Simulate Z given fixed rank nomination data

Simulates a random latent matrix Z given its expectation, dyadic correlation and fixed rank nomination data

Usage

rZ_frn_fc(Z, EZ, rho, Y, YL, 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

YL

list of ranked individuals, from least to most preferred in each row

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\[i,j\]>Y\[i,k\] => Z\[i,j\]>Z\[i,k\] , (2) Y\[i,j\]>0 => Z\[i,j\]>0 , (3) Y\[i,j\]=0 & odobs\[i\]<odmax\[i\] => Z\[i,j\]<0

Author

Peter Hoff