ldZgbme {amen} | R Documentation |
Calculation of the log conditional density of the
latent AMEN matrix Z
given observed data Y
.
ldZgbme(Z, Y, llYZ, EZ, rho, s2 = 1)
Z |
n X n latent relational matrix following an AMEN model |
Y |
n X n observed relational matrix |
llYZ |
a vectorizable function taking two arguments, y and z. See details below. |
EZ |
n X n mean matrix for |
rho |
dyadic correlation in AMEN model for |
s2 |
residual variance in AMEN model for |
This function is used for updating dyadic pairs of
the latent variable matrix Z
based on Y
and
an AMEN model for Z
. The function llYZ
specifies
the log likelihood for each single z[i,j]
based on
y[i,j]
, that is, llYZ
gives the log probability
density (or mass function) of y[i,j]
given z[i,j]
.
a symmetric matrix where entry i,j is proportional
to the log conditional bivariate density of z[i,j],z[j,i]
.
Peter Hoff
## For (overdispersed) Poisson regression, use
llYZ<-function(y,z){ dpois(y,z,log=TRUE) }