On an asymptotic goodness-of-fit test for a two-parameter gamma-distribution

1996 ◽  
Vol 81 (4) ◽  
pp. 2759-2765 ◽  
Author(s):  
Yu. V. Romantsova
Keyword(s):  
Gamma Distribution ◽  
Goodness Of Fit ◽  
Goodness Of Fit Test ◽  
Two Parameter

scholarly journals A New Goodness-of-Fit Test for the Two-Parameter Gamma Distribution

2022 ◽  
Vol 3 (1) ◽  
pp. 01-06
Author(s):  
Mbanefo S. Madukaife
Keyword(s):  
Gamma Distribution ◽  
Goodness Of Fit ◽  
Critical Values ◽  
Parameter Distribution ◽  
Goodness Of Fit Test ◽  
Gamma Distributions ◽  
Two Parameter

This paper proposes a new goodness-of-fit for the two-parameter distribution. It is based on a function of squared distances between empirical and theoretical quantiles of a set of observations being hypothesized to have come from the gamma distribution. The critical values of the proposed statistic are evaluated through extensive simulations of the unit-scaled gamma distributions and computations. The empirical powers of the statistic are obtained and compared with some well-known tests for the gamma distribution, and the results show that the proposed statistic can be recommended as a test for the gamma distribution.

scholarly journals A comparison of three parameter estimation methods of the gamma distribution of annual maximum low flow duration and deficit in the Upper Vistula catchment (Poland)

2018 ◽  
Vol 23 ◽  
pp. 00001
Author(s):  
Katarzyna Baran-Gurgul
Keyword(s):  
Gamma Distribution ◽  
Goodness Of Fit ◽  
Probability Distributions ◽  
Low Flow ◽  
Estimation Methods ◽  
Goodness Of Fit Test ◽  
Flow Duration ◽  
Distribution Parameters ◽  
Anderson Darling ◽  
Parameter Estimation Methods

Based on 30-year 24-hour flow sequences at 69 water gauging stations in the Upper Vistula catchment, it was determined that the probability distributions of the low flow duration and its maximum annual deficit can be described by the gamma distribution with the estimated parameters by the methods: MOM, the method of moments, LMOM, the method of linear moments, and MLE, the method of maximum likelihood. The stationarity of the time series was tested by the Mann-Kendall correlation using the Hamed and Rao variance correction. The low flows were defined by the SPA method, with the limit flow Q70%. The quality of the match was tested by the Anderson-Darling goodness of fit test. This test allowed accepting the gamma distribution in all analysed cases, regardless of the method used to estimate the distribution parameters, since the pv (p-values) values were greater than 5% (over 18% for Tmax and 7.5% for Vmax). The highest pv values for individual water gauging stations, as well as the highest 90% Tmax and Vmax quantiles were noted using LMOM to estimate the gamma distribution parameters. The highest 90% Tmax and Vmax quantiles were observed in the uppermost part of the studied area.

scholarly journals Probability Distribution of Rainfall in Medan

2019 ◽  
Vol 1 (2) ◽  
pp. 43-49 ◽  
Author(s):  
Elly Rosmaini
Keyword(s):  
Probability Distribution ◽  
Gamma Distribution ◽  
Goodness Of Fit ◽  
Monthly Rainfall ◽  
Rainfall Data ◽  
Goodness Of Fit Test ◽  
Normal Distributions ◽  
Lognormal Distributions ◽  
Kolmogorov Smirnov ◽  
Anderson Darling

In this paper we chose three stations in Medan City , Indonesia to estimate Monthly Rainfall Data i.e. Tuntungan, Tanjung Selamat, and Medan Selayang Stations. We took the data from 2007 to 2016. In this case fitted with Normal, Gamma, and Lognormal Distributions. To estimate parameters, we used this method. Furthermore, Kolmogorov-Smirnov and Anderson Darling tests were used the goodness-of-fit test. The Gamma and Normal Distributions is suitable for Tuntungan and Medan Selayang Stations were stated by Kolmogorov-Smirnov's test. Anderson Darling's test stated that Gamma Distribution was suitable for all stations.

The Statistical Boundary Polygon of a Two Parameter Stochastic Process

2006 ◽  
Author(s):  
Torfinn Ottesen ◽  
Jon A. Aarstein
Keyword(s):  
Convex Hull ◽  
Goodness Of Fit ◽  
Structural Integrity ◽  
Time Series Data ◽  
Extreme Values ◽  
Extreme Value Distribution ◽  
Series Data ◽  
Goodness Of Fit Test ◽  
Anderson Darling ◽  
Two Parameter

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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