plot.lvm {lava}

Plot path diagram

Description

Plot the path diagram of a SEM

Usage

## S3 method for class 'lvm'
plot(
  x,
  diag = FALSE,
  cor = TRUE,
  labels = FALSE,
  intercept = FALSE,
  addcolor = TRUE,
  plain = FALSE,
  cex,
  fontsize1 = 10,
  noplot = FALSE,
  graph = list(rankdir = "BT"),
  attrs = list(graph = graph),
  unexpr = FALSE,
  addstyle = TRUE,
  plot.engine = lava.options()$plot.engine,
  init = TRUE,
  layout = lava.options()$layout,
  edgecolor = lava.options()$edgecolor,
  graph.proc = lava.options()$graph.proc,
  ...
)

Arguments

x

Model object

diag

Logical argument indicating whether to visualize variance parameters (i.e. diagonal of variance matrix)

cor

Logical argument indicating whether to visualize correlation parameters

labels

Logical argument indiciating whether to add labels to plot (Unnamed parameters will be labeled p1,p2,...)

intercept

Logical argument indiciating whether to add intercept labels

addcolor

Logical argument indiciating whether to add colors to plot (overrides nodecolor calls)

plain

if TRUE strip plot of colors and boxes

cex

Fontsize of node labels

fontsize1

Fontsize of edge labels

noplot

if TRUE then return graphNEL object only

graph

Graph attributes (Rgraphviz)

attrs

Attributes (Rgraphviz)

unexpr

if TRUE remove expressions from labels

addstyle

Logical argument indicating whether additional style should automatically be added to the plot (e.g. dashed lines to double-headed arrows)

plot.engine

default 'Rgraphviz' if available, otherwise visNetwork,igraph

init

Reinitialize graph (for internal use)

layout

Graph layout (see Rgraphviz or igraph manual)

edgecolor

if TRUE plot style with colored edges

graph.proc

Function that post-process the graph object (default: subscripts are automatically added to labels of the nodes)

...

Additional arguments to be passed to the low level functions

Author(s)

Klaus K. Holst

Examples

if (interactive()) {
m <- lvm(c(y1,y2) ~ eta)
regression(m) <- eta ~ z+x2
regression(m) <- c(eta,z) ~ x1
latent(m) <- ~eta
labels(m) <- c(y1=expression(y[scriptscriptstyle(1)]),
y2=expression(y[scriptscriptstyle(2)]),
x1=expression(x[scriptscriptstyle(1)]),
x2=expression(x[scriptscriptstyle(2)]),
eta=expression(eta))
edgelabels(m, eta ~ z+x1+x2, cex=2, lwd=3,
           col=c("orange","lightblue","lightblue")) <- expression(rho,phi,psi)
nodecolor(m, vars(m), border="white", labcol="darkblue") <- NA
nodecolor(m, ~y1+y2+z, labcol=c("white","white","black")) <- NA
plot(m,cex=1.5)

d <- sim(m,100)
e <- estimate(m,d)
plot(e)

m <- lvm(c(y1,y2) ~ eta)
regression(m) <- eta ~ z+x2
regression(m) <- c(eta,z) ~ x1
latent(m) <- ~eta
plot(lava:::beautify(m,edgecol=FALSE))
}