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An Empirical Estimation Of Statistical Inferences For System Dynamics Model Parameters, Mohammed Mesabbah, Wael Rashwan, Amr Arisha
An Empirical Estimation Of Statistical Inferences For System Dynamics Model Parameters, Mohammed Mesabbah, Wael Rashwan, Amr Arisha
Conference papers
For system dynamics simulation (SD) models, an estimation of statistical distributions for uncertain parameters is crucial. These distributions could be used for testing models sensitivity, quality of policies, and/or estimating confidence intervals for these parameters. Assumptions related to normality, independence and constant variation are often misapplied in dynamic simulation. Bootstrapping holds a considerable theoretical advantage when used with non-Gaussian data for estimating empirical distributions for unknown parameters. Although it is a widely acceptable approach, it has had only limited use in system dynamics applications. This paper introduces an application of Direct Residual Bootstrapping (DRBS) for statistical inference in system dynamic …
‘I Just Want A Job’: The Untold Stories Of Entrepreneurship, Lucia Garcia-Lorenzo, Lucia Sell-Trujillo, Paul Donnelly
‘I Just Want A Job’: The Untold Stories Of Entrepreneurship, Lucia Garcia-Lorenzo, Lucia Sell-Trujillo, Paul Donnelly
Books/Book Chapters
In this chapter, we explore the untold stories of Spanish and Irish necessity entrepreneurs to better understand the process of becoming an entrepreneur. Working with narratives, media articles, and policy documents, we illustrate how necessity entrepreneurs do not recognize themselves in the institutionalized entrepreneur narrative as empowered, creative and independent individuals. It is necessity, not opportunity that is pushing, not pulling, them to become entrepreneurial. The process is experienced as more fragmented than official narratives outline. In exposing these untold stories, the chapter expands our understanding of entrepreneurship, presenting a more nuanced view of both entrepreneurs and the entrepreneurial process.
An Empirical Estimation Of Statistical Inferences For System Dynamics Model Parameters, Mohammed Mesabbah, Wael Rashwan, Amr Arisha
An Empirical Estimation Of Statistical Inferences For System Dynamics Model Parameters, Mohammed Mesabbah, Wael Rashwan, Amr Arisha
Conference papers
For system dynamics simulation (SD) models, an estimation of statistical distributions for uncertain parameters is crucial. These distributions could be used for testing models sensitivity, quality of policies, and/or estimating confidence intervals for these parameters. Assumptions related to normality, independence and constant variation are often misapplied in dynamic simulation. Bootstrapping holds a considerable theoretical advantage when used with non-Gaussian data for estimating empirical distributions for unknown parameters. Although it is a widely acceptable approach, it has had only limited use in system dynamics applications. This paper introduces an application of Direct Residual Bootstrapping (DRBS) for statistical inference in system dynamic …