Parameter estimation in the exponential distribution, confidence intervals and a monte carlo study for a goodness of fit test

1972 ◽  
Vol 13 (3) ◽  
pp. 225-246 ◽  
Author(s):  
R. M. J. Heuts
Keyword(s):  
Monte Carlo ◽  
Parameter Estimation ◽  
Exponential Distribution ◽  
Confidence Intervals ◽  
Goodness Of Fit ◽  
Monte Carlo Study ◽  
Goodness Of Fit Test

scholarly journals A simple non-parametric goodness-of-fit test for elliptical copulas

2017 ◽  
Vol 5 (1) ◽  
pp. 330-353 ◽  
Author(s):  
Miriam Jaser ◽  
Stephan Haug ◽  
Aleksey Min
Keyword(s):  
Monte Carlo ◽  
Goodness Of Fit ◽  
Monte Carlo Study ◽  
Goodness Of Fit Test ◽  
Kendall’S Tau ◽  
Kendall's Tau ◽  
Nominal Level ◽  
Empirical Application ◽  
Non Parametric

AbstractIn this paper, we propose a simple non-parametric goodness-of-fit test for elliptical copulas of any dimension. It is based on the equality of Kendall’s tau and Blomqvist’s beta for all bivariate margins. Nominal level and power of the proposed test are investigated in a Monte Carlo study. An empirical application illustrates our goodness-of-fit test at work.

A test for fuzzy exponentiality based on Kullback-Leibler information

2021 ◽  
pp. 1-8
Author(s):  
Lingtao Kong
Keyword(s):  
Biological Sciences ◽  
Monte Carlo ◽  
Goodness Of Fit ◽  
Experimental Studies ◽  
Real Data ◽  
Test Statistics ◽  
Test Statistic ◽  
Goodness Of Fit Test ◽  
Higher Power ◽  
Leibler Information

The exponential distribution has been widely used in engineering, social and biological sciences. In this paper, we propose a new goodness-of-fit test for fuzzy exponentiality using α-pessimistic value. The test statistics is established based on Kullback-Leibler information. By using Monte Carlo method, we obtain the empirical critical points of the test statistic at four different significant levels. To evaluate the performance of the proposed test, we compare it with four commonly used tests through some simulations. Experimental studies show that the proposed test has higher power than other tests in most cases. In particular, for the uniform and linear failure rate alternatives, our method has the best performance. A real data example is investigated to show the application of our test.

A monte carlo method for foutz's goodness-of-fit test

1988 ◽  
Vol 29 (4) ◽  
pp. 309-316 ◽  
Author(s):  
Myoungshic Jhun ◽  
Pui Lam Leung
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Goodness Of Fit ◽  
Goodness Of Fit Test
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