ARFIMA is a time series forecasting model, which is an improve d ARMA model, the ARFIMA model proposed in this article is d emonstrated and deduced in detail. combined with network traffi c of CERNET backbone and the ARFIMA model,the result sho ws that,compare to the ARMA model, the prediction efficiency a nd accuracy has increased significantly, and not susceptible to sa mpling.

Abstract Background Patient Reported Outcomes Measure (PROM) are commonly used in research and essential to understand the patient experience when receiving treatment. Arm Activity (ArmA) is a valid reliable self-report questionnaire for assessing passive (section A) active B) real-life arm function patients with disabling spasticity. The original English version of ArmA has been psychometrical...

In this paper an approach to on-line ARMA parameter estimation based on a pseudo-linear regression and a QR matrix decomposition is developed. The algorithm has proven to be stable and has fast convergence properties if the unknown ARMA model satisses the strictly positive real condition. The derivation of the algorithm is straightforward and the computational complexity is O(N 2), however, fas...

There have been a lot of works relating to time series analysis. In this paper, the Bayesian analysis method for ARMA model is discussed and an application example is given. Firstly, the Bayesian theoretic results about AR model and the determination approach for model order are obtained. Then, the approach are presented for Bayesian analysis of MA and ARMA models. As its application, the forec...

In this note we consider the autoregressive moving average recurrent neural network ARMA-NN(1; 1) process. We show that in contrast to the pure autoregressive process simple ARMA-NN processes exist which are not irreducible. We prove that the controllability of the linear part of the process is sufficient for irreducibility. For the irreducible process essentially the shortcut weight correspond...

Two cases of pulmonary infection due to strains of multidrug-resistant Klebsiella pneumoniae were investigated. Beta-lactamase determinants, such as bla(IMP-4) and bla(SHV-12), and the 16S rRNA methyltransferase-encoding gene armA were detected in these plasmid-bearing organisms. The integron-borne bla(IMP-4) and armA contained intervening sequences highly related to those of a Vibrio cholerae ...

The aim of this study, was to characterize the extended-spectrum-β-lactamases (ESBLs) producing clinical strains of Escherichia coli isolated between January 2009 and June 2012 from Algerian hospitals and to determine the prevalence of 16S rRNA methylase among them. Sixty-seven ESBL-producers were detected among the 239 isolates included: 52 CTX-M-15-producers, 5 CTX-M-3-producers, 5 CTX-M-1-pr...

Cardiovascular magnetic resonance (CMR) perfusion data are suitable for quantitative measurement of myocardial blood flow. The goal of perfusionCMR postprocessing is to recover tissue impulse-response from observed signalintensity curves. While several deconvolution techniques are available for this purpose, all of them use models with varying parameters for the representation of the impulse-re...

1 UNINOVA and DEE, Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa, Campus da FCT da UNL, Quinta da Torre, 2829-516 Caparica, Portugal 2 INESC ID, Rua Alves Redol, 9, 2o, 1000-029 Lisboa, Portugal 3 L2F INESC ID, Rua Alves Redol, 9, 2o, 1000-029 Lisboa, Portugal 4 Academia Militar, Rua Gomes Freire, 1150-175 Lisboa, Portugal Abstract – In this paper the modeling of Fractional ...

This paper presents a subband approach to financial time series prediction. Multivariate empirical mode decomposition MEMD is employed here for multiband representation of multichannel financial time series together. Autoregressivemoving average ARMA model is used in prediction of individual subband of any time series data. Then all the predicted subband signals are summed up to obtain the over...