Distinctive regional characteristics in different natural gas markets have increased the difficulty accurately forecasting prices. Moreover, experienced great structural instability due to advancement technology and rapid financialization over past few decades. We employ three classes of flexible time-varying parameters models evaluate effects on prices forecasts. Using data from US, EU Japanes...

A time-varying autoregressive model with time-varying coefficients is introduced in this paper for parameter extraction from non-stationary vibration signals. With this model, the relationship between linear time-varying modal parameters, i.e., instantaneous frequencies and damping factors, and time-varying autoregressive model coefficients is established. The time-varying autoregressive modeli...

Many systems arising in biological applications are subject to periodic forcing. In these systems the forcing parameter is not only time-varying but also known to have a periodic structure. We present an approach to estimate periodic, time-varying parameters using nonlinear Bayesian filtering. Most parameter estimation methodology in the literature is aimed at estimating constant parameters or ...

In this article, we write the time-varying parameter (TVP) regression model involving K explanatory variables and T observations as a constant coefficient with KT variables. contrast much of existing literature which assumes coefficients to evolve according random walk, hierarchical mixture on TVPs is introduced. The resulting closely mimics specification groups into several regimes. These flex...

Estimating and detecting faults is crucial in ensuring safe efficient automated systems. In the presence of disturbances, noise, or varying system dynamics, such estimation even more challenging. To address this challenge, article proposes a novel filter to estimate multiple fault signals for class discrete-time linear parameter-varying (LPV) The design formulated as an optimization problem sol...