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mnlHess

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,…,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, perossichi@gmail.com.

References

For further discussion, see Chapter 3, Bayesian Statistics and Marketing by Rossi, Allenby, and McCulloch.
http://www.perossi.org/home/bsm-1

See Also

Examples

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

bayesm

Bayesian Inference for Marketing/Micro-Econometrics

v3.1-4
GPL (>= 2)
Authors
Peter Rossi <perossichi@gmail.com>
Initial release
2019-10-14

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