The Normalized Prediction Error, or NPE, can be used for the evaluation of the fit of AR models, which are estimated from signals that are generated by an AR process. The NPE does not only provide a measure of the time domain fit, but also of the frequency domain fit of an estimated model. Therefore, it is a measure that can very well be used for comparison of different estimates. In this paper...

Despite their theoretical limitations, ARIMA models are widely used in real-life forecasting tasks. Parzen has proposed an extension of ARIMA models: ARARMA models. ARARMA models consist of an AR model followed by an ARMA model. Following Parzen approach,-NARMA neural network are MLP, the units of which are simple non-linear ARMA-based models (-NARMA units). They are a non-linear extension of A...

Keyhole arc welding is a cost-effective process to weld thick materials. To successfully apply this process, the state of the keyhole must be accurately detected and used in feedback control. In this paper, the dynamic behavior of the plasma reflection is described using the reflection arc angle (RAA). It is found that the RAA series can be considered an autoregressive moving-average (ARMA) pro...

In industries, how to improve forecasting accuracy such as sales, shipping is an important issue. There are many researches made on this. In this paper, a hybrid method is introduced and plural methods are compared. Focusing that the equation of exponential smoothing method(ESM) is equivalent to (1,1) order ARMA model equation, new method of estimation of smoothing constant in exponential smoot...

We introduce the new time series analysis features of scikits.statsmodels. This includes descriptive statistics, statistical tests and several linear model classes, autoregressive, AR, autoregressive moving-average, ARMA, and vector autoregressive models VAR.

The 16S rRNA methyltransferase ArmA is a worldwide emerging determinant that confers high-level resistance to most clinically relevant aminoglycosides. We report here the identification and characterization of a multidrug-resistant Salmonella enterica subspecies I.4,12:i:- isolate recovered from chicken meat sampled in a supermarket on February 2009 in La Reunion, a French island in the Indian ...

Multi-rate digital processing [1] is today a well-established topic, extensively applied in communications, image and audio industry and other areas, for signal coding, adaptive or statistical processing etc. A special class of discrete random processes [2] are those obtained by passing white-noise through a linear digital filter—called Moving-Average (MA) for an Finite-Impulse-Response (FIR) f...

In this paper we introduce a robust feature extractor, dubbed as Modified Function Cepstral Coefficients (MODFCC), based on gammachirp filterbank, Relative Spectral (RASTA) and Autoregressive Moving-Average (ARMA) filter. The goal of this work is to improve the robustness of speech recognition systems in additive noise and real-time reverberant environments. In speech recognition systems Mel-Fr...

Second order properties of nearly nonstationary ARMA processes are investigated in the cases when the autoregressive polynomial equation has (i) a real root close to 1; (ii) a real root close to -1; (iii) a pair of complex roots close to the unit circle. The effect of the closeness to the unit circle of the ARMA poles on its covariance and spectral density functions is considered. The obtained ...

The attenuated ultrasound pulse is divided into two parts: a stationary basic pulse and a nonstationary attenuation pulse. A standard ARMA model is used for the basic pulse, and a nonstandard ARMA model is derived for the attenuation pulse. The maximum likelihood estimator of the attenuated ultrasound pulse, which includes a maximum likelihood attenuation estimator, is derived. The results of t...