The estimation of dynamic factor models for large sets of variables has attracted considerable attention recently, due to the increased availability of large datasets. In this paper we propose a new methodology for estimating factors from large datasets based on state space models, discuss its theoretical properties and compare its performance with that of two alternative estimation approaches ...

todays, dynamic models are supposed as the most important tools in erosion and sediment phenomenadue to their complexities and existence of many affecting factors. towards, the present study wasconducted in the kojour watershed for daily sediment modeling using daily rainfall, discharge andsediment during 2007 to 2010. the modeling process was carried out all data and the monthly andseasonally ...

the present research is concerned with the determination of ductility, over-strength and response modification factors of coupled steel shear wall frames. three structural models with various numbers of stories, bay width and coupling beam height were analyzed using static pushover and incremental nonlinear dynamic analyses. the ductility, over-strength and response modification factors for the...

We discuss the development of dynamic factor models for multivariate nancial time series, and the incorporation of stochastic volatility components for latent factor processes. Bayesian inference and computation is developed and explored in a study of the dynamic factor structure of daily spot exchange rates for a selection of international currencies. The models are direct generalisations of u...

Factor models are used to condense high dimensional data consisting of many variables into a much smaller number of factors. Here we present an introductory survey to factor models for time series, where the factors represent the comovement between the single time series. Principal component analysis, linear dynamic factor models with idiosyncratic noise and generalized linear dynamic factor mo...

In this paper, to cope with the stochastic dynamic (or multi-period) problem, two new quadratic assignment-based mathematical models corresponding to the dynamic and static approaches are developed. The product demands are presumed to be dependent uncertain variables with normal distribution having known expectation, variance, and covariance that change from one period to the next one, randomly...