In this paper we are concerned with the distributional difference of forward swap rates between the lognormal forward–Libor model (LFM) or “Libor market model” and the lognormal forward-swap model (LSM) or “swap market model”, the two fundamental models for interest-rate derivatives. To measure this distributional difference, we resort to a “metric” in the space of distributions, the well known...

Traditional statistical estimates Ŝ(x1, . . . , xn) for different statistical characteristics S (such as mean, variance, etc.) implicitly assume that we know the sample values x1, . . . , xn exactly. In practice, the sample values x̃i come from measurements and are, therefore, in general, different from the actual (unknown) values xi of the corresponding quantities. Sometimes, we know the probab...

Mike Thelwall, Statistical Cybermetrics Research Group, University of Wolverhampton, UK. Many different citation-based indicators are used by researchers and research evaluators to help evaluate the impact of scholarly outputs. Although the appropriateness of individual citation indicators depends in part on the statistical properties of citation counts, there is no universally agreed best-fitt...

Establishing and characterizing exposure-biomarker relationships is an important problem in molecular epidemiology. The problem is difficult due to several complicating features, namely, the biomarker response is a nonlinear function of exposure and unknown parameters; variation in exposure and biomarker levels occurs both within and between subjects; and errors tend to be heteroscedastic. To o...

We investigate two important properties of real data: diversity and log-normality. Log-normality accounts for the fact that data follow the lognormal distribution, whereas diversity measures variations of the attributes in the data. To our knowledge, these two inherent properties have not been paid much attention from the machine learning community, especially from the topic modeling community....