scholarly journals Monte Carlo exact goodness-of-fit tests for nonhomogeneous Poisson processes

2010 ◽  
Vol 27 (3) ◽  
pp. 329-341 ◽  
Author(s):  
Bo H. Lindqvist ◽  
Bjarte Rannestad
2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Sohail Chand ◽  
Shahid Kamal

Model criticism is an important stage of model building and thus goodness of fit tests provides a set of tools for diagnostic checking of the fitted model. Several tests are suggested in literature for diagnostic checking. These tests use autocorrelation or partial autocorrelation in the residuals to criticize the adequacy of fitted model. The main idea underlying these portmanteau tests is to identify if there is any dependence structure which is yet unexplained by the fitted model. In this paper, we suggest mixed portmanteau tests based on autocorrelation and partial autocorrelation functions of the residuals. We derived the asymptotic distribution of the mixture test and studied its size and power using Monte Carlo simulations.


Author(s):  
Seyed Mahdi Amir Jahanshahi ◽  
Arezo Habibi Rad ◽  
Vahid Fakoor

In this paper, we introduce some new goodness-of-fit tests for the Rayleigh distribution based on Jeffreys, Lin-Wong and Renyi divergence measures. Then, the new proposed tests are compared with other tests in the literature. We compare the power of considered tests for some alternative distributions whose powers are calculated by Monte Carlo simulation. Finally, we conclude that entropy-based tests have a good performance in terms of power and among them Jeffreys test is the best one.  


2012 ◽  
Vol 17 (4) ◽  
pp. 489-501
Author(s):  
Marijus Radavičius ◽  
Pavel Samusenko

. For (very) sparse nominal data, common goodness-of-fit tests usually fail. Alternative goodness-of-fit tests based on extended empirical Bayes approach and grouping are proposed and their consistency is proved. The performance of the tests is illustrated and compared with classical criteria by Monte Carlo simulations.


Technometrics ◽  
2004 ◽  
Vol 46 (3) ◽  
pp. 330-338 ◽  
Author(s):  
M Bhattacharjee ◽  
J.V Deshpande ◽  
U.V Naik-Nimbalkar

2017 ◽  
Vol 40 (2) ◽  
pp. 279-290 ◽  
Author(s):  
Mahdi Mahdizadeh ◽  
Ehsan Zamanzade

In this paper, we develop some goodness of fit tests for Rayleigh distribution based on Phi-divergence. Using Monte Carlo simulation, we compare the power of the proposed tests with some traditional goodness of fit tests including Kolmogorov-Smirnov, Anderson-Darling and Cramer von-Mises tests. The results indicate that the proposed tests perform well as compared with their competing tests in the literature. Finally, the proposed procedures are illustrated via a real data set.


2019 ◽  
Vol 18 (2) ◽  
pp. 1-20
Author(s):  
Saeed Darijani ◽  
◽  
Hojatollah Zakerzade ◽  
Hamzeh Torabi ◽  
◽  
...  

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