The Stock–Watson coincident index and its subsequent extensions assume a static linear one-factor model for the component indicators. Such assumption is restrictive in practice, however, with as few as four indicators. In fact, such assumption is unnecessary if one poses the index construction problem as optimal prediction of latent monthly real GDP. This paper estimates a VAR model for latent ...

This paper investigates the forecasting accuracy of bankruptcy hazard rate models for U.S. companies over the time period 1962–1999 using both yearly and monthly observation intervals. The contribution of this paper is multiple-fold. One, using an expanded bankruptcy database we validate the superior forecasting performance of Shumway’s (2001) model as opposed to Altman (1968) and Zmijewski (19...

In this paper, we consider the temporal pattern in traffic flow time series, and implement a deep learning model for traffic flow prediction. Detrending based methods decompose original flow series into trend and residual series, in which trend describes the fixed temporal pattern in traffic flow and residual series is used for prediction. Inspired by the detrending method, we propose DeepTrend...

The temporal variations of the ionospheric critical frequency foF2 is a typical example of a time series in which deterministic variations at various time scales and nonstationary stochastic variations are involved. In a series of journal and conference papers we have obtained various modelling, prediction and forecast algorithms for foF2 variations over Europe, based on data from about 15 iono...

BACKGROUND Determining the temporal variation and forecasting the incidence of smear positive tuberculosis (TB) can play an important role in promoting the TB control program. Its results may be used as a decision-supportive tool for planning and allocating resources. The present study forecasts the incidence of smear positive TB in Iran. METHODS This a longitudinal study using monthly tuberc...

Land use and land cover (LULC) information is an important component influencing watershed modeling with regards to hydrology and water quality in the river basin. In this study, the sensitivity of the Soil and Water Assessment Tool (SWAT) model to LULC datasets with three points in time and three levels of detail was assessed in a coastal subtropical watershed located in Southeast China. The r...

Attitudes toward alternative behaviors, such as drinking soda instead of alcohol, might contribute to the prediction of young people's drinking behavior. The current study explored the associations between late adolescents' and young adults' attitudes toward alcoholic and non-alcoholic drinks and their alcohol consumption, and whether these associations were moderated by participants' sex, age ...

The effect of traffic flow prediction plays an important role in routing selection. Traditional traffic flow forecasting methods mainly include linear, nonlinear, neural network, and Time Series Analysis method. However, all of them have some shortcomings. This paper analyzes the existing algorithms on traffic flow prediction and characteristics of city traffic flow and proposes a road traffic ...

Two phase gas-liquid flow pattern in a horizontal pipeline is predicted very accurately using a newly-developed analytical relation. The pattern identification is based on one of the most widely used graphs, the Baker diagram, modified in a way that compensates for the unrealistic oversimplifications of recent works. The Kern's method of pressure drop calculation is used to obtain the frict...

this paper presents a hybrid approach to developing a short-term traffic flow prediction model. in thisapproach a primary model is synthesized based on neural networks and then the model structure is optimized throughgenetic algorithm. the proposed approach is applied to a rural highway, ghazvin-rasht road in iran. the obtainedresults are acceptable and indicate that the proposed approach can i...