A field method for calculation of Weibull distribution shape and scale parameters

Author(s):  
Gilberto Jorge Haviaras ◽  
Gilberto Francisco Martha De Souza
Author(s):  
Md Salauddin ◽  
John O'Sullivan ◽  
Soroush Abolfathi ◽  
Shudhi Dong ◽  
Jonathan Pearson

Maximum wave overtopping volumes on sea defences are an indicator for identifying risks to people and properties from wave hazards. The probability distribution of individual overtopping volumes can generally be described by a two-parameter Weibull distribution function (shape and scale parameters). Therefore, the reliable prediction of maximum individual wave overtopping volumes at coastal structures relies on an accurate estimation of the shape factor in the Weibull distribution. This study contributes to an improved understanding of the distribution of individual wave overtopping volumes at sloping structures by analysing the wave-by-wave overtopping volumes obtained from physical model experiments on a 1V:2H sloped impermeable structure with a permeable shingle foreshore of slope 1V:20H. Measurements of the permeable shingle foreshore were benchmarked against those from an identical experimental set-up with a smooth impermeable foreshore (1V:20H) of the same geometry. Results from both experimental set-ups were compared to commonly used empirical formulations, underpinned by the assumption that an impermeable foreshore exists in front of the sea structure. The effect on the shape factor in the Weibull distribution of incident wave steepness, relative crest freeboard, probability of overtopping waves and discharge are examined to determine the variation of individual overtopping volumes with respect to these key parameters. A key finding from the study is that no major differences in Weibull distribution shape parameter were observed for the tested impermeable and permeable sloped foreshores. Existing empirical formulae were also shown to predict reasonably well the Weibull distribution shape parameter, b, at sloping structures with both impermeable and permeable slopes.


2014 ◽  
Vol 53 (3) ◽  
pp. 660-675 ◽  
Author(s):  
Megan C. Kirchmeier ◽  
David J. Lorenz ◽  
Daniel J. Vimont

AbstractThis study presents the development of a method to statistically downscale daily wind speed variations in an extended Great Lakes region. A probabilistic approach is used, predicting a daily-varying probability density function (PDF) of local-scale daily wind speed conditioned on large-scale daily wind speed predictors. Advantages of a probabilistic method are that it provides realistic information on the variance and extremes in addition to information on the mean, it allows the autocorrelation of downscaled realizations to be tuned to match the autocorrelation of local-scale observations, and it allows flexibility in the use of the final downscaled product. Much attention is given to fitting the proper functional form of the PDF by investigating the observed local-scale wind speed distribution (predictand) as a function of the decile of the large-scale wind (predictor). It is found that the local-scale standard deviation and the local-scale shape parameter (from a gamma distribution) are nonconstant functions of the large-scale predictor. As such, a vector generalized linear model is developed to relate the large-scale and local-scale wind speeds. Maximum likelihood and cross validation are used to fit local-scale gamma distribution shape and scale parameters to the large-scale wind speed. The result is a daily-varying probability distribution of local-scale wind speed, conditioned on the large-scale wind speed.


2011 ◽  
Vol 291-294 ◽  
pp. 2195-2198 ◽  
Author(s):  
Xian Zhao Xu ◽  
Hong Liang Lou ◽  
Xing Lin Li

When sequential sampling method based on MTTF is applied to weibull distribution, shape parameter is considered to be fixed. But, shape parameter in criterions or references is different from that in practice. According to sequential sampling method, with the shape parameter changing, changes of acceptance probability and rejection probability are studied. Finally, the result of simulation evaluating shows that the method of sequential sampling method is feasible and reasonable.


Author(s):  
Kai Huang ◽  
Jie Mi

This paper studies the frequentist inference about the shape and scale parameters of the two-parameter Weibull distribution using upper record values. The exact sampling distribution of the MLE of the shape parameter is derived. The asymptotic normality of the MLEs of both parameters are obtained. Based on these results this paper proposes various confidence intervals of the two parameters. Assuming one parameter is known certain testing procedures are proposed. Furthermore, approximate prediction interval for the immediately consequent record value is derived too. Conclusions are made based on intensive simulations.


2011 ◽  
Vol 2011 ◽  
pp. 1-12
Author(s):  
Eun-Joo Lee ◽  
Dane Walker ◽  
David Elliott ◽  
Katlyn Mathy ◽  
Seung-Hwan Lee

The Weibull distribution is widely used in the parametric analysis of lifetime data. In place of the Weibull distribution, it is often more convenient to work with the equivalent extreme value distribution, which is the logarithm of the Weibull distribution. The main advantage in working with the extreme value distribution is that unlike the Weibull distribution, the extreme value distribution has location and scale parameters. This paper is devoted to a discussion of statistical inferences for the extreme value distribution with censored data. Numerical simulations are performed to examine the finite sample behaviors of the estimators of the parameters. These procedures are then applied to real-world data.


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