The needs of accuracy of machines are strictly increasing for the manufacturing processes. It is costly to use high precision machine to achieve the goal. Therefore, if the forecasting of errors can be obtained from the gathered past error values, it allows the control system to compensate the errors. In this paper, the simulations of manufacturing processes are using the ARMA and ARMAX models....

non-linear time series models have become fashionable tools to describe and forecast stock market returns in recent years. a significant amount of evidence supports a negative relationship between volume and future returns. this suggests that volume could act as a suitable threshold variable in lstar and tar models. in this research, we compared the forecasting ability of lsatr and tar models w...

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...

Long intermediate AR models are used in Durbin's algorithms for ARMA estimation. The order of that long AR model is infinite in the asymptotical theory, but very high AR orders are known to give inaccurate ARMA models in practice. A theoretical derivation is given for two different finite AR orders, as a function of the sample size. The first is the AR order optimal for prediction with a purely...

Discrete time-varying autoregressive moving average (ARMA) models are used to describe realistic earthquake ground motion time histories. Both amplitude and frequency nonstationarities are incorporated in the model. An iterative Kalman filtering scheme is introduced to identify the time-varying parameters of an ARMA model from an actual earthquake record. Several model verification tests are pe...

In this research, monthly rainfall of Shiraz synoptic station from March 1971 to February 2016 was studied using different time series models by ITSM Software. Results showed that the ARMA (1,12) model based on Hannan-Rissanen method was the best model which fitted to the data. Then, to assess the verification and accuracy of the model, the monthly rainfall for 60 months (from March 2011 to Feb...