RecordLinkage (version 0.4-10)

mygllm: Generalized Log-Linear Fitting

Description

Fits a log-linear model for collapsed contingency tables.

Usage

mygllm(y, s, X, maxit = 1000, tol = 1e-05, E = rep(1, length(s)))

Arguments

y

Vector of observed cell frequencies.

s

Scatter matrix. s[i] is the cell in the observed array that corresponds to cell i in the full array.

X

Design matrix.

maxit

Maximum number of iterations.

tol

Convergence parameter.

E

Full contingency table. Should be initialized with either ones or a priori estimates.

Value

Estimated full contingency table.

Details

This is an implementation and extension of the algorithm published by Haber (1984). It also incorporates ideas of David Duffy (see references).

A priori estimates of the full contingency table can be given as start values by argument E. This can reduce execution time significantly.

References

Michael Haber, Algorithm AS 207: Fitting a General Log-Linear Model, in: Applied Statistics 33 (1984) No. 3, 358--362.

David Duffy: gllm: Generalised log-linear model. R package version 0.31. see http://www.qimr.edu.au/davidD/#loglin

See Also

emWeights, which makes use of log-linear fitting for weight calculation.