Publication Type

Book Chapter

Publication Date

1-2013

Abstract

The conditional independence assumption is commonly used in multivariate mixture models in behavioral research. We propose an exponential tilt model to analyze data from a multivariate mixture distribution with conditionally independent components. In this model, the log ratio of the density functions of the components is modeled as a quadratic function in the observations. There are a number of advantages in this approach. First, except for the exponential tilt assumption, the marginal distributions of the observations can be completely arbitrary. Second, unlike some previous methods, which require the multivariate data to be discrete, modeling can be performed based on the original data.

Keywords

Empirical likelihood, Exponential tilting, Repeated measures, Mixture distribution, Multivariate

Discipline

Economics

Research Areas

Econometrics

First Page

371

Last Page

392

ISBN

9783319224039

Publisher

Springer

City or Country

Switzerland

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org./10.1007/978-3-319-22404-6_21

Included in

Economics Commons

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