Skip to Main Content
Some bivariate distributions for modeling the strength properties of lumberAuthor(s): Richard A. Johnson; James W. Evans; David W. Green
Source: (Research paper FPL ; RP-575):11 p. : ill. ; 28 cm.
Publication Series: Research Paper (RP)
Station: Forest Products Laboratory
PDF: View PDF (148 KB)
DescriptionAccurate modeling of the joint stochastic nature of the strength properties of dimension lumber is essential to the determination of reliability-based design safety factors. This report reviews the major techniques for obtaining bivariate distributions and then discusses bivariate distributions whose marginal distributions suggest they might be useful for modeling the joint distribution of two strength properties. Finally, we pick a bivariate Weibull distribution and show that we can write its likelihood function under a proof loading scheme, offering the possibility that it can be used to model the joint distribution of two properties that must each be measured using a destructive test.
- We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
- This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
CitationJohnson, Richard A.; Evans, James W.; Green, David W. Some bivariate distributions for modeling the strength properties of lumber. (Research paper FPL ; RP-575):11 p. : ill. ; 28 cm.
KeywordsLumber, Strength, Models, Variance, Distribution, Weibull distribution
- Statistical models for the distribution of modulus of elasticity and modulus of rupture in lumber with implications for reliability calculations
- Small Sample Properties of Asymptotically Efficient Estimators of the Parameters of a Bivariate Gaussian–Weibull Distribution
- Maximum likelihood estimation of the parameters of a bivariate Gaussian-Weibull distribution from machine stress-rated data
XML: View XML