Great Salt Lake (GSL) is the largest salt lake in the western hemisphere, the fourthlargest terminal lake in the world. The elevation of GSL has critical effect on the people who live nearby and their properties. It is crucial to build an exact model of GSL elevation time series in order to predict the GSL elevation precisely. Although some models, such as ARIMA or FARIMA (fractional auto-regre...

Naturally ventilated tropical greenhouse is classified as a complex system because it involves with nonlinear process and multivariable system. The purpose of this study is to determine the mathematical model of NVTG climates to in order to describe and predict the dynamic behavior of temperature and humidity inside NVTG for development of its control system. The modeling of the system is divid...

In this paper, we introduce an autoregressive model which has an evolution that is driven by an exogenous pilot signal. This model shares some properties with TAR (Threshold Auto Regressive) models and STAR (Smooth Transition Auto Regressive) models. This text de nes the model, it presents an estimator for this model, and an estimator for the variance of the innovation, which is not constant in...

A two-yers longitudinal study waz conducted in 1996.the data are letated to a cohort of 317 healthy neonated(164 girls and 153 boys) randomly selected in june 1996 from the city of shiraz followed from birth to two years of age.Firstly,logistic regression model and HRY (Healy-Rashash-Yang)method were used on ten selected milestones separately.secondly, we use an auto-regressive multivariate mul...

There is a compelling need to accurately and efficiently compute option values. Existing literature shows that models based on constant stock volatilities have been widely used in option valuation. However, stock volatilities change constantly in real life situations. The introduction of the Auto Regressive Conditional Heteroskedasticity (ARCH) model and subsequently, the Generalized Auto Regre...

This paper presents a method for speech analysis/synthesis/ conversion by using sequential processing. The aims of this method are to improve the quality of synthesized speech and to convert the original speech into another speech of different characteristics. We apply the Kalman Filter for estimating the auto-regressive coefficients of ‘time varying AR model with unknown input (ARUI model)’, w...

Generative models based on deep neural networks are quite powerful in modelling natural image statistics. In particular, deep auto-regressive models provide state of the art performance, in terms of log likelihood scores, by modelling tractable densities over the image manifold. In this work, we employ a learned deep auto-regressive model as data prior for solving different inverse problems in ...