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answer the following questions: (i) How realistic are these classic assumptions in simulation practice? (ii) How can these … assumptions be tested? (iii) If assumptions are violated, can the simulation's I/O data be transformed such that the assumptions …
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In many regression applications, users are often faced with difficulties due to nonlinear relationships, heterogeneous subjects, or time series which are best represented by splines. In such applications, two or more regression functions are often necessary to best summarize the underlying...
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This paper introduces a novel simulation-based filtering method for general state space models. It allows for the …
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John Snow and causal inference -- RStudio and R -- Regression and simulation -- Potential outcomes -- Causal graphs … intuitive, using helpful concepts, applications, simulation, and data graphs. Many public policy questions are inherently causal …
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This working paper aims to stress the role of the institutional capital and its components, as primary factors, in economic results at the national level, using adequate measurement indicators and econometric models. For this purpose, we analysed the following aspects: the definition of...
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