In this paper we propose several goodness-of-fit tests based on robust measures of skewness and tail weight. They can be seen as generalisations of the Jarque-Bera test (Bera and Jarque, 1981) based on the classical skewness and kurtosis, and as an alternative to the approach of Moors et al. (1996) using quantiles. The power values and the robustness properties of the different tests are investigated by means of simulations and applications on real data. We conclude that MC-LR, one of our proposed tests, shows the best overall power and that it is moderately influenced by outlying values.
An important problem in statistical inference is to check the adequacy of models upon which inferenc...
A new approach of parameterization is proposed to construct a general goodness-of-fit test. It can n...
INTRODUCTION In the goodness--of--fit testing problem one is given a data set of N measured observa...
In this paper we propose a series of goodness-of-fit tests for the family of skew-normal models when...
In this thesis we introduce, implement and compare several multivariate goodness-of-fit tests. First...
Location and scale-free goodness-of-fit tests based on new orderings of skewness and kurtosis are in...
The properties of Pearson’s goodness-of-fit test, as used in density forecast evaluation, income dis...
We propose three new statistics, Z(p), C-p, and R-p for testing a p-variate (p >= 2) normal distribu...
Skew-symmetric (ss) models are semiparametric models for continuous random vectors. Starting with a ...
The robustness problem is tackled by adopting a parametric class of distributions flexible enough to...
The robustness problem is tackled by adopting a parametric class of distributions flexible enough ...
AbstractWe give the results of a comprehensive simulation study of the power properties of prominent...
Abstract—Goodness-of-fit tests are statistical procedures used to test the hypothesis H0 that a set ...
If we know the statistics of central tendency and dispersion, we still cannot nature a complete desi...
Mini Dissertation (MSc (Advanced Data Analytics))--University of Pretoria, 2023.The normality assump...
An important problem in statistical inference is to check the adequacy of models upon which inferenc...
A new approach of parameterization is proposed to construct a general goodness-of-fit test. It can n...
INTRODUCTION In the goodness--of--fit testing problem one is given a data set of N measured observa...
In this paper we propose a series of goodness-of-fit tests for the family of skew-normal models when...
In this thesis we introduce, implement and compare several multivariate goodness-of-fit tests. First...
Location and scale-free goodness-of-fit tests based on new orderings of skewness and kurtosis are in...
The properties of Pearson’s goodness-of-fit test, as used in density forecast evaluation, income dis...
We propose three new statistics, Z(p), C-p, and R-p for testing a p-variate (p >= 2) normal distribu...
Skew-symmetric (ss) models are semiparametric models for continuous random vectors. Starting with a ...
The robustness problem is tackled by adopting a parametric class of distributions flexible enough to...
The robustness problem is tackled by adopting a parametric class of distributions flexible enough ...
AbstractWe give the results of a comprehensive simulation study of the power properties of prominent...
Abstract—Goodness-of-fit tests are statistical procedures used to test the hypothesis H0 that a set ...
If we know the statistics of central tendency and dispersion, we still cannot nature a complete desi...
Mini Dissertation (MSc (Advanced Data Analytics))--University of Pretoria, 2023.The normality assump...
An important problem in statistical inference is to check the adequacy of models upon which inferenc...
A new approach of parameterization is proposed to construct a general goodness-of-fit test. It can n...
INTRODUCTION In the goodness--of--fit testing problem one is given a data set of N measured observa...