llmnl {bayesm}R Documentation

Evaluate Log Likelihood for Multinomial Logit Model

Description

llmnl evaluates log-likelihood for the multinomial logit model.

Usage

llmnl(beta,y, X)

Arguments

beta k x 1 coefficient vector
y n x 1 vector of obs on y (1,..., p)
X n*p x k Design matrix (use createX to make)

Details

Let mu_i=X_i β, then Pr(y_i=j) = exp(mu_{i,j})/sum_kexp(mu_{i,k}).
X_i is the submatrix of X corresponding to the ith observation. X has n*p rows.

Use createX to create X.

Value

value of log-likelihood (sum of log prob of observed multinomial outcomes).

Warning

This routine is a utility routine that does not check the input arguments for proper dimensions and type.

Author(s)

Peter Rossi, Graduate School of Business, University of Chicago, Peter.Rossi@ChicagoGsb.edu.

References

For further discussion, see Bayesian Statistics and Marketing by Rossi, Allenby and McCulloch.
http://faculty.chicagogsb.edu/peter.rossi/research/bsm.html

See Also

createX, rmnlIndepMetrop

Examples

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## Not run: ll=llmnl(beta,y,X)
[Package bayesm version 2.2-2 Index]