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Simulation: A Modeler's Approach
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The generation of "random" numbers random quadrature Monte Carlo solutions of differential equations Markov chains, Poisson processes and linear equations SIMEST, SIMDAT, and pseudoreality models for stocks and derivatives simulation assessment of multivariate and robust procedures in statistical process control noise and chaos Bayesian approaches resampling based tests optimisation and estimation in a noisy world modeling the USA AIDS epidemic.Abstract:
The generation of "random" numbers random quadrature Monte Carlo solutions of differential equations Markov chains, Poisson processes and linear equations SIMEST, SIMDAT, and pseudoreality models for stocks and derivatives simulation assessment of multivariate and robust procedures in statistical process control noise and chaos Bayesian approaches resampling based tests optimisation and estimation in a noisy world modeling the USA AIDS epidemic - exploration, simulation and conjecture.read more
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Journal ArticleDOI
Quantum implementation of the unitary coupled cluster for simulating molecular electronic structure
TL;DR: In this paper, the authors provide experimental evidence that indeed the unitary version of the coupled-cluster ansatz can be reliably performed in a physical quantum system, a trapped-ion system.
Journal ArticleDOI
Simulation as experiment: a philosophical reassessment for biological modeling
TL;DR: It is argued that current discussions in the philosophy of science and in the physical sciences fields about the use of simulation as an experimental system have important implications for biology, especially complex sciences such as evolution and ecology.
Journal ArticleDOI
Definition and Review of Virtual Prototyping
TL;DR: A definition of VP as well as components of a virtual prototype are proposed and VP is compared with and distinguished from virtual reality (VR), virtual environment (VE), and virtual manufacturing (VM) techniques.
Book
Elements of computational statistics
TL;DR: Preliminaries * Monte Carlo Methods for Inference * Randomization and Data Partitioning * Bootstrap Methods * Tools for Identification of Structure in Data * Estimation of Functions * Graphical Methods in Computational Statistics * Estimating of Probability Density Functions Using Parametric Models * Nonparametric Estimation.
Journal ArticleDOI
Simple matrix methods for analyzing diffusion models of choice probability, choice response time, and simple response time
TL;DR: This tutorial explains step by step, using a matrix approach, how to construct these models for binaries choices for unidimensional and multiattribute choice alternatives; for simple reaction time tasks; and for three alternatives choice problems.
References
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Nonparametric probability density estimation
Book
Nonparametric Function Estimation, Modeling, and Simulation
TL;DR: In this article, the authors present some approaches to nonparametric density estimation in higher dimensions, such as in the case of model building and speculative data analysis, and numerical solution of constrained optimization problems.