A consistent correlation-type goodness-of-fit test;with application to the two-parameter weibull distribution

1979 ◽  
Vol 10 (3) ◽  
pp. 427-452 ◽  
Author(s):  
B. Gerlach
2016 ◽  
Vol 61 (3) ◽  
pp. 489-496
Author(s):  
Aleksander Cianciara

Abstract The paper presents the results of research aimed at verifying the hypothesis that the Weibull distribution is an appropriate statistical distribution model of microseismicity emission characteristics, namely: energy of phenomena and inter-event time. It is understood that the emission under consideration is induced by the natural rock mass fracturing. Because the recorded emission contain noise, therefore, it is subjected to an appropriate filtering. The study has been conducted using the method of statistical verification of null hypothesis that the Weibull distribution fits the empirical cumulative distribution function. As the model describing the cumulative distribution function is given in an analytical form, its verification may be performed using the Kolmogorov-Smirnov goodness-of-fit test. Interpretations by means of probabilistic methods require specifying the correct model describing the statistical distribution of data. Because in these methods measurement data are not used directly, but their statistical distributions, e.g., in the method based on the hazard analysis, or in that that uses maximum value statistics.


Author(s):  
Torfinn Ottesen ◽  
Jon A. Aarstein

The simultaneous values of tension and bending are of primary interest when checking the structural integrity of dynamic risers and umbilicals. Considering extreme checks, it is generally sufficient to check the simultaneous values along the convex hull of the extreme contour. A method for obtaining a boundary polygon that approximates the statistical extreme convex hull from time series data is described. The procedure for obtaining the extreme values from the most suitable extreme value distribution as determined by the Anderson-Darling Goodness-of-Fit test is outlined.


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