spatial-temporal modeling of air pollutants, ground-level ozone concentrations in particular, has attracted recent attention because by using spatial-temporal modeling, can analyze, interpolate or predict ozone levels at any location. in this paper we consider daily averages of troposphere ozone over tehran city. for eliminating the trend of data, a dynamic linear model is used, then some featu...

stochastic, processes can be stationary or nonstationary. they depend on the magnitude of shocks. in other words, in an auto regressive model of order one, the estimated coefficient is not constant. another finding of this paper is the relation between estimated coefficients and residuals. we also develop a catastrophe and chaos theory for change of roots from stationary to a nonstationary one ...

Simple exponential smoothing (SES) methods are the most commonly used methods in forecasting and time series analysis. However, they are generally insensitive to non-stationary structural events such as level shifts, ramp shifts, and spikes or impulses. Similar to that of outliers in stationary time series, these non-stationary events will lead to increased level of errors in the forecasting pr...

Stochastic, processes can be stationary or nonstationary. They depend on the magnitude of shocks. In other words, in an auto regressive model of order one, the estimated coefficient is not constant. Another finding of this paper is the relation between estimated coefficients and residuals. We also develop a catastrophe and chaos theory for change of roots from stationary to a nonstationary one ...