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bayesm (version 1.1-2)

llmnl: Evaluate Log Likelihood for Multinomial Logit Model

Description

llmnl evaluates log-likelihood for the multinomial logit model.

Usage

llmnl(y, X, beta)

Arguments

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

Value

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

concept

  • multinomial logit
  • likelihood

Warning

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

Details

Let $mu_i=X_i \beta$, 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.

References

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

See Also

createX, rmnlIndepMetrop

Examples

Run this code
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ll=llmnl(y,X,beta)

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