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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
Takes a straightforward approach to illustrating the value of the CML method for the estimation of discrete and mixed dependent variable models in Econometrics. This monograph discusses theoretical aspects of CML methods, provides an overview of developments and applications of the CML inference approach, and explains why the approach can be particularly very effective for the estimation and analysis of high-dimensional heterogeneous data. In addition, it provides a blueprint (complete with matrix notation) to apply the CML estimation technique to a wide variety of discrete and mixed dependent variable model systems.
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
Takes a straightforward approach to illustrating the value of the CML method for the estimation of discrete and mixed dependent variable models in Econometrics. This monograph discusses theoretical aspects of CML methods, provides an overview of developments and applications of the CML inference approach, and explains why the approach can be particularly very effective for the estimation and analysis of high-dimensional heterogeneous data. In addition, it provides a blueprint (complete with matrix notation) to apply the CML estimation technique to a wide variety of discrete and mixed dependent variable model systems.