The problem we tackle concerns forecasting time series in financial markets. AutoRegressive Moving-Average (ARMA) methods and computational intelligence have also been used to tackle this problem. We propose a novel method for time series forecasting based on a hybrid combination of ARMA and Gene Expression Programming (GEP) induced models. Time series from financial domains often encapsulate d...

BACKGROUND Aminoglycosides are a group of antimicrobial agents still the most commonly used in the treatment of life-threatening bacterial infections in human and animals. The emergence and spread of 16S rRNA methylases, which confer high-level resistance to the majority of clinically relevant aminoglycosides, constitute a major public health concern. OBJECTIVES Our goal was to evaluate the d...

In this paper, a new method of estimation of the magnitude square coherence function (MSC) by an ARMA model is proposed. The estimation is achieved by modeling the periodogram estimate of the MSC and the ARMA model has been realized by the pole-zero decomposition property of the group delay function (GDF). Its performance has been found to be superior to that of the periodogram MSC estimate in ...

Objectives To investigate the context of the ribosomal RNA methyltransferase gene armA in carbapenem-resistant global clone 2 (GC2) Acinetobacter baumannii isolates from Singapore. Methods Antibiotic resistance was determined using disc diffusion; PCR was used to identify resistance genes. Whole genome sequences were determined and contigs were assembled and ordered using PCR. Resistance regi...

In this paper, the S&P 500 stock index is studied for its time varying volatility and stylized facts. The ARMA mean equation with asymmetric power ARCH errors is used to model the series correlations and the conditional heteroscadesticity in the asset returns. The conditional distributions of the standardized residuals are assumed to be the normal distribution, the t distribution or the skew-t ...

The pourpose of this paper is to propose the Stock Market (SM) volatility estimation method based on the Higher Order Cumulant (HOC) function, and to apply it to the cases when stock market returns have a non Gaussian distribution and/or when a distribution of SM innovations is unknown. The HOC functions of the third and fourth order are used not only as a means for non Gaussian model testing b...

The behavior of hydrological processes is periodic and stochastic due to the influence climatic factors. Therefore, it crucial develop models based on their periodicity nature for prediction. Furthermore, forecasting streamflow, as one main components cycle, a primary subject. In this study, statistical method, Fuzzy C-means clustering, was used find in daily discharge time series, whereas auto...

The adequate modeling of correlated input processes is an important step in building simulation models. Modeling independent identically distributed data is well established in simulation whereas the integration of correlation is still a challenge. In this paper, ARTA processes which have been used several times for describing correlated input processes in simulation are extended by using ARMA ...

Emergence of the newly identified 16S rRNA methylases RmtA, RmtB, and ArmA in pathogenic gram-negative bacilli has been a growing concern. ArmA, which had been identified exclusively in Europe, was also found in several gram-negative pathogenic bacilli isolated in Japan, suggesting global dissemination of hazardous multiple aminoglycoside resistance genes.