Assuming a first-order auto-regressive model for the auto-correlation structure between observations, in this paper, a transformation method is first employed to eliminate the effect of auto-correlation. Then, a maximum likelihood estimator (MLE) of a step change in the parameters of the transformed model is derived and three separate EWMA control charts are used to monitor the parameters of th...

in general, energy prices, such as those of crude oil, are affected by deterministic events such as seasonal changes as well as non-deterministic events such as geopolitical events. it is the non-deterministic events which cause the prices to vary randomly and makes price prediction a difficult task. one could argue that these random changes act like noise which effects the deterministic variat...

In this paper, we are estimating the pitch of telephone speech signal. We use different types of methods such us, Burg, Covariance, Fast Fourier transform, Modified Covariance, Multiple Signal Classification (MUSIC) algorithm or Eigen vector, Multi Taper method (MTM), Welch, and Yule Auto Regressive (Yule AR) , to estimate the PSD using signal processing tool box of MATLAB. The spectrum was con...

Great Salt Lake (GSL) is the largest salt lake in the western hemisphere, the fourthlargest terminal lake in the world. The elevation of GSL has critical effect on the people who live nearby and their properties. It is crucial to build an exact model of GSL elevation time series in order to predict the GSL elevation precisely. Although some models, such as ARIMA or FARIMA (fractional auto-regre...

In this paper usefulness of time series based Auto Regressive (AR) modelling technique has been explored for identification of a person. For this purpose, time series is obtained from the contour coordinates of the ear. AR model is fitted to this time series. AR coefficients thus obtained serve as a feature vector. Recognition Rate (RR) has been found by a classifier that is based on Euclidian ...

Generative models based on deep neural networks are quite powerful in modelling natural image statistics. In particular, deep auto-regressive models provide state of the art performance, in terms of log likelihood scores, by modelling tractable densities over the image manifold. In this work, we employ a learned deep auto-regressive model as data prior for solving different inverse problems in ...

COND In order to construct a motion model for the endoscope camera that moves freely in the 3D tracheo-bronchial tree, a second order auto-regressive (AR) model is used. For a Kthorder auto-regressive model, the following equation applies: Flexible fiber-optic bronchoscopy is performed on patients who are fully awake or with light conscious sedation. The procedure can entail considerable discom...

The relationship between exports, imports and economic growth of Ethiopia has been investigated in this paper for the period 1981-2018 by using annual data from World Bank. For analysis, Vector Auto Regressive Model, Johansen co-integration analysis Granger-Causality tests were implemented. outcome reveals that there is no relation Ethiopia. Conversely, we found a strong evidence bidirectional ...