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functional magnetic resonance imaging (fMRI) data from an investment decision (ID) study for ID-related effects. We propose a new … technique for identifying activated brain regions: Cluster, Estimation, Activation and Decision (CEAD) method. Our analysis is … activation between conditions. This sequence of Cluster, Estimation, Activation and Decision admits a model-free analysis of the …
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This article develops a theoretical model for evaluating mandatory activation of welfare recipients in complex … activation programmes. The model aims to summarize and describe heterogeneous content that is difficult to comprehend because of … essential characteristics for capturing generic components of activation programmes. We use experience from an on-site interview …
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Sequential Monte Carlo (SMC) methods are widely used for non-linear filtering purposes. However, the SMC scope encompasses wider applications such as estimating static model parameters so much that it is becoming a serious alternative to Markov-Chain Monte-Carlo (MCMC) methods. Not only do SMC...
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A flexible predictive density combination model is introduced for large financial data sets which allows for dynamic weight learning and model set incompleteness. Dimension reduction procedures allocate the large sets of predictive densities and combination weights to relatively small sets....
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