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Forest Products Laboratory
One Gifford Pinchot Drive
Madison, WI 53726-2398
Phone: (608) 231-9200
Fax: (608) 231-9592
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Economics, Statistics and Life Cycle Analysis Research

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View the 17 publications associated with this project.

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Publications associated with this Project

Publication YearTitleDate Posted
2018A fit of a mixture of bivariate normals to lumber stiffness—strength data09/21/18
2015Asymptotically Efficient Estimation of a Bivariate Gaussian-Weibull Distribution and an Introduction to the Associated Pseudo-truncated Weibull11/12/15
2018Distributions of MOE and MOR in a full lumber population09/27/18
2020Distributions of MOE and MOR in eight mill-run lumber populations (four mills at two times)08/14/20
2019Distributions of modulus of elasticity and modulus of rupture in four mill run lumber populations09/27/19
2020Estimated probability of breakage of lumber of a fixed “grade” can vary greatly from mill to mill and time to time08/21/20
2019Forest Products Laboratory contributions to the use of Weibull distribution in wood engineering09/26/19
2016Maximum likelihood estimation of the parameters of a bivariate Gaussian-Weibull distribution from machine stress-rated data08/24/16
2015Problems with a Type of Matched Subjects Design and Analysis09/08/16
2019Procedures for estimation of Weibull parameters03/07/19
2014Reliability Implications in Wood Systems of a Bivariate Gaussian-Weibull Distribution and the Associated Univariate Pseudo-truncated Weibull09/09/14
2017Reminder about potentially serious problems with a type of blocked ANOVA analysis09/05/17
2019Simulations of nonparametric analyses of predictor sort (matched specimens) data09/05/19
2017Simulations of solid lumber strength property monitoring tests06/20/17
2017Statistical models for the distribution of modulus of elasticity and modulus of rupture in lumber with implications for reliability calculations12/07/17
2019Visual and MSR grades of lumber are not 2-parameter Weibulls and why this may matter09/06/19
2019Visual and MSR grades of lumber are not two-parameter Weibulls and why it matters (with a discussion of censored data fitting)03/06/20

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