Obtaining the exact and near-exact distributions of the likelihood ratio statistic to test circular symmetry through the use of characteristic functions

2013 ◽  
Vol 28 (5) ◽  
pp. 2091-2115 ◽  
Author(s):  
Filipe J. Marques ◽  
Carlos A. Coelho
2010 ◽  
Author(s):  
Filipe J. Marques ◽  
Carlos A. Coelho ◽  
Theodore E. Simos ◽  
George Psihoyios ◽  
Ch. Tsitouras

Author(s):  
Marianne Jonker ◽  
Aad Van der Vaart

AbstractIn practice, nuisance parameters in statistical models are often replaced by estimates based on an external source, for instance if estimates were published before or a second dataset is available. Next these estimates are assumed to be known when the parameter of interest is estimated, a hypothesis is tested or confidence intervals are constructed. By this assumption, the level of the test is, in general, higher than supposed and the coverage of the confidence interval is too low. In this article, we derive the asymptotic distribution of the likelihood ratio statistic if the nuisance parameters are estimated based on a dataset that is independent of the data used for estimating the parameter of interest. This distribution can be used for correctly testing hypotheses and constructing confidence intervals. Four theoretical and practical examples are given as illustration.


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