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)
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