dgr function

Indegree, outdegree and degree of the vertices

Computes the requested degree measure for each node in the graph.

dgr(
  graph,
  cmode = "degree",
  undirected = getOption("diffnet.undirected", FALSE),
  self = getOption("diffnet.self", FALSE),
  valued = getOption("diffnet.valued", FALSE)
)

## S3 method for class 'diffnet_degSeq'
plot(
  x,
  breaks = min(100L, nrow(x)/5),
  freq = FALSE,
  y = NULL,
  log = "xy",
  hist.args = list(),
  slice = ncol(x),
  xlab = "Degree",
  ylab = "Freq",
  ...
)

Arguments

• graph: Any class of accepted graph format (see netdiffuseR-graphs).
• cmode: Character scalar. Either "indegree", "outdegree" or "degree".
• undirected: Logical scalar. When TRUE only the lower triangle of the adjacency matrix will considered (faster).
• self: Logical scalar. When TRUE autolinks (loops, self edges) are allowed (see details).
• valued: Logical scalar. When TRUE weights will be considered. Otherwise non-zero values will be replaced by ones.
• x: An diffnet_degSeq object
• breaks: Passed to hist.
• freq: Logical scalar. When TRUE the y-axis will reflex counts, otherwise densities.
• y: Ignored
• log: Passed to plot (see par).
• hist.args: Arguments passed to hist.
• slice: Integer scalar. In the case of dynamic graphs, number of time point to plot.
• xlab: Character scalar. Passed to plot.
• ylab: Character scalar. Passed to plot.
• ...: Further arguments passed to plot.

Returns

A numeric matrix of size $n * T$. In the case of plot, returns an object of class histogram.

Examples

# Comparing degree measurements ---------------------------------------------
# Creating an undirected graph
graph <- rgraph_ba()
graph

data.frame(
   In=dgr(graph, "indegree", undirected = FALSE),
   Out=dgr(graph, "outdegree", undirected = FALSE),
   Degree=dgr(graph, "degree", undirected = FALSE)
 )

# Testing on Korean Family Planning (weighted graph) ------------------------
data(kfamilyDiffNet)
d_unvalued <- dgr(kfamilyDiffNet, valued=FALSE)
d_valued   <- dgr(kfamilyDiffNet, valued=TRUE)

any(d_valued!=d_unvalued)

# Classic Scale-free plot ---------------------------------------------------
set.seed(1122)
g <- rgraph_ba(t=1e3-1)
hist(dgr(g))

# Since by default uses logscale, here we suppress the warnings
# on points been discarded for <=0.
suppressWarnings(plot(dgr(g)))

See Also

Other statistics: bass, classify_adopters(), cumulative_adopt_count(), ego_variance(), exposure(), hazard_rate(), infection(), moran(), struct_equiv(), threshold(), vertex_covariate_dist()

Other visualizations: diffusionMap(), drawColorKey(), grid_distribution(), hazard_rate(), plot_adopters(), plot_diffnet2(), plot_diffnet(), plot_infectsuscep(), plot_threshold(), rescale_vertex_igraph()

Author(s)

George G. Vega Yon