Discrepancy in regression estimates between log-normal and gamma: some case studies
In regression models with multiplicative error, estimation is often based on either the log-normal or the gamma model. It is well known that the gamma model with constant coefficient of variation and the log-normal model with constant variance give almost the same analysis. This article focuses on the discrepancies of the regression estimates between the two models based on real examples. It identifies that even though the variance or the coefficient of variation remains constant, but regression estimates may be different between the two models. It also identifies that for the <italic>same</italic> positive data set, the variance is constant under the log-normal model but non-constant under the gamma model. For this data set, the regression estimates are completely <italic>different</italic> between the two models. In the process, it explains the causes of discrepancies between the two models.
Year of publication: |
2012
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Authors: | Das, Rabindra Nath ; Park, Jeong-Soo |
Published in: |
Journal of Applied Statistics. - Taylor & Francis Journals, ISSN 0266-4763. - Vol. 39.2012, 1, p. 97-111
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Publisher: |
Taylor & Francis Journals |
Saved in:
Saved in favorites
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