# sample_last_cit

From igraph v1.0.0
by Gabor Csardi

##### Random citation graphs

`sample_last_cit`

creates a graph, where vertices age, and
gain new connections based on how long ago their last citation
happened.

- Keywords
- graphs

##### Usage

```
sample_last_cit(n, edges = 1, agebins = n/7100, pref = (1:(agebins +
1))^-3, directed = TRUE)
```last_cit(...)

sample_cit_types(n, edges = 1, types = rep(0, n), pref = rep(1,
length(types)), directed = TRUE, attr = TRUE)

cit_types(...)

sample_cit_cit_types(n, edges = 1, types = rep(0, n), pref = matrix(1,
nrow = length(types), ncol = length(types)), directed = TRUE, attr = TRUE)

cit_cit_types(...)

##### Arguments

- n
- Number of vertices.
- edges
- Number of edges per step.
- agebins
- Number of aging bins.
- pref
- Vector (
`sample_last_cit`

and`sample_cit_types`

or matrix (`sample_cit_cit_types`

) giving the (unnormalized) citation probabilities for the different vertex types. - directed
- Logical scalar, whether to generate directed networks.
- ...
- Passed to the actual constructor.
- types
- Vector of length
, the types of the vertices. Types are numbered from zero.`n`

- attr
- Logical scalar, whether to add the vertex types to the generated
graph as a vertex attribute called
.`type`

##### Details

`sample_cit_cit_types`

is a stochastic block model where the
graph is growing.

`sample_cit_types`

is similarly a growing stochastic block model,
but the probability of an edge depends on the (potentiall) cited
vertex only.

##### Value

- A new graph.

*Documentation reproduced from package igraph, version 1.0.0, License: GPL (>= 2)*

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