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.
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Showing 1 to 20 of 27 for “"Heavy-tailed distributions"”.
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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 …
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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 …
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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>
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A unified study of bounds and asymptotic estimates for renewal equations and compound distributions with applications to insurance risk analysis
… estimates for renewal equations and compound distributions and gives applications to aggregate claim distributions, stop-loss premium and ruin probabilities with general claim sizes and especially with heavy-tailed distributions. Chapter 1 presents the probability models of compound …
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Simulating Statistical Power Curves with the Bootstrap and Robust Estimation
… normal theory counterpart whenever the data had heavy tailed distributions; 2) bootstrap empirical power is higher for Mestimators than the normal theory counterpart when the data had heavy tailed distributions; 3) the smoothed bootstrap controls type I error rate (less than 6%) under the null …
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Robust Statistical Modeling In Functional Linear Regression
… has been devoted to addressing outliers or heavy-tailed distributions in the data. Consequently, robust statistical analysis remains an underdeveloped practice in this area. The primary objective of this dissertation is to enhance the utilization of robust methods for modeling functional …
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Pricing index-linked catastrophe bonds via Monte Carlo simulation
… these exercises, it becomes apparent that very heavy-tailed distributions need to be used with caution. In the former case, the use of very heavy-tailed distributions places restrictions on the distributions that can be used for the mixed-approximation method. Finally, as a more realistic avenue …
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Hidden Markov Model with Binned Duration and Its Application
… in some real-world applications where the distributions on state intervals deviate signi cantly from the geometric distribution, such as multi-modal distributions and heavy-tailed distributions. The hidden Markov model with duration (HMMD) avoids this limitation by explicitly incor- …
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Lévy processes in credit risk and market models
… aspects of credit risk, generalized hyperbolic distributions and Lévy processes. In the overview of the structural approach, it is shown how Lévy processes can be used to generalize the classical structural approach. The second chapter contains a generalization of the software package …
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Monitoring unknown source IP addresses and packet sizes to detect DDoS attacks
… sizes that follows a mixture of discrete and heavy tailed distributions. Both detection systems monitor the percentage of unknown source IP addresses. The rst detection model is formulated as a xed sample size binary hypothesis testing. The decision making is based on the Neyman-Pearson …
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Latent variable augmentation for approximate Bayesian inference
… each with its pitfalls and limits. For instance, heavy-tailed distributions represent a challenge for sampling methods, and strongly correlated variables quickly become a bottleneck for many inference algorithms. Instead of developing yet another new state-of-the-art sampler or optimizer, we focus …
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Robust sequential decision-making on networks
… rewards are drawn from a family of extremely heavy-tailed distributions known as a-stable distributions. For this setting, I extended an existing upper confidence bound algorithm, to create an optimal frequentist algorithm, titled [alpha]-UCB. Next, I developed a variant of the Bayesian …
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Memory Properties Of Transformations Of Linear Processes And Symmetric Gini Correlation
… the dependence between random variables with heavy tailed distributions. However, the asymmetry of Gini covariance and correlation brings a substantial difficulty in interpretation. In this dissertation, we propose a symmetric Gini-type covariance and correlation (ρg) based on the joint rank …
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On Laplace transforms, generalized gamma convolutions, and their applications in risk aggregation
… approximation (MMA) method for approximating the distributions of the sums of insurance risks. Our method approximates the distributions of interest to any desired precision, works equally well for light and heavy-tailed distributions, and is reasonably fast irrespective of the number of the …
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Traffic Characterization of Social Network Applications
… diurnal patterns, complex user interactions, and heavy-tailed distributions for connection durations and transfer sizes. Instagram exceeded 1 TB of daily traffic volume on our campus network and the four IM apps contributed about 650 GB per day. By analyzing and characterizing the network traffic …
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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 …
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Gini Covariance Matrix and its Affine Equivariant Version
… definition of location for non-symmetric distributions. We study the properties of both GCMs. They possess the so-called independence property, which is highly important, for example, in independent component analysis. Influence functions of two GCMs are derived to assess their robustness. …
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Invariant tests for scale parameters under elliptical symmetry
… necessarily either Gaussian or independent. The distributions considered are the spherically symmetric vector laws, i.e. laws for which x(nx1) and Px have the same distribution for every (nxn) orthogonal matrix P, and natural extensions of these to laws of random matrices. If x has a spherical …
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Environmental constraints on human memory
… known as Lévy flights. Lévy flights or Lévy distributions are positively skewed; heavy-tailed distributions that contain many more extremely large distances than would be expected from a Gaussian distribution and have a slope of (1 < ≤ 3). Although, any number in this range will give rise to …
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Contributions to Robust Methods: Modified Rank Covariance Matrix and Spatial-EM Algorithm
… in data and poor in the efficiency for heavy-tailed distributions. A straightforward treatment is to replace the sample covariance matrix with a robust one. Visuri et al. (2000) proposed a technique for robust covariance matrix estimation based on different notions of multivariate sign …
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