# random_walk

0th

Percentile

##### Random walk on a graph

Do a random walk. From the given start vertex, take the given number of steps, choosing an edge from the actual vertex uniformly randomly. Edge directions are observed in directed graphs (see the mode argument as well). Multiple and loop edges are also observed.

##### Usage
random_walk(graph, start, steps, mode = c("out", "in", "all"),
stuck = c("return", "error"))
##### Arguments
graph

The input graph, might be undirected or directed.

start

The start vertex.

steps

The number of steps to make.

mode

How to follow directed edges. "out" steps along the edge direction, "in" is opposite to that. "all" ignores edge directions. This argument is ignored for directed graphs.

stuck

What to do if the random walk gets stuck. "return" returns the partial walk, "error" raises an error.

##### Value

A vertex sequence containing the vertices along the walk.

• random_walk
##### Examples
# NOT RUN {
## Stationary distribution of a Markov chain
g <- make_ring(10, directed = TRUE) %u%
make_star(11, center = 11) + edge(11, 1)

ec <- eigen_centrality(g, directed = TRUE)$vector pg <- page_rank(g, damping = 0.999)$vector
w <- random_walk(g, start = 1, steps = 10000)

## These are similar, but not exactly the same
cor(table(w), ec)

## But these are (almost) the same
cor(table(w), pg)
# }

Documentation reproduced from package igraph, version 1.0.1, License: GPL (>= 2)

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