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 Tails"”.
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Heavy Tails and Anomalous Diffusion in Human Online Dynamics
… is found to be related to the vanishing of the heavy-tailed characteristics of step lengths in newer logs as well as the switch from superdiffusion to normal diffusion in the diffusive processes of the random walks. In the language of foraging, the newer logs indicate that online searches …
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Some new Laplace-based probability distributions for modeling data with pronounced peaks combined with heavy tails and outliers
… with pronounced peaks combined with long and heavy tails. First, we revisit the class of univariate uniform-Laplace mixture (ULM) distributions, which are well-suited to model these features with great flexibility. Our primary objective here is to address the estimation issues associated with …
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Robust mixtures of regression models
… squares estimate, is sensitive to outliers and heavy-tailed error distributions. We propose a robust estimation procedure and an EM-type algorithm to estimate the mixture regression models. Using a Monte Carlo simulation study, we demonstrate that the proposed new estimation method is robust and …
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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 …
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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 …
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The joint distribution of the maximum and duration of stochastic events driven by Pareto II observations
… hydrology and climate. However, the existence of heavy tails in environmental variables motivated this model. Our results for this research include derivations of the joint probability density function, cumulative distribution function, conditional and marginal distributions, conditional survival …
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Miery závislosti pre náhodné veličiny s nekonečnými rozptylmi
… distributions, which are characterized by their heavy tails. The introduction summarizes the theory of characteristic functions and stable distributions, which is necessary for the main objective of this work-namely, the presen- tation of alternative measures of dependence applicable to this …
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Linear Mixed Models With Non-Normal Distributions
… Capitanio, 2003), which account for skewness and heavy tails for both the random effects and the errors. This approach has been applied to the real data obtained from deglutition and respiration studies and showed significant improvement over normal model fits. The estimators are shown to be …
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Power Transformation Towards Linear or Partially Linear Quantile Regression Models
… in the presence of heteroscedasticity and heavy-tails. Inferences about the transformation parameter and about the covariate effects are considered mathematically as well as empirically. A test for the adequacy of the power-transformation models is also proposed. For the power-transformed …
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Algorithms for Mixture Models
… algorithm that can learn distributions with heavy tails, including those with infinite variance and expectation. We formulate necessary conditions and provide an algorithm which guarantees that the underlying mixture model can be learned by observing only polynomially many samples. We also …
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The Cauchy-Net Mixture Model for Clustering with Anomalous Data
… to the well-defined components by leveraging its heavy tails. Through isolating the anomalous observations in a single component, we simultaneously identify the observations in the net as warranting further inspection and prevent them from interfering with the formation of the remaining …
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Portfolio risk minimization under departures from normality
… focus on extreme tail risk. In the presence of heavy tails and tail dependence, we show that portfolios based on the minimization of alternative robust measures of risk may in fact have lower variance than those based on the minimization of sample variance. We show that minimizing the sample …
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Error analysis of the COS method for options pricing
… jump model, which encompass a range of jump and heavy-tailed behaviors. Through extensive numerical experiments, we demonstrate that the COS method achieves high accuracy and rapid convergence across all tested models. For instance, under the classical Black–Scholes (GBM) model, the COS expansion …
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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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Probabalistic quantification of intermittently unstable dynamical systems
… spikes in the time series of the system or heavy-tails in the probability density function (pdf) of the response. We formulate a method that can analytically approximate the response pdf (both the main probability mass and heavy-tail structure) for systems where intermittency is important to …
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Towards robust inference for Bayesian filtering of linear Gaussian dynamical systems subject to additive change
… is signal noise and observation noise, regarding heavy tailedness in that the true dynamic frequently produces observation outliers or abrupt jumps of the signal state due to realizations of these heavy tails not considered by the model. We propose a formalisation of observation noise …
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Analysis of equity and interest rate returns in South Africa under the context of jump diffusion processes
… return distributions are leptokurtic and have heavy tails. Although jump diffusion models have been identified as being useful to capture these stylized facts, there has not been consensus as to how these jump diffusion models should be calibrated. This dissertation tackles this calibration …
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Lagrangian dynamics of turbulence: Applications with 3D particle tracking velocimetry
… core. PDF of the Lagrangian acceleration exhibit heavy tails in both geometries; however, the curvature PDF revealed a distinct footprint of the pipe shape. In addition, a rich data-set of Lagrangian trajectories was used to study the structure of various acceleration components, vorticity, and …
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Highly efficient pricing of exotic derivatives under mean-reversion, jumps and stochastic volatility
… capture the various empirical features, such as heavy tails and asymmetry, commonly observed in financial data. However, under such a framework, the density function governing the underlying asset price process is generally not available. This leads to a breakdown of the classical risk-neutral …
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On inference about rare events
… that are asymptotically non-trivial only in a heavy-tail setting. This explains the success of this method in natural language modeling, where one often has Zipf law behavior. We then study the strong consistency of estimators, in the sense of ratios converging to one. We first show that the …
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