fda.usc (version 1.2.3)

metric.hausdorff: Compute the Hausdorff distances between two curves.

Description

Hausdorff distance is the greatest of all the distances from a point in one curve to the closest point in the other curve (been closest the euclidean distance).

Usage

metric.hausdorff(fdata1, fdata2 = fdata1)

Arguments

fdata1

Curves 1 of fdata class. The dimension of fdata1 object is (n1 x m), where n1 is the number of points observed in t coordinates with lenght m.

fdata2

Curves 2 of fdata class. The dimension of fdata2 object is (n2 x m), where n2 is the number of points observed in t coordinates with lenght m.

Details

Let $G(X)={(t,X(t)) \in R^2}$ and $G(Y)={(s,Y(s)) \in R^2}$ be two graphs of the considered curves $X$ and $Y$ respectively, the Hausdorff distance $d_H(X, Y)$ is defined as,

$$ d_H(X,Y)=max\left\{ sup_{x\in G(X)} inf_{y\in G(Y)} d_2(x,y), sup_{y\in G(Y)} inf_{x\in G(X)}d_2(x,y)\right\},$$ where $d_2(x,y)$ is the euclidean distance, see metric.lp.

Examples

## Not run:    
# data(poblenou)
# nox<-poblenou$nox[1:6]
# # Hausdorff vs maximum distance
# out1<-metric.hausdorff(nox)       
# out2<-metric.lp(nox,lp=0) 
# out1
# out2
# par(mfrow=c(1,3))
# plot(nox)
# plot(hclust(as.dist(out1)))
# plot(hclust(as.dist(out2)))
# ## End(Not run)