Asymptotically Efficient Estimation of a Bivariate Gaussian–Weibull Distribution and an Introduction to the Associated Pseudo-truncated Weibull

Steve P. Verrill, James W. Evans, David E. Kretschmann and Cherilyn A. Hatfield

Communications in Statistics - Theory and Methods, 2015, vol. 44, issue 14, 2957-2975

Abstract: Two important wood properties are stiffness (modulus of elasticity or MOE) and bending strength (modulus of rupture or MOR). In the past, MOE has often been modeled as a Gaussian and MOR as a lognormal or a two or three parameter Weibull. It is well known that MOE and MOR are positively correlated. To model the simultaneous behavior of MOE and MOR for the purposes of wood system reliability calculations, we introduce a bivariate Gaussian–Weibull distribution and the associated pseudo-truncated Weibull. We use asymptotically efficient likelihood methods to obtain an estimator of the parameter vector of the bivariate Gaussian–Weibull, and then obtain the asymptotic distribution of this estimator.

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:44:y:2015:i:14:p:2957-2975

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DOI: 10.1080/03610926.2013.805626

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