Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 93 for “"Heavy-tailed"”.
-
Heavy-Tailed Crack Distribution Families and Applications
The heavy-tailedness and right-skewness are two typical features of loss data resulting from catastrophic natural phenomena such as severe weather events and earthquakes. In this thesis, we consider a new class of heavy-tailed crack distribution families as an extension of the three-parameter …
-
Hypothesis Testing Using Spatially Dependent Heavy-Tailed Multisensor Data
<p>The detection of spatially dependent heavy-tailed signals is considered in this dissertation. While the central limit theorem, and its implication of asymptotic normality of interacting random processes, is generally useful for the theoretical characterization of a wide variety of natural and …
-
Stochastic Modelling of Heavy-Tailed Precipitations in Canadian Prairies
… observations exhibits characteristics such as heavy-tailedness and volatility clustering (i.e., some periods of high and some periods of low volatility) which make it challenging to develop an effective model for both the theoretical and observations viewpoints. The main goal of this study is …
-
Scheduling in switched queueing networks with heavy-tailed trac
… the networks that we consider receive a mix of heavy-tailed and light-tailed trac. In this setting we evaluate the delay performance of the widely-studied class of Max-Weight scheduling policies. As performance metric we use the notion of delay stability, i.e., whether the steady-state expected …
-
Extended Entropy Maximisation and Queueing Systems with Heavy-Tailed Distributions
… and/or long-range dependent, because of the heavy (long) tails for the various distributions of interest, including intermittent intervals and queue lengths. Other studies have addressed vacation in no-customers’ queueing system or when the server fails. These patterns are important for …
-
Fair, Robust, and Calibrated Deep Learning with Heavy-Tailed Subgroups
… they are fair, robust, and calibrated. However, heavy-tails pose a challenge to this mandate, especially since real world data is often imbalanced and marginalized subgroups tend to be underrepresented. To move toward safer systems, we present two studies on fair pre-processing and ensemble …
-
Economic Capital Analysis with Portfolios of Dependent and Heavy-Tailed Risks
In the nowadays reality of prudent risk management, the problem of determining aggregate risk capital in financial entities has been intensively studied for quite long. As a result, canonical methods have been developed and even embedded in regulatory accords. While applauded by some and questioned …
-
Coupling in SPDEs and spectral analysis of heavy-tailed random operators
… and (2) a large deviation result in the light-tailed regime, and the distribution of the top eigenvalues in the heavy-tailed regime, under various tail assumptions on the random potential and the rate of downward scaling. In the third part, the author considers Wigner matrices, randomly …
-
Size-independent vs. size-dependent policies in scheduling heavy-tailed distributions
… server, where the job size distribution is heavy-tailed. We focus on two distributions, for which we prove that the performance of the optimal size-independent policy is asymptotically worse than that of a simple size-dependent policy. First, we consider a simple distribution where incoming …
-
Using importance sampling to simulate queuing networks with heavy-tailed service time distributions
… service time. We run it on a M/G/1 queue with heavy-tailed service time distributions and show simulation gains of two orders of magnitude over direct simulation for a fixed confidence interval.
-
Robust recursive estimation of the state of a discrete-time stochastic linear dynamic system in the presence of heavy-tailed observation noise
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 1989.
-
Evidence-based Cybersecurity: Data-driven and Abstract Models
… the data-driven models show that the presence of heavy-tailed distributions can make naive analysis of trends and interventions misleading. First, I examine ten years of publicly reported data breaches and find that there has been no increase in size or frequency. I also find that reported and …
-
Rare Events in Stochastic Systems: Modeling, Simulation Design and Algorithm Analysis
… Chapter 5. The titles of the main chapters are detailed as follows: Chapter 2: Analysis of a Splitting Estimator for Rare Event Probabilities in Jackson Networks Chapter 3: Splitting for Heavy-tailed Systems: An Exploration with Two Algorithms Chapter 4: State Dependent Importance Sampling with …
-
Data driven approaches to improve operational efficiency of emergency medical services
… economies. These systems usually operate under heavy resource constraints and face significant operational challenges, making them structurally and operationally different from systems in developed countries. In this thesis we study two specific issues - (i) modeling human behavior, and (ii) …
-
On the derivation of non-local diffusion equations in confined spaces
… diffusion equations from kinetic models with heavy-tailed equilibrium in velocity. We are particularly interested in confining the kinetic equations and developing methods that allow us, from the confined kinetic models, to derive confined versions of non-local diffusion equations.
-
Robust Bayesian Anomaly Detection Methods for Large Scale Sensor Systems
… Bayesian mixture model approaches that utilize heavy-tailed Cauchy assumptions. First, we propose a Robust Bayesian Regression, which utilizes a scale-mixture model to induce a Cauchy regression. Second, we extend elements of the Robust Bayesian Regression methodology using additive mixture …
-
Simulation Study on Confidence Interval Estimation for Standard Deviation with Non-Normal Distributions
… is compromised when dealing with skewed or heavy-tailed distributions and exhibits sensitivity to outliers. Our research addresses these limitations by investigating alternative estimation methods that offer greater robustness and accuracy.</p>
-
A unified study of bounds and asymptotic estimates for renewal equations and compound distributions with applications to insurance risk analysis
… with general claim sizes and especially with heavy-tailed distributions. Chapter 1 presents the probability models of compound distributions and renewal equations in insurance risk analysis and gives the summary of the results of this thesis. In Chapter 2, we develop a general method to …
-
Non-Gaussian Stochastic Process Priors for Learning
… L\'evy processes that display varying levels of heavy-tailed, non-Gaussian behaviour while maintaining the Brownian motion as an edge parameter setting. In this work, we review the theoretical background required to study non-Gaussian behaviour in continuous-time dynamical systems and …
Page 1 of 5