Forecasting Canadian time series with the New Keynesian model

The intelligent forecasting model of time series

Automatic forecasts of univariate time series are largely demanded in business and science. In this paper, we investigate the forecasting task for geo-referenced time series. We take into account the temporal and spatial dimension of time series to get accurate forecasting of future data. We describe two algorithms for forecasting which ARIMA models. The first is designed for seasonal data and ...

The New Keynesian Model

Forecasting economic time series with the DyFor genetic program model

Neal Wagner, Moutaz Khouja*, Zbigniew Michalewicz and Rob Roy McGregor Department of Mathematics and Computer Science, Augusta State University, Augusta, GA 30904, USA Department of Business Information Systems, University of North Carolina, Charlotte, NC 28223, USA School of Computer Science, University of Adelaide, Adelaide, SA 5005, Australia Institute of Computer Science, Polish Academy of ...

Software Aging Forecasting Using Time Series Model

With the emergence of virtualization and cloud computing technologies, several services are housed on virtualization platform. Virtualization is the technology that many cloud service providers rely on for efficient management and coordination of the resource pool. As essential services are also housed on cloud platform, it is necessary to ensure continuous availability by implementing all nece...

A New Keynesian Model with Heterogeneous Expectations

This paper introduces heterogeneous expectations into a New Keynesian model. Our primary theoretical contribution is to provide an aggregation result for a model with nominal rigidities and heterogeneous bounded rationality. We incorporate bounded rationality at the individual agent level and determine restrictions on expectations operators sufficient to imply aggregate IS and AS relations of t...