Scilab Function
Last update : 5/9/2006

sba - create the derivational BA model with arbitrary attractiveness, fitness and nonlinear attachment probability.

### Calling Sequence

  `[a,b] = sba(M0,M,T,ASSORT,K0,EXP)`

### Parameters

- `M0` : integer
- `M` : integer
- `T` : integer
- `ASSORT` : attractiveness matrix
- `K0` : fitness matrix
- `EXP` : nonlinear attachment exponent
- `a` : row vector of the numbers of the tail nodes of the graph (its size is the number of edges of the graph)
- `b` : row vector of the numbers of the head nodes of the graph (its size is the number of edges of the graph)

### Description

  Recently scholars purposed several new parameters such as attractiveness, fitness and nonlinear attachment probability in order to simulate the different statistic results of networks. People could define the matrix assort, k0, with different rules, generate the Dorogovtsev -Mendes-Samukhin (DMS) model, Krapivsky model, Bianconi-Barabasi (BB) model.

### Examples

    	assort=ones(1,10000);
    	k0=zeros(1,10000);
    	[a b]=sba(6,4,9994,assort,k0,2);

### See Also

`er` , `ws` , `ba` , `bbv` ,

### Authors

  Wubo