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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.