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Showing 1 to 20 of 23 for “"Dependence Structures"”.

  1. Essays on Quantitative Risk Management

    … Subsequently we move to the key concept of dependence by investigating the importance of dynamic linkages between credit and equity markets. We propose a flexible regime-switching copula model to explore the dynamics of dependence and possible structure breaks with special consideration on …

    city-london Repository record for Essays on Quantitative Risk Management (opens in a new tab)

  2. PERFORMANCE OF THE TWO SAMPLE LIKELIHOOD RATIO TEST UNDER A NESTED DIRICHLET: A SIMULATION STUDY

    … (NDD), which accommodates more flexible dependence structures than the standard Dirichlet model. This thesis builds on the methodology of Turner et al. Chapter 1 introduces the nature of compositional data and explains the limitations of traditional multivariate techniques. Chapter 2 …

    sfasu Repository record for PERFORMANCE OF THE TWO SAMPLE LIKELIHOOD RATIO TEST UNDER A NESTED DIRICHLET: A SIMULATION STUDY (opens in a new tab)

  3. Kernel Machines are Not Black Boxes - On the Interpretability of Kernel-based Nonparametric Models

    … using gradient information to interpret the co-dependence structures, as discovered by kernel canonical correlation analysis, between two variable sets.

    toronto-retro Repository record for Kernel Machines are Not Black Boxes - On the Interpretability of Kernel-based Nonparametric Models (opens in a new tab)

  4. Risk management and solvency: mathematical methods in theory and practice

    … (Federal Financial Supervisory Authority). The dependences between risks play an essential role in Solvency II since their negligence can lead to a substantial misestimation of the solvency capital. This is particularly critical when looking at natural catastrophes where dependencies can occur …

    oldenburg Repository record for Risk management and solvency: mathematical methods in theory and practice (opens in a new tab)

  5. Bayesian Model Selection for Spatial Data and Cost-constrained Applications

    … tool for identifying an appropriate model class, dependence structure, and valuable predictors for a wide variety of applications. In this work we consider objective Bayesian model selection where no subjective information is available to inform priors on model parameters a priori, specifically in …

    vt Repository record for Bayesian Model Selection for Spatial Data and Cost-constrained Applications (opens in a new tab)

  6. Statistical models for dependent and non-stationary extreme events

    … a univariate sequence which displays short-range dependence within the sample extremes. Next we propose a method for modelling the extremes of a non-stationary univariate process; we then extend this methodology to model a multivariate process with non-stationary marginal and dependence

    lancaster Repository record for Statistical models for dependent and non-stationary extreme events (opens in a new tab)

  7. Bankroto tikimybė nehomogeniniam rizikos atstatymo modeliu /

    … different distributions and satisfying certain dependence structures. The obtained property is used to prove the weak law of large numbers for an inhomogeneous renewal process. Additional corollaries are presented concerning elementary renewal theorems for the inhomogeneius renewal process. …

    vilnius Repository record for Bankroto tikimybė nehomogeniniam rizikos atstatymo modeliu / (opens in a new tab)

  8. Essays on Cross-Sectional and Network Dependence

    Cross-sectional dependence is a common phenomenon in economic data. It has attracted increasing attention recently and puts forward new challenges. This dissertation consists of three chapters that deal with several important econometric problems that arise when crosssectional dependence is …

    cambridge Repository record for Essays on Cross-Sectional and Network Dependence (opens in a new tab)

  9. Optimal bandwidth selection rule for kernel regression estimator with dependent variables

    … estimator have been developed under certain dependence structures for the process (X$\sb{\rm t}$,Y$\sb{\rm t}$). One of the crucial points in applying a kernel estimator is the choice of bandwidth. The main purpose of this work is to establish asymptotic optimality for a bandwidth selection …

    uiuc Repository record for Optimal bandwidth selection rule for kernel regression estimator with dependent variables (opens in a new tab)

  10. Dynamic dependence analysis : modeling and inference of changing dependence among multiple time-series

    … the problem of reasoning over evolving structures which describe the dependence among multiple, possibly vector-valued, time-series. Such problems arise naturally in variety of settings. Consider the problem of object interaction analysis. Given tracks of multiple moving objects one may …

    mit Repository record for Dynamic dependence analysis : modeling and inference of changing dependence among multiple time-series (opens in a new tab)

  11. Three Essays on Extremes and Non-Linearities in Asset Pricing

    … can be further characterized by a non-linear dependence structure. The second essay "Credit Cycle Dependent Spread Determinants in Emerging Sovereign Debt Markets", empirically estimates non-linear dependence structures of determinants of changes in sovereign bond spreads. Empirical results of …

    passau-thes Repository record for Three Essays on Extremes and Non-Linearities in Asset Pricing (opens in a new tab)

  12. Advances in spatial modeling for complex data with applications to symbolic data and spatial transcriptomics.

    … mismatch, and high-dimensional gene-level dependence structures. Specifically, three methodological contributions are proposed and evaluated. First, a harmonized kriging framework for Spatial Interval-Valued Data (SIVD) is proposed to improve spatial prediction by integrating information …

    baylor Repository record for Advances in spatial modeling for complex data with applications to symbolic data and spatial transcriptomics. (opens in a new tab)

  13. High-dimensional covariance estimation with applications to functional genomics

    … estimation facilitates the identification of dependence structures between molecular variables that shed light on the underlying biological processes. However, covariance estimation is generally difficult because high-throughput molecular experiments often generate high-dimensional and noisy …

    cambridge Repository record for High-dimensional covariance estimation with applications to functional genomics (opens in a new tab)

  14. High-Dimensional Functional Graphs and Inference for Unknown Heterogeneous Populations

    … on uncovering hidden patterns and network structures within such complex data. We utilize functional graphical models (FGMs) to explore the conditional dependence structure among random elements. We mainly focus on the following three research projects. The first project combines the …

    vt Repository record for High-Dimensional Functional Graphs and Inference for Unknown Heterogeneous Populations (opens in a new tab)

  15. A copula approach to sample selection modeling of treatment adherence and viral suppression among HIV patients on antiretroviral therapy (ART) in Namibia

    … ART in Namibia, to examine the presence of tail dependence in sample selection bias, and investigate the factors associated with viral suppression, viral load and ART adherence. The study used two datasets; HIV data of patients, aged above 16 years, on antiretroviral therapy in Erongo region and …

    namibia Repository record for A copula approach to sample selection modeling of treatment adherence and viral suppression among HIV patients on antiretroviral therapy (ART) in Namibia (opens in a new tab)

  16. Statistical methods for weather-related insurance claims

    … this work is the first to de- fine flexible dependence structures for such functions. In particular, the first approach considers a Bayesian framework and estimates are obtained by Markov chain Monte Carlo algorithms while the second approach is optimization-based. The last part of the thesis …

    lancaster Repository record for Statistical methods for weather-related insurance claims (opens in a new tab)

  17. Extreme value modelling of heatwaves

    … it is vital to explicitly model extremal dependence in time and space. An aim of this thesis is to develop extreme value methods that can accurately capture the temporal evolution of heatwaves. Specifically, this is the first to use a broad class of asymptotically motivated dependence

    lancaster Repository record for Extreme value modelling of heatwaves (opens in a new tab)

  18. Copulas and stochastic processes

    The modelling of dependence relations between random variables is one of the most widely studied subjects in probability theory and statistics. The most prominent models, particularly in practice, are presumably those which are based on correlation structures using second order moments. However, it …

    aachen Repository record for Copulas and stochastic processes (opens in a new tab)

  19. Stochastic Ground Motion Models for Uncertainty Quantification in Earthquake Engineering

    … design and risk management for civil infrastructures. An Uncertainty Quantification (UQ) framework is typically characterized by a probabilistic input, a computational model and quantities of interest used for decision-making. In the context of Earthquake Engineering, UQ aims to identify, …

    trento Repository record for Stochastic Ground Motion Models for Uncertainty Quantification in Earthquake Engineering (opens in a new tab)

  20. Recent Advances in Bayesian Copula Models for Mixed Data and Quantile Regression

    … marginal distributions under a multivariate dependence structure to define a valid joint distribution for a random vector. By estimating the joint distribution of a multivariate random vector, we are granted access to a myriad of information, from marginal properties and conditional …

    rice Repository record for Recent Advances in Bayesian Copula Models for Mixed Data and Quantile Regression (opens in a new tab)

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