In this work, we report the experimental implementation of a Quantitative Feedback Theory (QFT) based robust controller, designed online using hybrid global optimization and constraint propagation techniques. The hybrid global optimization combines interval global optimization and nonlinear local optimization methods. The constraint propagation techniques are very effective in discarding infeas...

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In this chapter we draw connections between two seemingly opposing approaches to probability and statistics: evidential probability on the one hand and objective Bayesian epistemology on the other.

The degree of empirical support of a priori plausible structures on the cointegration vectors has a central role in the analysis of cointegration. Historically, this question has been answered by classical testing of over-identifying restrictions on the cointegration space. This paper introduces an exact finite sample Bayesian procedure to calculate the posterior probability of restrictions on ...

In this paper joint mean and variance beta regression models are proposed. The proposed models are fitted applying Bayesian methodology and assuming normal prior distribution for the regression parameters. An analysis of structural and real data is included, assuming the proposed model, together with a comparison of the result obtained assuming joint modeling of the mean and precision parameters.

A key step in “Designing for the Consequences of Hazard” is choosing which hazards to design for. This paper argues that the Bayesian perspective is the rational and prudent framework.

A Confounder is a variable whose presence affects the variables being studied so that the results do not reflect the actual relationship. There are various ways to exclude or control confounding variables including Randomization, Restriction and Matching. But all these methods are applicable at the time of study design. When experimental designs are premature, impractical, or impossible, resear...

Although common in the educational and developmental areas, multilevel models are not often utilized in the analysis of data from experimental designs. This article illustrates how multilevel models can be useful with two examples from experimental designs with repeated measurements not involving time. One example demonstrates how to properly examine independent variables for experimental stimu...

In this Data in Brief paper, a central composite experimental design was planned to collect the surface roughness of an end milling operation of AISI 1045 steel. The surface roughness values are supposed to suffer some kind of variation due to the action of several factors. The main objective here was to present a multivariate experimental design and data collection including control factors, n...