mnlHess: Computes -Expected Hessian for Multinomial Logit

In bayesm: Bayesian Inference for Marketing/Micro-Econometrics

Computes –Expected Hessian for Multinomial Logit

Description

mnlHess computes expected Hessian (E[H]) for Multinomial Logit Model.

Usage

mnlHess(beta, y, X)

Arguments

beta	k x 1 vector of coefficients
y	n x 1 vector of choices, (1,\ldots,p)
X	n*p x k Design matrix

Details

See llmnl for information on structure of X array. Use createX to make X.

Value

k x k matrix

Warning

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

Author(s)

Peter Rossi, Anderson School, UCLA, [e-mail].

References

For further discussion, see Chapter 3, Bayesian Statistics and Marketing by Rossi, Allenby, and McCulloch.

See Also

llmnl, createX, rmnlIndepMetrop

Examples

## Not run: mnlHess(beta, y, X)

bayesm documentation built on Sept. 24, 2023, 1:07 a.m.