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Simulation and Its Application
In this chapter, we will introduce Monte Carlo simulation which is a problem-solving technique. This technique can approximate the probability of...
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Predictive and Simulation Analytics Deeper Insights for Better Business Decisions
This book connects predictive analytics and simulation analytics, with the end goal of providing Rich Information to stakeholders in complex systems...
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A simulation model to analyze the behavior of a faculty retirement plan: a case study in Mexico
The main goal in this study was to determine confidence intervals for average age, average seniority, and average money-savings, for faculty members...
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Melding Predictive and Simulation Analytics
I introduce the melding of Predictive and Simulation Analytics in this chapter. This is best done by examples. The perspective for the examples...
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Inflation Simulation
This chapter investigates the impact of different scenarios on Great Britain’s inflation and consumer prices (as an annual percentage) using the...
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Simulation Study of Estimators of the Gamma Rate Parameter Using MLE as a Baseline Estimator
Classical estimation methods of the rate parameter of the gamma distribution have shown to have quality issues. In this paper we propose three...
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Stochastic Simulation of Continuous Time Random Walks: Minimizing Error in Time-Dependent Rate Coefficients for Diffusion-Limited Reactions
A reaction limited by standard diffusion is simulated stochastically to illustrate how the continuous time random walk (CTRW) formalism can be...
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Simulation Analysis of a Base Station Using Finite Buffer M/G/1 Queueing System with Variant Sleeps
In communication networks, the signals from mobile phones are transmitted through Base Stations(BS). Nowadays the usage of mobile phones has...
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Probability, Statistics and Simulation With Application Programs Written in R
This book presents in a compact form the program carried out in introductory statistics courses and discusses some essential topics for research...
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Continuous simulation of storm processes
Storm processes constitute prototype models for spatial extremes. They are classically simulated on a finite number of points within a given domain....
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Simulation comparisons between Bayesian and de-biased estimators in low-rank matrix completion
In this paper, we study the low-rank matrix completion problem, a class of machine learning problems, that aims at the prediction of missing entries...
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Construction and Simulation of Generalized Multivariate Hawkes Processes
The main contribution of the paper amounts to providing a mathematical construction of a generalized multivariate Hawkes process (GMHP), as well as a...
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Optimal Liquidation Through a Limit Order Book: A Neural Network and Simulation Approach
We present a learning algorithm based on simulation and neural networks to solve a stochastic optimal control problem with a large state space using...
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Simulation
In this chapter we look at the geostatistical simulation of compositional data. The workflow typically consists of first applying a log-ratio...
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Statistical Modeling and Simulation for Experimental Design and Machine Learning Applications Selected Contributions from SimStat 2019 and Invited Papers
This volume presents a selection of articles on statistical modeling and simulation, with a focus on different aspects of statistical estimation and...
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Stochastic Simulation Algorithms for Solving Transient Anisotropic Diffusion-recombination Equations and Application to Cathodoluminescence Imaging
A meshless Random Walk on arbitrary parallelepipeds simulation algorithm is developed and implemented for solving transient anisotropic...
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Designing and Analyzing a Simulation
I noted in Chap. 7 that there are two general application domains for simulations: scientific research and...
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Building a Tontine Simulation in R
In this chapter I explain the core of the (basic, version 1.0) modern tontine simulation algorithm and provide R-scripts that can be used to generate...
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Investigating Variable Selection Techniques Under Missing Data: A Simulation Study
Variable selection is one of the most pervasive problems researchers face, especially with the increased ease in data collection arising from online...