EurekaMag.com logo
+ Site Statistics
References:
53,214,146
Abstracts:
29,074,682
+ Search Articles
+ Subscribe to Site Feeds
EurekaMag Most Shared ContentMost Shared
EurekaMag PDF Full Text ContentPDF Full Text
+ PDF Full Text
Request PDF Full TextRequest PDF Full Text
+ Follow Us
Follow on FacebookFollow on Facebook
Follow on TwitterFollow on Twitter
Follow on Google+Follow on Google+
Follow on LinkedInFollow on LinkedIn

+ Translate

Parameter and quantile estimation for the distributions of failure strength of structural lumber


Forest products journal 47(4): 80-88
Parameter and quantile estimation for the distributions of failure strength of structural lumber
Estimating various characteristics, such as selected quartiles or the parameters, of a probability distribution of structural lumber failure strength is critical to quality control during manufacturing operations and for reliability-based structural design. This paper presents and compares the performances (in terms of bias and root mean square error) of several alternative estimation methods when censored strength data are used in the statistical estimation process. This study concludes that the method of maximum likelihood is nearly universally superior to a regression method that appears to be in wide use in the lumber industry. Recommendations are made about the use of alternative strategies for implementing the maximum likelihood method. The results of this work will be valuable when selecting the best estimation method for a particular set of circumstances. The results also establish the foundation for a computer program that will use a rule-based expert system to facilitate the estimation process.

(PDF 0-2 workdays service: $29.90)

Accession: 002914983



Related references

Estimation of lower tail quantiles of Weibull probability distributions for lumber strength. Forest products journal 48(1): 96-101, 1998

Differences of tensile strength distributions between mechanically high-grade and low-grade Japanese larch lumber III: effect of knot restriction on the strength of lumber. Journal of Wood Science 46(2): 95-101, 2000

Quantile maximum likelihood estimation of response time distributions. Psychonomic Bulletin & Review 9(2): 394-401, 2002

Modeling distributions of air pollutant concentrations ii. estimation of one and two parameter statistical distributions. Atmospheric Environment 20(12): 2435-2448, 1986

Strength properties of finger-jointed lumber for structural use I. Bending and tensile strength of sugi finger-jointed lumber. Mokuzai Gakkaishi = Journal of the Japan Wood Research Society 37(3): 194-199, 1991

Some bivariate distributions for modeling the strength properties of lumber. Research Paper Forest Products Laboratory, USDA Forest Service (FPL-RP-575): i + 11 pp., 1999

Strength distribution of timber structures: measured variation of the cross sectional strength of structural lumber. Rapport, Afdelingen for Baerende Konstruktioner, Danmarks Tekniske Hoejskole (R114): 73, 1979

Evaluation of simple quantile estimation functions for modeling forest diameter distributions in even-aged stands of interior Douglas-fir. Canadian Journal Of Forest Research. 23(11): 2376-2382, 1993

Nonparametric quantile estimation with correlated failure time data. Lifetime Data Analysis 9(4): 357-371, 2004

The effect of sample size on parameter estimation for doubly censored lumber data. Time dependent failure mechanisms and assessment methodologies Proceedings of the 35th meeting of the Mechanical failures prevention group, National Bureau of Standards, Gaithersburg, Maryland, April 20-22, 1982: 91-99, 1982