Fitting high-dimensional statistical models often requires the use of non-linear parameter estimation procedures. As a consequence, it is generally impossible to obtain an exact characterization of the probability distribution of the parameter estimates. This in turn implies that it is extremely challenging to quantify the uncertainty associated with a certain parameter estimate. Concretely, no...

Whereas the research of the 19th-century mathematician Augustus De Morgan in formal logic is fairly familiar to historians of mathematics, his work in probability is largely unknown to the modern reader. For this reason, few would be aware that this work contains a self-admitted error in probabilistic reasoning. This mistake is intriguing not only because it features in the work of someone who ...

An important part of statistical data analysis is hypothesis testing. For example, we know the probability distribution of the characteristics corresponding to a certain disease, we have the values of the characteristics describing a patient, and we must make a conclusion whether this patient has this disease. Traditional hypothesis testing techniques are based on the assumption that we know th...

The growth of world-wide-web (WWW) spreads its wings from an intangible quantities of web-pages to a gigantic hub of web information which gradually increases the complexity of crawling process in a search engine. A search engine handles a lot of queries from various parts of this world, and the answers of it solely depend on the knowledge that it gathers by means of crawling. The information s...

Two alternative exact characterizations of the minimum error probability of Bayesian M -ary hypothesis testing are derived. The first expression corresponds to the error probability of an induced binary hypothesis test and implies the tightness of the meta-converse bound by Polyanskiy, Poor and Verdú; the second expression is function of an information-spectrum measure and implies the tightness...

Diffusion tensor imaging (DTI) provides a powerful tool for identifying white matter (WM) alterations in clinical populations. The prevalent method for group-level analysis of DTI is statistical comparison of the diffusion tensor fractional anisotropy (FA) metric. The FA metric, however, does not capture the full orientational information contained in the diffusion tensor. For example, the FA t...

We present a web-based interactive comparison of hypothesis tests as are used in statistical model checking, providing users and tool developers with more insight into their characteristics. Parameters can be modified easily and their influence is visualized in real time; an integrated simulation engine further illustrates the behaviour of the tests. Finally, since the source code is available,...

Statistical ensembles of networks, i.e., probability spaces of all networks that are consistent with given aggregate statistics, have become instrumental in the analysis of complex networks. Their numerical and analytical study provides the foundation for the inference of topological patterns, the definition of network-analytic measures, as well as for model selection and statistical hypothesis...

We present a platform named Redhyte, short for an interactive platform for “Rapid exploration of data and hypothesis testing”. Redhyte aims to augment the conventional statistical hypothesis testing framework with data-mining techniques in a bid for more wholesome and efficient hypothesis testing. The platform is self-diagnosing (it can detect whether the user is doing a valid statistical test)...

In hypothesis testing, statistical significance is typically based on calculations involving p-values and Type I error rates. A p-value calculated from a single statistical hypothesis test can be used to determine whether there is statistically significant evidence against the null hypothesis. The upper threshold applied to the p-value in making this determination (often 5% in the scientific li...