Some properties of composition operators on Hilbert spaces of Dirichlet series

In this paper, we study some properties of composition operators on Hilbert spaces of Dirichlet series, which include the Fredholmness, Hilbert-Schmidtness, spectra, cyclic and hypercyclic phenomenons, and also answer a norm question raised by Cowen and MacCluer.     

Determination of breath gas composition of lung cancer patients using gas chromatography/mass spectrometry with monolithic material sorptive extraction

A gas chromatographic–mass spectrometric method with monolithic material sorptive extraction (MMSE) pretreatment was developed to determine the breath gas composition in lung cancer patients. MonoTrap silica monolithic and hybrid adsorbent was selected as the extraction medium during MMSE, given its strong capacity to extract volatile organic compounds (VOC) from exhaled gas. Under the appropriate conditions, high extraction efficiency was achieved. Using the selected ion‐monitoring mode, the limit of detection (signal‐to‐noise ratio 3) for the benzene series was 0.012–2.172 ng L^?1. The limit of quantitation (signal‐to‐noise ratio, 10) was 0.042–7.24 ng L^?1. The linearity range of the method was 4–400 ng L^?1. Average recovery of the benzene series at lower concentrations was 65–74% (20 ng L^?1). The relative standard deviation of benzene series contents determined within the linear range of detection was <10% of the mean level determined. Our proposed method is simple, rapid and sensitive, and can be competently applied to determine the breath gas composition of lung cancer patients. Copyright © 2014 John Wiley & Sons, Ltd.     

Automatic β-expansions of formal Laurent series over finite fields

We consider β-expansions of formal Laurent series over finite fields. If the base β is a Pisot or Salem series, we prove that the β-expansion of a Laurent series α is automatic if and only if α is algebraic.     

On Applications of Quasi-Monotone Sequences and Quasi Power Increasing Sequences

In this article, we prove a general theorem dealing with an application of quasi-f-power increasing sequences and δ-quasi monotone sequences. This theorem also includes some known and new results.     

Change points in heavy‐tailed multivariate time series: Methods using precision matrices

We propose two robust data‐driven techniques for detecting network structure change points between heavy‐tailed multivariate time series for situations where both the placement and number of change points are unknown. The first technique utilizes the graphical lasso method to estimate the change points, whereas the second technique utilizes the tlasso method. The techniques not only locate the change points but also estimate an undirected graph (or precision matrix) representing the relationship between the time series within each interval created by pairs of adjacent change points. An inference procedure on the edges is used in the graphs to effectively remove false‐positive edges, which are caused by the data deviating from normality. The techniques are compared using simulated multivariate t‐distributed (heavy‐tailed) time series data and the best method is applied to two financial returns data sets of stocks and indices. The results illustrate the method's ability to determine how the dependence structure of the returns changes over time. This information could potentially be used as a tool for portfolio optimization.     

The differentiation operator in the space of uniformly convergent Dirichlet series

Continuity, compactness, the spectrum and ergodic properties of the differentiation operator are investigated, when it acts in the Fréchet space of all Dirichlet series that are uniformly convergent in all half-planes for each . The properties of the formal inverse of the differentiation are also investigated.     

On the estimation of nonlinear time series models

In the present paper, a framework for parametric estimation in nonlinear time series is developed. Strong consistency and asymptotic normality of minimum Hellinger distance estimates for a determined class of nonlinear models are investigated. The main Interest for these estimates is motivated by their robustness under perturbations as it has been emphazized in Beran [2]. The first part of the paper is devoted to the study of some probabilistic properties which ensure the existence and the optimal properties of the estimates