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...

When it comes to measuring inflation persistence, a common practice in empirical research is to estimate univariate autoregressive moving average (ARMA) time series models and measure persistence as the sum of the estimated AR coefficients. We examine four potential sources of lag dynamics in inflation: the evolution of policymakers‟ willingness to stabilize output, shifts in the mean inflation...

In this paper the boundaries of several families of (time-invariant) ARMA models and corresponding linear state space models are described. The topology of pointwise convergence of the Markov parameters is used.

This paper addresses the problem of fitting a known distribution to the innovation distribution in a class of stationary and ergodic time series models. The asymptotic null distribution of the usual Kolmogorov–Smirnov test based on the residuals generally depends on the underlying model parameters and the error distribution. To overcome the dependence on the underlying model parameters, we prop...

Ten candidate models of the Auto-Regressive Moving Average (ARMA) family are investigated for representing and forecasting monthly and ten-day streamflow in three Indian rivers. The best models for forecasting and representation of data are selected by using the criteria of Minimum Mean Square Error (MMSE) and Maximum Likelihood (ML) respectively. The selected models are validated for significa...

The challenge of predicting future values of a time series covers a variety of disciplines. The fundamental problem of selecting the order and identifying the time varying parameters of an autoregressive moving average model (ARMA) concerns many important fields of interest such as linear prediction, system identification and spectral analysis. Recent research activities in forecasting with art...

When modeling time series data using autoregressive-moving average processes, it is a common practice to presume that the residuals are normally distributed. However, sometimes we encounter non-normal residuals and asymmetry of data marginal distribution. Despite widespread use of pure autoregressive processes for modeling non-normal time series, the autoregressive-moving average models have le...

the artificial accelerograms have been developed for assessing the dynamic response ofstructures. considering seismological properties of the site are necessary for the best simulation ofaccelerograms. the real recorded accelergrams for simulating earthquake phenomenon are used in thearma model. this is due to the fact that the arma model can be considered more advantageous than theothers.in th...