# socialInductionWeighted: Social induction model with weights In tbonne/SocialIntegrationNet:

## Description

This function runs the social induction model of network formation (see Ilany et al. 2016), with the addition of weighted edges.

## Usage

 ```1 2``` ```socialInductionWeighted(obsNet = startingNet, Pn, Pr, Pb, En1, En2, Er1, Er2, maxE, iter) ```

## Arguments

 `obsNet` Starting network. This must be a weighted and non-directed igraph network. `Pn` Probability of forming ties with a mother's partner. `Pr` Probability of forming ties with a non mother's partner. `Pb` Probability of forming ties with mother. `En1` Alpha parameter for effort into a mother's partner. Where effort is defined by a beta distribution (0,1) using alpah and beta. `En2` Beta parameter for effort into a mother's partner. Where effort is defined by a beta distribution (0,1) using alpah and beta. `Er1` Alpha parameter for effort into a non mother's partner. Where effort is defined by a beta distribution (0,1) using alpah and beta. `Er2` Beta parameter for effort into a non mother's partner. Where effort is defined by a beta distribution (0,1) using alpah and beta. `maxE` Maximum grooming effort used to scale the beta distribution. This choice should represent an upper limit of effort. `iter` Number of iteration, where each iteration removes one node and introduces a new one.

## Examples

 ```1 2 3 4 5``` ```startingNet = erdos.renyi.game(n=10, type = c("gnm"), p.or.m = 15) E(startingNet)\$weight<-c(2,25,1,1,1,1,4,5,6,9,2,1,2,1,2) predWeightedNet<-socialInductionWeighted(startingNet, Pn=0.4,Pr=0.1,Pb=1,En1=0.1,En2=4,Er1=0.1,Er2=4,maxE=100,iter=100) plot(startingNet, edge.width=E(startingNet)\$weight) plot(predWeightedNet, edge.width=E(predWeightedNet)\$weight) ```

tbonne/SocialIntegrationNet documentation built on July 31, 2018, 4:11 a.m.