emgllmfitter {gllm} | R Documentation |
Generalized log-linear modelling by EM and iterative proportional fitting
Description
Fits log-linear models for incomplete contingency tables, via an EM approach.
Usage
emgllmfitter(y,s,X,maxit,tol)
Arguments
y |
is the observed contingency table. |
s |
is a vector of indices, one for each cell of the full (unobserved)
contingency table, representing the appropriate cell of |
X |
is the design matrix. |
maxit |
is the number of EM iterations. |
tol |
is the convergence criterion for the LR criterion. |
Details
The call to Andreas Borg's C code that fits the model by EM/IPF. The algorithm follows the approach in Haber (1984).
Value
A list with components:
y |
the observed table |
ji |
s, the scatter vector |
c |
the design matrix |
istop |
maximum EM iterations |
conv |
the convergence tolerance |
e |
expected counts for the full (unobserved) table |
ni |
nrow(X) |
nj |
length(y) |
nk |
ncol(X)-1 |
f |
expected counts |
References
Haber M (1984). AS207: Fitting a general log-linear model. Appl Statist 33:358-362.