The proposed numerical technique is employed in well-understood problems to assess its efficiency. It is assumed that the workload is observed at Poisson instants. If the result from part 1 indicates a risk for Down syndrome that is higher than the screen cutoff, the screen is completed, and a report is issued. The main objective of this paper is to develop methods for distinguishing between two characteristic exponent functions, say 0()and 1(), based on observations of the corresponding workload process, rather than on observations of the Lvy input processes themselves. Bridge sampling Data augmentation Gamma process Lvy process Lvy density. It requires a nuchal translucency measurement and blood collection in the first trimester. Finally, we test our method on a classical insurance dataset. Hence, instead of solving the problem analytically, we use a collocation technique: the value function is replaced by a truncated series of polynomials with unknown coefficients that, together with the boundary points, are determined by forcing the series to satisfy the boundary conditions and, at fixed points, the integro-differential equation. Testing Algorithm Sequential maternal screening is a 2-step test, with first- and second-trimester components. In full sequential approaches, one doesn’t check the data. Due to the form of the Lévy measure of a gamma process, determining the solution of this equation and the boundaries is not an easy task. An advantage to non-sequential testing is that in case of sufficient evidence, one can stop data collection halfway through the process. The initial optimal stopping problem is reduced to a free-boundary problem where, at the unknown boundary points separating the stopping and continuation set, the principles of the smooth and/or continuous fit hold and the unknown value function satisfies on the continuation set a linear integro-differential equation. We study the Bayesian problem of sequential testing of two simple hypotheses about the parameter α > 0 of a Lévy gamma process. We present the sequential testing of two simple hypotheses for a large class of Lévy processes.
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