In this paper a forward–backward basis function approach for instantaneous frequency estimation of the frequency-modulated signal in noisy environment is presented. At first, a forward– backward prediction approach is applied for least squares estimation of time-varying autoregressive parameters. A time-varying parameters are expressed as a summation of constants multiplied by basis functions. ...

a r t i c l e i n f o JEL classification: C32 C51 L94 Q40 Keywords: Wholesale spot electricity price markets Constant and dynamic conditional correlation Multivariate GARCH This paper examines the interrelationships of wholesale spot electricity prices among the four regional A multivariate generalised autoregressive conditional heteroscedasticity model with time-varying correlations. Dynamic c...

A generalized minimum variance controller is developed for servo application for multiple input and multiple output systems having time-varying dynamics. The plant to be controlled is a controlled autoregressive moving average model and the control objective is to minimize a generalized minimum variance performance index that is an extension of the standard index from linear time invariant case...

A generalised minimum variance controller is developed for linear time-varying systems. The plants to be controlled are described using a controlled autoregressive moving average model and are exponentially stable. Both, the plant parameters and the noise variance are time-varying. The generalised minimum variance cost functional is the sum of a tracking error variance between a filtered plant ...

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 paper proposes a simple approach to analyzing profit dynamics which allows for time-varying persistence of profits. The time series model is a simple autoregressive process where the dynamics of the persistence parameter follow an autoregressive or random walk process. Using the longest time series available on profits for six US firms (Archer-Daniels-Midland , Avon, Coca Cola, Johnson & J...

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...

Asymmetry and fat-tail are both stylized facts of financial return data. Many asymmetric and fat-tailed distributions have been used to model the innovation in autoregressive conditional heteroskedasticity (ARCH) models. This article introduces two more distributions from systems of frequency curves into the ARCH context: Pearson’s Type IV and Johnson’s SU. Both distributions have two shape par...