This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices ...that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum simulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. No other book incorporates all these fields, which have arisen in the past 20 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
Continuous System Simulation Cellier, François E; Kofman, Ernesto
Kluwer Academic Publishers eBooks,
2006, 2006-02-15
eBook
Odprti dostop
Continuous System Simulation describes in detail how to build mathematical simulations of systems that change continuously over time. It covers:
- Numerical integration
- Simulation of stiff systems
...- Simulation of marginally stable systems
- Simulation of noisy systems
- Model validation techniques
- Simulation verification
- The inverse problem
- Dynamic nonlinear programming
- Simulation software
- Simulation hardware
Intended for advanced undergraduates in electrical, computer, mechanical, and civil engineering, it is a highly computer-oriented text, introducing numerical methods and algorithms along with the applications and conceptual tools. Homework problems, suggestions for research projects, and open-ended questions conclude each chapter.
The Stanford Geostatistical Modeling Software (SGeMS) is an open-source computer package for solving problems involving spatially related variables. It provides geostatistics practitioners with a ...user-friendly interface, an interactive 3-D visualization, and a wide selection of algorithms. This practical book provides a step-by-step guide to using SGeMS algorithms. It explains the underlying theory, demonstrates their implementation, discusses their potential limitations, and helps the user make an informed decision about the choice of one algorithm over another. Users can complete complex tasks using the embedded scripting language, and new algorithms can be developed and integrated through the SGeMS plug-in mechanism. SGeMS was the first software to provide algorithms for multiple-point statistics, and the book presents a discussion of the corresponding theory and applications. Incorporating the full SGeMS software (now available from www.cambridge.org/9781107403246), this book is a useful user-guide for Earth Science graduates and researchers, as well as practitioners of environmental mining and petroleum engineering.
We present a rigid body simulation method that can resolve small temporal and spatial details by using a quasi explicit integration scheme that is unconditionally stable. Traditional rigid body ...simulators linearize constraints because they operate on the velocity level or solve the equations of motion implicitly thereby freezing the constraint directions for multiple iterations. Our method always works with the most recent constraint directions. This allows us to trace high speed motion of objects colliding against curved geometry, to reduce the number of constraints, to increase the robustness of the simulation, and to simplify the formulation of the solver. In this paper we provide all the details to implement a fully fledged rigid body solver that handles contacts, a variety of joint types and the interaction with soft objects.
The NEURON Book Carnevale, Nicholas T.; Hines, Michael L.
2006.
eBook
The authoritative reference on NEURON, the simulation environment for modeling biological neurons and neural networks that enjoys wide use in the experimental and computational neuroscience ...communities. This book shows how to use NEURON to construct and apply empirically based models. Written primarily for neuroscience investigators, teachers, and students, it assumes no previous knowledge of computer programming or numerical methods. Readers with a background in the physical sciences or mathematics, who have some knowledge about brain cells and circuits and are interested in computational modeling, will also find it helpful. The NEURON Book covers material that ranges from the inner workings of this program, to practical considerations involved in specifying the anatomical and biophysical properties that are to be represented in models. It uses a problem-solving approach, with many working examples that readers can try for themselves.
Control systems have come to play an important role in the performance of modern vehicles with regards to meeting goals on low emissions and low fuel consumption. To achieve these goals, modeling, ...simulation, and analysis have become standard tools for the development of control systems in the automotive industry.
iCyst: 1 year, 1000 and more simulations through an app Balduzzi, A.; Marchegiani, G.; Andrianello, S. ...
Pancreatology : official journal of the International Association of Pancreatology (IAP) ... et al.,
July 2021, 2021-07-00, 20210701, Letnik:
21
Journal Article
The Amazon basin is a key component of the global carbon cycle. The old-growth rainforests in the basin represent storage of ~ 120 petagrams of carbon (Pg C) in their biomass. Annually, these ...tropical forests process approximately 18 Pg C through respiration and photosynthesis. This is more than twice the rate of global anthropogenic fossil fuel emissions. The basin is also the largest global repository of biodiversity and produces about 20 percent of the world's flow of fresh water into the oceans. Despite the large carbon dioxide (CO2) efflux from recent deforestation, the Amazon rainforest ecosystem is still considered to be a net carbon sinks of 0.8-1.1 Pg C per year because growth on average exceeds mortality (Phillips et al. 2008). However, current climate trends and human-induced deforestation may be transforming forest structure and behavior (Phillips et al. 2009). Increasing temperatures may accelerate respiration rates and thus carbon emissions from soils (Malhi and Grace 2000). High probabilities for modification in rainfall patterns (Malhi et al. 2008) and prolonged drought stress may lead to reductions in biomass density. Resulting changes in evapo-transpiration and therefore convective precipitation could further accelerate drought conditions and destabilize the tropical ecosystem as a whole, causing a reduction in its biomass carrying capacity or dieback. In turn, changes in the structure of the Amazon and its associated water cycle will have implications for the many endemic species it contains and result in changes at a continental scale. Clearly, with much at stake, if climate-induced damage alters the state of the Amazon ecosystem, there is a need to better understand its risk, process, and dynamics. The objective of this study is to assist in understanding the risk, process, and dynamics of potential Amazon dieback and its implications.
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