orthobasis {ade4} | R Documentation |
These functions returns object of class 'orthobasis'
that contains data frame with n rows and n-1 columns.
Each data frame defines an orthonormal basis for the uniform weights.
orthobasic.neig
returns the eigen vectors of the matrix N-M where M is the symmetric n by n matrix of the between-sites neighbouring graph and N is the diagonal matrix of neighbour numbers.
orthobasis.line
returns the analytical solution for the linear neighbouring graph.
orthobasic.circ
returns the analytical solution for the circular neighbouring graph.
orthobsic.mat
returns the eigen vectors of the general link matrix M.
orthobasis.listw
returns the eigen vectors of the general link matrix M associated to a listw
object.
orthobasis.haar
returns wavelet haar basis.
orthobasis.neig(neig) orthobasis.line(n) orthobasis.circ(n) orthobasis.mat(mat, cnw=TRUE) orthobasis.listw(listw) orthobasis.haar(n) print.orthobasis(x,...)
neig |
is an object of class neig |
n |
is an integer that defines length of vectors |
mat |
is a n by n phylogenetic or spatial link matrix |
listw |
is a 'listw' object |
cnw |
if TRUE, the matrix of the neighbouring graph is modified to give Constant Neighbouring Weights |
x |
is an object of class orthobasis |
... |
: further arguments passed to or from other methods |
All the functions excepted print.ortobasis
return an object of class orthobasis
containing a data frame.
This data frame defines an orthonormal basis with n-1 vectors of length n. Various attributes are associated to it :
names |
: names of the vectors |
row.names |
: row names of the data frame |
class |
: class |
values |
: row weights (uniform weights) |
weights |
: numeric values to class vectors according to their quadratic forms (Moran ones) |
call |
: call |
the function orthobasis.haar
uses function wavelet.filter
from package waveslim.
Sébastien Ollier ollier@biomserv.univ-lyon1.fr
Daniel Chessel chessel@biomserv.univ-lyon1.fr
Misiti, M., Misiti, Y., Oppenheim, G. and Poggi, J.M. (1993) Analyse de signaux classiques par décomposition en ondelettes. Revue de Statistique Appliquée, 41, 5–32.
Cornillon, P.A. (1998) Prise en compte de proximités en analyse factorielle et comparative. Thèse, Ecole Nationale Supérieure Agronomique, Montpellier.
gridrowcol
that defines an orthobasis for square grid, phylog
that defines an orthobasis for phylogenetic tree, orthogram
and mld
# a 2D spatial orthobasis par(mfrow = c(4,4)) w <- gridrowcol(8,8) for (k in 1:16) s.value(w$xy, w$orthobasis[,k], cleg = 0, csi = 2, incl = FALSE, addax = FALSE, sub = k, csub = 4, ylim = c(0,10), cgri = 0) par(mfrow = c(1,1)) barplot(attr(w$orthobasis, "values")) # Haar 1D orthobasis w <- orthobasis.haar(32) par(mfrow = c(8,4)) par(mar = c(0.1,0.1,0.1,0.1)) for (k in 1:31) { plot(w[,k], type="S",xlab = "", ylab = "", xaxt = "n", yaxt = "n", xaxs = "i", yaxs = "i",ylim=c(-4.5,4.5)) points(w[,k], type = "p", pch = 20, cex = 1.5) } # a 1D orthobasis w <- orthobasis.line(n = 33) par(mfrow = c(8,4)) par(mar = c(0.1,0.1,0.1,0.1)) for (k in 1:32) { plot(w[,k], type="l",xlab = "", ylab = "", xaxt = "n", yaxt = "n", xaxs = "i", yaxs = "i",ylim=c(-1.5,1.5)) points(w[,k], type = "p", pch = 20, cex = 1.5) } par(mfrow = c(1,1)) barplot(attr(w, "values")) w <- orthobasis.circ(n = 26) #par(mfrow = c(5,5)) #par(mar = c(0.1,0.1,0.1,0.1)) # for (k in 1:25) # dotcircle(w[,k], xlim = c(-1.5,1.5), cleg = 0) par(mfrow = c(1,1)) #barplot(attr(w, "values")) ## Not run: # a spatial orthobasis data(mafragh) w <- orthobasis.neig(mafragh$neig) par(mfrow = c(4,2)) for (k in 1:8) s.value(mafragh$xy, w[,k],cleg = 0, sub = as.character(k), csub = 3) par(mfrow = c(1,1)) barplot(attr(w, "values")) # a phylogenetic orthobasis data(njplot) phy <- newick2phylog(njplot$tre) wA <- phy$Ascores wW <- phy$Wscores table.phylog(phylog = phy, wA, clabel.row = 0, clabel.col = 0.5) table.phylog(phylog = phy, wW, clabel.row = 0, clabel.col = 0.5) ## End(Not run)