Abstract The periodic behavior of real data can be manifested in the time series or its characteristics. One characteristics that often manifests is sample autocovariance function. In this case, periodically correlated (PC) considered. main models exhibits PC property autoregressive (PARMA) model considered as generalization classical moving average (ARMA) process. However, when one considers d...

Inspired by Conway’s surreal numbers, we study real closed fields whose value group is isomorphic to the additive reduct of field. We call such omega-fields and prove that any omega-field bounded Hahn series with coefficients admits an exponential function making it into a model theory also consider relative versions more general coefficient fields.

Computer experiments are utilized as a popular tool of studying the relationship between responses and the factors that affect them. They are widely used in scientific researches and applications. Dynamic computer experiments refer to computer experiments with time-series responses. Different dynamic computer models have been proposed to emulate the relationship between the time-series response...

In this paper the performance of different multi-rate schemes in Direct Sequence Code Division Multiple Access (DS/CDMA) systems are evaluated. The assumptions are random code sequences and AWGN channel. We have looked at four different solutions: different spreading factors, mixed modulation, parallel channels and Parallel Combinatory Spread Spectrum (PC/SS). Our conclusion is that parallel ch...

The microscopic electric polarization in terms of the dipole-dipole polarizability and its second hyperpolarizability of aligned films and ropes of carbon nanotubes has been studied theoretically by a point-dipole interaction model. The results show clearly the influence of intertube interactions on the microscopic polarization demonstrating the sensitivity of the electronic structure of carbon...

We consider the use of generalized additive models with correlated errors for analysing trends in time series. The trend is represented as a smoothing spline so that it can be extrapolated. A method is proposed for choosing the smoothing parameter. It is based on the ability to predict a short term into the future. The choice not only addresses the purpose in hand, but also performs very well, ...

In this paper, we propose a bounded influence estimation (BIE) and outlier detection procedure for GARCH models. Previous studies show that maximum likelihood estimates of GARCH models are sensitive to outliers and financial time series present a heavy tail due to outliers. The proposed BIE limits the influence of a small subset of the data and is asymptotically normal. Its robustness against o...

Introduction: Ultra-high molecular weight polyethylene (UHMWPE) has been ubiquitous as a bearing surface material in joint arthroplasty for decades. Yet, its vulnerability to wear and fatigue failure following oxidation remains a major concern. Although significant gains in wear reduction and oxidation resistance have been achieved with a combination of cross-linking and heat treatments, these ...

Abstract—The aim of this paper is to select the most accurate forecasting method for predicting the future values of the unemployment rate in selected European countries. In order to do so, several forecasting techniques adequate for forecasting time series with trend component, were selected, namely: double exponential smoothing (also known as Holt`s method) and Holt-Winters` method which acco...

In order to study the inheritance of some traits related to grain yield in drought stress conditions in bread wheat (Triticum aestivum L.), F2, F3 and F4 generations derived from a Kharchia (tolerant) × Gaspard (susceptible) cross and their parents were used separately in a complete randomized block design with two replications. Stem length, biological yield, main spike straw weight, total spik...