There are many parameters which are very difficult to calibrate in the threshold autoregressive prediction model for nonlinear time series. The threshold value, autoregressive coefficients, and the delay time are key parameters in the threshold autoregressive prediction model. To improve prediction precision and reduce the uncertainties in the determination of the above parameters, a new DNA de...

This paper poses the problem of model order determination of an autoregressive (AR) pro ess within a Bayesian framework. Several original hierar hi al prior models are proposed that allow for the stability of the model to be enfor ed and a ount for a possible unknown initial state. Obtaining the posterior model order probabilities requires integration of the resulting posterior distribution, an...

In the study, we discussed the generalized autoregressive conditional heteroskedasticity model and enhanced it with wavelet transform to evaluate the daily returns for 1/4/2002-30/12/2011 period in Brent oil market. We proposed discrete wavelet transform generalized autoregressive conditional heteroskedasticity model to increase the forecasting performance of the generalized autoregressive cond...

The classical method of process capability analysis necessarily assumes that collected data are independent; nonetheless, some processes such as biological and chemical processes are autocorrelated and violate the independency assumption. Many processes exhibit a certain degree of correlation and can be treated by autoregressive models among which the autoregressive model of order one (AR (1)) ...

introduction: agriculture as one of old sectors of economy has been important role in the supply food for peoples and raw materials. globalization causes rapid growth of world trade and reduces information and communications costs. globalization and rapid growth of trade increases the potential benefits of trade for agriculture from various aspects. the potential benefits of trade for agricultu...

In this paper we examine the forecast accuracy of four univariate time series models for 47 macroeconomic variables of the G7 economies. The models considered are the linear autoregressive model, the smooth transition autoregressive model, and two neural network models. The two neural network models are different because they are specified using two different techniques. Forecast accuracy is as...