An approach is presented to get interconnections between the Fisher information matrix of an ARMAX process and a corresponding solution of a Stein equation. The case of algebraic multiplicity greater than one and the case of distinct eigenvalues are addressed. Appropriate links are constructed for these two cases by applying a factorization both for the Fisher information matrix and for a corre...

OBJECTIVE To evaluate the effect that seasonality has on the occurrence of respiratory symptoms in a Brazilian city with a tropical climate. METHODS This was a cross-sectional study, in which data related to subjects who sought outpatient treatment at a primary health care clinic in the city of Goiânia, Brazil, were correlated with daily meteorological data. Over a one-year period, all the pa...

In this paper we derive the maximum likelihood problem for missing data from a Gaussian model. We present in total eight di erent equivalent formulations of the resulting optimization problem, four out of which are nonlinear least squares formulations. Among these formulations are also formulations based on the expectation-maximization algorithm. Expressions for the derivatives needed in order ...

ARX models, is a suitable model class for linear control implementations. The parameter estimation problem is convex and easily handed for both SISO and MIMO system in contrast to ARMAX or State Space model. Model predictive control implementations insuring offset-free tracking are discussed and related. Special attention is given to an adaptive disturbance estimation method with time-varying f...

The control theory and automation technology is widely used in industries. Many control algorithms are based on the mathematical models of dynamic systems. Mathematical models and parameter estimation are basics for automatic control. A recursive least squares parameter estimation algorithms and Kaczmarz’s projection algorithm is applied based on ARMAX model and OE models. The estimated paramet...

The robust self-tuning regulator of a class of linear systems, which can be described by the input-output Auto-Regressive Moving Average with exogenous (ARMAX) mathematical model with unknown and time-varying parameters, at bounded external disturbances is developed. A scheme of polynomial approximation has been applied to approximate the unknown and time-varying parameters of systems. The modi...

Traffic Management Centers (TMC) want to improve the performance of road networks and reduce congestion by actively managing the infrastructure of a freeway corridor. A promising avenue for proactive traffic management is the prediction of the near-future traffic conditions in real-time by employing a traffic flow model. An important set of calibration parameters of such a model are the boundar...

In this thesis we primarily consider the development and applications of risk-sensitive identification schemes for fast convergence of parameter estimates. Initially we consider the risk-sensitive identification problem for hidden Markov models (HMMs). Finite dimensional filters are derived, for the risk-sensitive identification of HMMs, by combining the techniques of maximum likelihood (ML) id...