EpiModel (version 2.0.1)

plot.netdx: Plot Dynamic Network Model Diagnostics

Description

Plots dynamic network model diagnostics calculated in netdx.

Usage

# S3 method for netdx
plot(
  x,
  type = "formation",
  method = "l",
  sims,
  stats,
  sim.lines,
  sim.col,
  sim.lwd,
  mean.line = TRUE,
  mean.smooth = TRUE,
  mean.col,
  mean.lwd = 2,
  mean.lty = 1,
  qnts = 0.5,
  qnts.col,
  qnts.alpha,
  qnts.smooth = TRUE,
  targ.line = TRUE,
  targ.col,
  targ.lwd = 2,
  targ.lty = 2,
  plots.joined,
  legend,
  grid = FALSE,
  ...
)

Arguments

x

An EpiModel object of class netdx.

type

Plot type, with options of "formation" for network model formation statistics, "duration" for dissolution model statistics for average edge duration, or "dissolution" for dissolution model statistics for proportion of ties dissolved per time step.

method

Plot method, with options of "l" for line plots and "b" for boxplots.

sims

If type="epi" or "formation", a vector of simulation numbers to plot. If type="network", a single simulation number for network plot, or else "min" to plot the simulation number with the lowest disease prevalence, "max" for the simulation with the highest disease prevalence, or "mean" for the simulation with the prevalance closest to the mean across simulations at the specified time step.

stats

Network statistics to plot, among those specified in the call to netdx, with the default to plot all statistics contained in the object.

sim.lines

If TRUE, plot individual simulation lines. Default is to plot lines for one-group models but not for two-group models.

sim.col

Vector of any standard R color format for simulation lines.

sim.lwd

Line width for simulation lines.

mean.line

If TRUE, plot mean of simulations across time.

mean.smooth

If TRUE, use a lowess smoother on the mean line.

mean.col

Vector of any standard R color format for mean lines.

mean.lwd

Line width for mean lines.

mean.lty

Line type for mean lines.

qnts

If numeric, plot polygon of simulation quantiles based on the range implied by the argument (see details). If FALSE, suppress polygon from plot.

qnts.col

Vector of any standard R color format for polygons.

qnts.alpha

Transparency level for quantile polygons, where 0 = transparent and 1 = opaque (see transco).

qnts.smooth

If TRUE, use a lowess smoother on quantile polygons.

targ.line

If TRUE, plot target or expected value line for the statistic of interest.

targ.col

Vector of standard R colors for target statistic lines, with default colors based on RColorBrewer color palettes.

targ.lwd

Line width for the line showing the target statistic values.

targ.lty

Line type for the line showing the target statistic values.

plots.joined

If TRUE and type="formation", combine all target statistics in one plot, versus one plot per target statistic if FALSE.

legend

If TRUE, plot default legend.

grid

If TRUE, a grid is added to the background of plot (see grid for details), with default of nx by ny.

...

additional arguments to pass.

Details

The plot function for netdx objects will generate plots of two types of model diagnostic statistics that run as part of the diagnostic tools within that function. The formation plot shows the summary statistics requested in nwstats.formula, where the default includes those statistics in the network model formation formula specified in the original call to netest.

The duration plot shows the average age of existing edges at each time step, up until the maximum time step requested. This is calculated with the edgelist_meanage function. The age is used as an estimator of the average duration of edges in the equilibrium state.

The dissolution plot shows the proportion of the extant ties that are dissolved at each time step, up until the maximum time step requested. Typically, the proportion of ties that are dissolved is the reciprocal of the mean relational duration. This plot thus contains similar information to that in the duration plot, but should reach its expected value more quickly, since it is not subject to censoring.

The plots.joined argument will control whether the statistics in the formation plot are joined in one plot or plotted separately. The default is based on the number of network statistics requested. The layout of the separate plots within the larger plot window is also based on the number of statistics.

See Also

netdx

Examples

# NOT RUN {
# Network initialization and model parameterization
nw <- network_initialize(n = 100)
nw <- set_vertex_attribute(nw, "sex", rbinom(100, 1, 0.5))
formation <- ~edges + nodematch("sex")
target.stats <- c(50, 40)
coef.diss <- dissolution_coefs(dissolution = ~offset(edges), duration = 50)

# Estimate the model
est <- netest(nw, formation, target.stats, coef.diss, verbose = FALSE)

# Static diagnostics
dx1 <- netdx(est, nsims = 1e4, dynamic = FALSE,
             nwstats.formula = ~edges + meandeg + concurrent +
                                nodefactor("sex", levels = NULL) +
                                nodematch("sex"))
dx1

# Plot diagnostics
plot(dx1)
plot(dx1, stats = c("edges", "concurrent"), mean.col = "black",
     sim.lines = TRUE, plots.joined = FALSE)
plot(dx1, stats = "edges", method = "b",
     col = "seagreen3", grid = TRUE)

# Dynamic diagnostics
dx2 <- netdx(est, nsims = 10, nsteps = 500,
             nwstats.formula = ~edges + meandeg + concurrent +
                                nodefactor("sex", levels = NULL) +
                                nodematch("sex"))
dx2

# Formation statistics plots, joined and separate
plot(dx2, grid = TRUE)
plot(dx2, type = "formation", plots.joined = TRUE)
plot(dx2, type = "formation", sims = 1, plots.joined = TRUE,
     qnts = FALSE, sim.lines = TRUE, mean.line = FALSE)
plot(dx2, type = "formation", plots.joined = FALSE,
     stats = c("edges", "concurrent"), grid = TRUE)

plot(dx2, method = "b", col = "bisque", grid = TRUE)
plot(dx2, method = "b", stats = "meandeg", col = "dodgerblue")

# Duration statistics plot
plot(dx2, type = "duration", mean.col = "black", grid = TRUE)
plot(dx2, type = "duration", sims = 10, mean.line = FALSE, sim.line = TRUE,
     sim.col = "steelblue", sim.lwd = 3, targ.lty = 1, targ.lwd = 0.5)

# Dissolution statistics plot
plot(dx2, type = "dissolution", mean.col = "black", grid = TRUE)
plot(dx2, type = "dissolution", method = "b", col = "pink1")
# }
# NOT RUN {
# }