A new approach to the BHEP tests for multivariate normality
Journal of Multivariate Analysis
Goodness-of-fit tests for a multivariate distribution by the empirical characteristic function
Journal of Multivariate Analysis
Journal of Multivariate Analysis
Testing goodness of fit for the distribution of errors in multivariate linear models
Journal of Multivariate Analysis
Fourier methods for testing multivariate independence
Computational Statistics & Data Analysis
A test for the two-sample problem based on empirical characteristic functions
Computational Statistics & Data Analysis
Empirical Hankel transforms and its applications to goodness-of-fit tests
Journal of Multivariate Analysis
An affine invariant multiple test procedure for assessing multivariate normality
Computational Statistics & Data Analysis
Goodness-of-fit tests in semi-linear models
Statistics and Computing
Goodness-of-fit test for stochastic volatility models
Journal of Multivariate Analysis
International Journal of Data Analysis Techniques and Strategies
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A class of goodness-of-fit tests based on the empirical characteristic function is studied. They can be applied to continuous as well as to discrete or mixed data with any arbitrary fixed dimension. The tests are consistent against any fixed alternative for suitable choices of the weight function involved in the definition of the test statistic. The bootstrap can be employed to estimate consistently the null distribution of the test statistic. The goodness of the bootstrap approximation and the power of some tests in this class for finite sample sizes are investigated by simulation.