We present a Bayesian approach for modeling multivariate, dependent functional data. To account for the three dominant structural features in the data—functional, time dependent, and multivariate components—we extend hierarchical dynamic linear models for multivariate time series to the functional data setting. We also develop Bayesian spline theory in a more general constrained optimization fr...

This paper attempts to theoretically understand the process of catching-up or falling behind particularly within the context of developing countries. The main aim of the paper consists in investigating the impact of domestic innovation, via its interaction with the learning capability, on the technology gap of an economy. More specifically, we seek to shed some light on why the tendency for poo...

In this paper we aim to compare the performance of three different Bayesian model averaging (or mixture) methods applied to regression dynamic linear models for beverage data from Zimbabwe. The models are chosen to reflect different plausible causal structures of association between beverage sales and other variables, thought to influence beverage sales, such as prices, temperature and maize cr...

    Dynamic cellular manufacturing systems,   Mixed-integer non-linear programming,   Production planning, Manufacturing attributes   This paper presents a novel mixed-integer non-linear programming model for the design of a dynamic cellular manufacturing system (DCMS) based on production planning (PP) decisions and several manufacturing attributes. Such an integrated DCMS model with an extensi...

To facilitate the damping matching of dampers for vehicle passive suspensions, this paper proposes an analytical matching method of the optimal piecewise linear damping characteristics curve. Based on the vehicle vibration model, taking the suspension dynamic deflection as the constraint, by the vibration acceleration and the wheel dynamic load, an objective function about the relative damping ...

Evolving models have found applications in many real world systems. In this paper, potentials of the Evolving Linear Models (ELMs) in tracking control design for nonlinear variable structure systems are introduced. At first, an ELM is introduced as a dynamic single input, single output (SISO) linear model whose parameters as well as dynamic orders of input and output signals can change through ...