Simulates a random latent matrix Z given its expectation, dyadic correlation
and censored binary nomination data
Usage
rZ_cbin_fc(Z, EZ, rho, Y, odmax, odobs)
Arguments
- Z
a square matrix, the current value of Z
- EZ
expected value of Z
- rho
dyadic correlation
- Y
square matrix of ranked nomination data
- odmax
a scalar or vector giving the maximum number of nominations for
each individual
- odobs
observed outdegree
Value
a square matrix, the new value of Z
Details
simulates Z under the constraints (1) Y\[i,j\]=1, Y\[i,k\]=0 => Z\[i,j\]>Z\[i,k\] ,
(2) Y\[i,j\]=1 => Z\[i,j\]>0 , (3) Y\[i,j\]=0 & odobs\[i\]<odmax\[i\] => Z\[i,j\]<0