Unbiased estimation of Weibull modulus using linear least squares analysis—A systematic approach
Access Status
Authors
Date
2017Type
Metadata
Show full item recordCitation
Source Title
ISSN
School
Collection
Abstract
© 2016 Elsevier Ltd The wide applicability of the Weibull distribution to fields such as hydrology and materials science has led to a large number of probability estimators being proposed, in particular for the widely used technique of obtaining the Weibull modulus, m, using unweighted linear least squares (LLS) analysis. In this work a systematic approach using the Monte Carlo method has been taken to determining the optimal probability estimators for unbiased estimation of m (mean, median and mode) using the general equation F=(i-a)/(N+b) whilst simultaneously minimising the coefficient of variation for each of the average values. A wide range of a and b values were investigated within the region 0=a=1 and 1=b=1000 with the form of F=(i-a)/(N+1) being chosen as the recommend probability estimator equation due to its simplicity and relatively small coefficient of variation. Values of a as a function of N were presented for the mean, median and mode m values.
Related items
Showing items related by title, author, creator and subject.
-
Sithole, Moses M. (1997)This thesis is mainly concerned with the estimation of parameters in autoregressive models with censored data. For convenience, attention is restricted to the first-order stationary autoregressive (AR(1)) model in which ...
-
Chong, Yen N. (2001)General routing problems deal with transporting some commodities and/or travelling along the axes of a given network in some optimal manner. In the modern world such problems arise in several contexts such as distribution ...
-
Li, Tian Siong (2000)Precipitation of gibbsite from supersaturated caustic aluminate solutions has been investigated extensively due to its central role in the commercial Bayer plant, for extracting the alumina compound from bauxite. The ...