plot.lsjm: Two dimensional plot of Latent Space Joint Model output

In lvm4net: Latent Variable Models for Networks

Description

Function to plot an object of class 'lsjm'

Usage

## S3 method for class 'lsjm'
plot(x, Y, drawCB = FALSE, dimZ = c(1, 2),
  plotZtilde = FALSE, colPl = 1, colEll = rgb(0.6, 0.6, 0.6, alpha =
  0.1), LEVEL = 0.95, pchplot = 20, pchEll = 19, pchPl = 19,
  cexPl = 1.1, mainZtilde = NULL, arrowhead = FALSE, curve = NULL,
  xlim = NULL, ylim = NULL, main = NULL, ...)

Arguments

x	object of class 'lsjm'
Y	list containing a (N x N) binary adjacency matrix for each network view.
drawCB	logical if drawCB = TRUE draw confidence bounds
dimZ	dimensions of the latent variable to be plotted. Default dimZ = c(1, 2)
plotZtilde	if TRUE do the plot for the last step of LSM
colPl	col for the points representing the nodes. Default colPl = NULL
colEll	col for the ellipses. Default rgb(.6, .6 ,.6 , alpha=.1)
LEVEL	levels of confidence bounds shown when plotting the ellipses. Default LEVEL = .95
pchplot	Default pchplot = 20
pchEll	pch for the ellipses. Default pchEll = 19
pchPl	pch for the points representing the nodes. Default pchPl = 19
cexPl	cex for the points representing the nodes. Default cexPl = 1.1
mainZtilde	title for single network plots TRUE do the plot for the last step of LSM
arrowhead	logical, if the arrowed are to be plotted. Default arrowhead = FALSE
curve	curvature of edges. Default curve = 0
xlim	range for x
ylim	range for y
main	main title
...	Arguments to be passed to methods, such as graphical parameters (see par).

Examples

## Simulate Undirected Network
  N <- 20
  Ndata <- 2
   Y <- list()
   Y[[1]] <- network(N, directed = FALSE)[,]
   ### create a new view that is similar to the original
  for(nd in 2:Ndata){
    Y[[nd]] <- Y[[nd - 1]] - sample(c(-1, 0, 1), N * N, replace = TRUE, 
    prob = c(.05, .85, .1))
    Y[[nd]] <- 1 * (Y[[nd]]  > 0 )
  diag(Y[[nd]]) <- 0
   }

par(mfrow = c(1, 2))
z <- plotY(Y[[1]], verbose = TRUE, main = 'Network 1')
plotY(Y[[2]], EZ = z, main = 'Network 2')
par(mfrow = c(1, 1))

modLSJM <- lsjm(Y, D = 2) 
plot(modLSJM, Y, drawCB = TRUE)
plot(modLSJM, Y, drawCB = TRUE, plotZtilde = TRUE)

Example output

Loading required package: MASS
Loading required package: ergm
Loading required package: network
network: Classes for Relational Data
Version 1.14-377 created on 2019-03-04.
copyright (c) 2005, Carter T. Butts, University of California-Irvine
                    Mark S. Handcock, University of California -- Los Angeles
                    David R. Hunter, Penn State University
                    Martina Morris, University of Washington
                    Skye Bender-deMoll, University of Washington
 For citation information, type citation("network").
 Type help("network-package") to get started.


ergm: version 3.9.4, created on 2018-08-15
Copyright (c) 2018, Mark S. Handcock, University of California -- Los Angeles
                    David R. Hunter, Penn State University
                    Carter T. Butts, University of California -- Irvine
                    Steven M. Goodreau, University of Washington
                    Pavel N. Krivitsky, University of Wollongong
                    Martina Morris, University of Washington
                    with contributions from
                    Li Wang
                    Kirk Li, University of Washington
                    Skye Bender-deMoll, University of Washington
Based on "statnet" project software (statnet.org).
For license and citation information see statnet.org/attribution
or type citation("ergm").

NOTE: Versions before 3.6.1 had a bug in the implementation of the bd()
constriant which distorted the sampled distribution somewhat. In
addition, Sampson's Monks datasets had mislabeled vertices. See the
NEWS and the documentation for more details.

Loading required package: ellipse

Attaching package: 'ellipse'

The following object is masked from 'package:graphics':

    pairs

lvm4net documentation built on June 13, 2019, 5:03 p.m.