Alters labels of nodes and edges in the graph of a latent variable model

# S3 method for default
labels(object, ...) <- value
# S3 method for lvm
edgelabels(object, to, ...) <- value
# S3 method for default
nodecolor(object, var=vars(object),
border, labcol, shape, lwd, ...) <- value

Arguments

object

lvm-object.

...

Additional arguments (lwd, cex, col, labcol), border.

value

node label/edge label/color

to

Formula specifying outcomes and predictors defining relevant edges.

var

Formula or character vector specifying the nodes/variables to alter.

border

Colors of borders

labcol

Text label colors

shape

Shape of node

lwd

Line width of border

Author

Klaus K. Holst

Examples

m <- lvm(c(y,v)~x+z) regression(m) <- c(v,x)~z labels(m) <- c(y=expression(psi), z=expression(zeta)) nodecolor(m,~y+z+x,border=c("white","white","black"), labcol="white", lwd=c(1,1,5), lty=c(1,2)) <- c("orange","indianred","lightgreen") edgelabels(m,y~z+x, cex=c(2,1.5), col=c("orange","black"),labcol="darkblue", arrowhead=c("tee","dot"), lwd=c(3,1)) <- expression(phi,rho) edgelabels(m,c(v,x)~z, labcol="red", cex=0.8,arrowhead="none") <- 2 if (interactive()) { plot(m,addstyle=FALSE) } m <- lvm(y~x) labels(m) <- list(x="multiple\nlines") if (interactive()) { op <- par(mfrow=c(1,2)) plot(m,plain=TRUE) plot(m) par(op) d <- sim(m,100) e <- estimate(m,d) plot(e,type="sd") }