This paper looks at the problem of system identification from non-uniformly sampled input-output data. It describes how refined instrumental variable estimators can be derived to directly identify the parameters of continuous-time output error and Box-Jenkins transfer function models from irregularly sampled data. Monte Carlo simulation analysis is used to illustrate the properties of the propo...

journal of accounting advances (j.a.a) vol. 5, no. 1, 2013, ser. 64/3     extended abstract   a study of characteristics of interim cash flow series and their proxies and the ability to predict them            dr. m. a. aghaei              v. ahmadian             f. daviran tarbiat modares university   introduction the predicting of annual and interim cash flows from operations is one of the mo...

Time series forecasting plays a significant role in numerous applications, including but not limited to, industrial planning, water consumption, medical domains, exchange rates and consumer price index. The main problem is insufficient accuracy. present study proposes hybrid methods to address this need. proposed method includes three models. first model based on the autoregressive integrated m...

The aim of this paper is to prove the validity of an alternative prediction technique to another classical one, which is Box-Jenkins methodology, in order to produce multivariate prediction. In particular, one-step ahead forecasts will be obtained for two time series: thermic and hydraulic power production. These forecasts are based on the past values of those series.