Analysis of covariance under inverse Gaussian model

Mohammad Reza Meshkani, Afshin Fallah and Amir Kavousi

Journal of Applied Statistics, 2014, vol. 41, issue 6, 1189-1202

Abstract: This paper considers the problem of analysis of covariance (ANCOVA) under the assumption of inverse Gaussian distribution for response variable. We develop the essential methodology for estimating the model parameters via maximum likelihood method. The general form of the maximum likelihood estimator is obtained in color closed form. Adjusted treatment effects and adjusted covariate effects are given, too. We also provide the asymptotic distribution of the proposed estimators. A simulation study and a real world application are also performed to illustrate and evaluate the proposed methodology.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:41:y:2014:i:6:p:1189-1202

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DOI: 10.1080/02664763.2013.862222

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