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In some cases, the estimators obtained in compound tests have better features than the traditional ones, obtained from individual tests, cf. Sobel and Elashoff (1975), Garner et al. (1989) and Loyer (1983). The bias, the efficiency and the robustness of these estimators are investigated in several papers, e.g. Chen and Swallow (1990), Hung and Swallow (1999) and Lancaster and Keller-McNulty (1998). Thus, the use of estimators based on compound tests not only allows a substantial saving of costs, but they also can (in some situations) be more accurate than the estimators based on the individual tests. Nevertheless, each laboratory produces estimates for the prevalence rate of a given infection using different methodologies, such as halving nested procedures (Sobel and Elashoff, 1975) and square array testing (Kim et al., 2007). The logistic regression or the weighted least squares regression can be used in order to combine different prevalence rate estimates (Chen and Swallow, 1990). In this work some meta-analytical techniques are proposed as an alternative approach. This methodology has the advantage of being quite simple and flexible to account for the error source.
EN
Software for modeling and simulation (MSS) of mechanical systems helps to reduce production costs for industry. Usually, such software relies on (possibly erroneous) finite precision arithmetic and does not take into account uncertainty in the input data. The program SmartMOBILE enhances the existing MSS MOBILE with verified techniques to provide a guarantee that the obtained results are correct and measure the influence of data uncertainty. In this paper, we outline the main features and functionalities of SmartMOBILE. In particular, we focus on its use of newly developed methods for sensitivity analysis and DAE solving for several practically relevant mechanical systems.
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Continuity of solutions of Riccati equations for the discrete-time JLQP

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The continuity of the solutions of difference and algebraic coupled Riccati equations for the discrete-time Markovian jump linear quadratic control problem as a function of coefficients is verified. The line of reasoning goes through the use of the minimum property formulated analogously to the one for coupled continuous Riccati equations presented by Wonham and a set of comparison theorems.
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