# stochastic_matrix

0th

Percentile

##### Stochastic matrix of a graph

Retrieves the stochastic matrix of a graph of class igraph.

Keywords
graphs
##### Usage
stochastic_matrix(graph, column.wise = FALSE,
sparse = igraph_opt("sparsematrices"))
##### Arguments
graph

The input graph. Must be of class igraph.

column.wise

If FALSE, then the rows of the stochastic matrix sum up to one; otherwise it is the columns.

sparse

Logical scalar, whether to return a sparse matrix. The Matrix package is needed for sparse matrices.

##### Details

Let $M$ be an $n \times n$ adjacency matrix with real non-negative entries. Let us define $D = \textrm{diag}(\sum_{i}M_{1i}, \dots, \sum_{i}M_{ni})$

The (row) stochastic matrix is defined as $$W = D^{-1}M,$$ where it is assumed that $D$ is non-singular. Column stochastic matrices are defined in a symmetric way.

##### Value

A regular matrix or a matrix of class Matrix if a sparse argument was TRUE.

as_adj

##### Aliases
• stochastic_matrix
• get.stochastic
##### Examples
# NOT RUN {
library(Matrix)
## g is a large sparse graph
g <- sample_pa(n = 10^5, power = 2, directed = FALSE)
W <- stochastic_matrix(g, sparse=TRUE)

## a dense matrix here would probably not fit in the memory
class(W)

## may not be exactly 1, due to numerical errors
max(abs(rowSums(W))-1)

# }

Documentation reproduced from package igraph, version 1.2.3, License: GPL (>= 2)

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