Estimation of the long-term health effects of air pollution is a challenging task, especially when modelling small-area disease incidence data in an ecological study design. The challenge comes from the unobserved underlying spatial correlation structure in these data, which is accounted for using random effects modelled by a globally smooth conditional autoregressive model. These smooth random...

Tunisia is experiencing rapid social and economic expectations. The penetration of information communication technology (ICT) might be useful for green development. This paper takes a novel use the logistic smooth transition regression model in studying pattern from link between growth CO2 emissions over period 1970–2018. results indicate that follows nonlinear with ICT as variable affecting re...

We develop a mixture model for transition density approximation, together with soft selection, in the presence of noisy and heterogeneous nonlinear dynamics. Our builds on Gaussian distribution (MTD) continuous state spaces, extending component means functions that are modeled using process (GP) priors. The resulting flexibly captures lag dependence when several components active, identifies lo...

In this paper, we discuss a Bayesian approach to quantile autoregressive (QAR) time series model estimation and forecasting. Together with a combining forecasts technique, we then predict USD to GBP currency exchange rates. Combined forecasts contain all the information captured by the fitted QAR models at different quantile levels and are therefore better than those obtained from individual mo...

The main objective of this paper is to show potential usefulness of the combination of autoregressive integrated moving average (ARIMA) models and logistic regression with automatic model selection (see our work presented at SUGI’28 and SUGI’29.) Timeseries analysis with ARIMA provides only one perspective of the information in the surveillance data (i.e. the number of patients as a function of...

In this paper we apply an Adaptive Network-Based Fuzzy Inference System (ANFIS) with one input, the dependent variable with one lag, for the forecasting of four macroeconomic variables of US economy, the Gross Domestic Product, the inflation rate, six monthly treasury bills interest rates and unemployment rate. We compare the forecasting performance of ANFIS with those of the widely used linear...

By combining the field-weakening control principle of a new axial flux-switching permanent-magnet motor (AFFSSPM) with the space vector pulse width modulation (SVPWM) and maximum torque per voltage (MTPV) control principle, a novel field-weakening control strategy for AFFSSPM is proposed in this paper. In the first stage of the field-weakening, the difference between the reference voltage updat...