We discuss the existence and uniqueness of stationary ergodic nonlinear autoregressive processes when exogenous regressors are incorporated into dynamic. To this end, we consider convergence backward iterations dependent random maps. In particular, give a new result classical condition contraction on average is replaced with in conditional expectation. Under some conditions, also dependence pro...

In this paper we propose the Gaussian Dynamic Bayesian Smooth Transition Autoregressive (DBSTAR) models for nonlinear autoregressive time series processes as alternative to both the classical Smooth Transition Autoregressive (STAR) models of Chan and Tong (1986) and the computational Bayesian STAR (CBSTAR) models of Lopes and Salazar (2005). The DBSTAR models are autoregressive formulations of ...

Normal residual is one of the usual assumptions of autoregressive models but in practice sometimes we are faced with non-negative residuals case. In this paper we consider some autoregressive models with non-negative residuals as competing models and we have derived the maximum likelihood estimators of parameters based on the modified approach and EM algorithm for the competing models. Also,...

This article presents a new class of constrained and specialized Auto-Regressive (AR) processes. They are derived from lattice filters where some reflection coefficients are forced to zero at a priori locations. Optimizing the filter topology allows to build parametric spectral models that have a greater number of poles than the number of parameters needed to describe their location. These NUT ...

The Third Meeting of the Federation of European Societies of Neuropsychology (ESN) took place at the Congress Centre in Basel, Switzerland, from 7–9 September 2011. The theme of this meeting, which assembled more than 400 clinicians and researchers from many European countries as well as from North America, Asia and Australia, was ‘Neuropsychology across the Lifespan’. This theme gave the oppor...

Music genre classification systems are normally build as a feature extraction module followed by a classifier. The features are often short-time features with time frames of 10-30ms, although several characteristics of music require larger time scales. Thus, larger time frames are needed to take informative decisions about musical genre. For the MIREX music genre contest several authors derive ...

in this article using autoregressive (ar), autoregressive conditional heteroskedasticity (arch), generalized autoregressive conditional heteroskedasticity (garch) models we assess the weekend effect and also compare the trading patterns of individual and legal investors during 1381-1385 in tehran stock exchange. our findings suggest that weekend effect exists in tehran stock exchanges which are...

This paper analyzes whether a wealth of information contained in 126 monthly series used by large-scale Bayesian Vector Autoregressive (LBVAR) models, as well as Factor Augmented Vector Autoregressive (FAVAR) models, either Bayesian or classical, can prove to be more useful in forecasting real house price growth rate of the nine census divisions of the US, compared to the small-scale VAR models...

agriculture as one of the major economic sectors of iran, has an important role in gross domestic production by providing about 14% of gdp. this study attempts to forecast the value of the agriculture gdp using periodic autoregressive model (par), as the new seasonal time series techniques. to address this aim, the quarterly data were collected from march 1988 to july 1989. the collected data w...