Assign: Assign a certain amount of clones to each node.
In GiulioCostantini/TOMproject: Simulation of Topological Overlap

Description Usage Arguments Details Value Author(s) Examples

Assign clones to each node according to different distributions, uniform (same number of clones for each node), pwr (power function) and beta (beta distribution).

1	Assign(N, N2, method_assign = c("unif", "pwr", "beta"), pwr = 1, shape1 = .1, shape2 = 1)

`N`	Integer. Number of nodes in the original network.
`N2`	Integer. Number of nodes in the cloned network. N2 > N.
`method_assign`	Character string. One of "unif", "pwr" or "beta".
`pwr`	Numeric. The exponent. Only relevant if method_assign = "pwr".
`shape1`	Numeric. The first parameter of the beta distribution. Only relevant if method_assign = "beta".
`shape2`	Numeric. The second parameter of the beta distribution. Only relevant if method_assign = "beta".

Independent of the method chosen, each node has always at least one clone. Method "unif" just assigns the same number of clones to each node (+-1, if N2 is not multiple of N). Method "pwr" draws N equally spaced numbers from .1 to .9, takes their pwr-th power, reshuffles them and distributes the clones to the N nodes proportionally to the resulting vector. Method "pwr" with pwr = 0 is equivalent to method "unif". Method "beta" draws N random numbers from a beta distribution with parameters shape1 and shape2 and distributes the clones to the N nodes, proportionally to the resulting vector. For shape1>>1 and shape2<<1 you get a uniform distribution of clones to nodes, for shape1<<1 and shape2>>1 you get that most nodes have only one clone and a few nodes have most clones. For both methods "pwr" and "beta" rounding issues may cause the presence of few more/less clones than desired. In this case, missing clones are added randomly or clones in excess are removed randomly.

A vector of integers, indicating how many clones are assigned to each node.

Giulio Costantini

# uniform assignment
Assign(N = 10, N2 = 100, method_assign = "unif")
# very asymmetric power assignment
Assign(N = 10, N2 = 100, method_assign = "pwr", pwr = 10)
# very symmetric power assignment
Assign(N = 10, N2 = 100, method_assign = "pwr", pwr = 0.2)
# very asymmetric beta assignment
Assign(N = 10, N2 = 100, method_assign = "beta", shape1 = .1, shape2 = 1)
# very symmetric beta assignment
Assign(N = 10, N2 = 100, method_assign = "beta", shape1 = 100, shape2 = .001)