We present a complete Bayesian treatment of autoregressive model estimation incorporating choice of autoregressive order, enforcement of stationarity, treatment of outliers and allowance for missing values and multiplicative seasonality. The paper makes three distinct contributions. First, we enforce the stationarity conditions using a very eecient Metropolis-within-Gibbs algorithm to generate ...

We propose the autoregressive HMM for speech synthesis. We show that the autoregressive HMM supports efficient EM parameter estimation and that we can use established effective synthesis techniques such as synthesis considering global variance with minimal modification. The autoregressive HMM uses the same model for parameter estimation and synthesis in a consistent way, in contrast to the stan...

Recently, there has been a renewed interest in modeling economic time series by vector autoregressive moving-average models. However, this class of models has been unpopular in practice because of estimation problems and the complexity of the identification stage. These disadvantages could have led to the dominant use of vector autoregressive models in macroeconomic research. In this paper, sev...

This paper proposes a new estimation procedure for the first-order spatial autoregressive (SAR) model, where disturbance term also follows autoregression and its innovations may be heteroscedastic. The is based on principle of indirect inference that matches ordinary least squares estimator two SAR coefficients (one in outcome equation other equation) with approximate analytical expectation. re...

This study explores the asymmetric impact of oil supply and demand shocks on sectoral stock market returns Pakistan. For this purpose, uses non-linear autoregressive distributed lag (ARDL) approach based monthly time series data for four sectors in Pakistan Stock Exchange over period 2005–2018. First, findings unit root tests identified that all are stationary at first difference. Second, F-bou...

This study investigates the long term relationship between behaviour of stock markets during 2008 crisis and some selected international macroeconomic variables using information from January 2005 to December 2015. The procedures Autoregressive Distributed Lag modeling techniques (ARDL) are employed for analysis. bounds testing procedure in ARDL framework is used test existence relationships ma...

We study situations in which autoregressive models are estimated on time series that contain switches in the data generating parameters and these switches are not accounted for. The geometry of this estimation problem causes estimated vector autoregressive models to display a unit eigenvalue, and the sum of the estimated autoregressive parameters of ARMA and GARCH models to be close to one. Thi...

Forecasting of the Renewable Energy plays a major role in optimal decision formula for government and industrial sector in Bangladesh. This research is based on time series modeling with special application to solar energy data for Dhaka city. Three families of time series models namely, the autoregressive integrated moving average models, Holt’s linear exponential smoothing, and the autoregres...