", zlab="mu(t,c)",theta = -30,
phi = 30, expand = 0.5, col = "lightblue", ltheta = 120,
shade = 0.05, ticktype = "detailed")
#Examples for asy.varCS1D
asy.varCS1D(1.2,.8)
tseq<-seq(0.01,5,by=.05)
cseq<-seq(0.01,.99,by=.05)
ltseq<-length(tseq)
lcseq<-length(cseq)
var.grid<-matrix(0,nrow=ltseq,ncol=lcseq)
for (i in 1:ltseq)
for (j in 1:lcseq)
{
var.grid[i,j]<-asy.varCS1D(tseq[i],cseq[j])
}
persp(tseq,cseq,var.grid, xlab="t", ylab="c", zlab="var(t,c)", theta = -30,
phi = 30, expand = 0.5, col = "lightblue", ltheta = 120,
shade = 0.05, ticktype = "detailed")