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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 105 for “"bayesian estimation"”.
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Bayesian estimation of self-similarity exponent
Estimation of the self-similarity exponent has attracted growing interest in recent decades and became a research subject in various fields and disciplines. Real-world data exhibiting self-similar behavior and/or parametrized by self-similarity exponent (in particular Hurst exponent) have been …
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Bayesian Estimation for White Light Interferometry
… steps of pre- and postprocessing within Bayesian inference. An adept formulation of the prior allows for the exact computation of the height estimate, obviating the need for stochastic sampling or simulation methods. In conventional surface estimation for white light interferometry, a …
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Essays on DSGE Models and Bayesian Estimation
This thesis explores the theory and practice of sovereignty. I begin with a conceptual analysis of sovereignty, examining its theological roots in contrast with its later influence in contestations over political authority. Theological debates surrounding God’s sovereignty dealt not with the …
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Bayesian Estimation of Multi-unidimensional Graded Response IRT Models
… normal ogive GRM under the fully Bayesian framework via the use of Markov chain Monte Carlo (MCMC). The performance of the proposed model was evaluated using the Monte Carlo simulations. It was further compared with conventional GRMs under simulated and real test situations. …
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Uncertainty Analysis of Biological Nonlinear Models Based on Bayesian Estimation
… models, especially biological models. Parameter estimation, random number generation, and uncertainty analysis are closely related in Monte Carlo simulation based model assessment. All three aspects are discussed in this study. Because of the complexity of models and inflexibility of estimation …
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Bayesian estimation of Thurstonian ranking models based on the Gibbs sampler
… a small number of objects. This paper presents a Bayesian approach to the estimation of the parameters of Thurstonian ranking models based on Gibbs sampling methods. Monte Carlo studies demonstrate that the Gibbs sampler is applicable to ranking problems with a large number of objects. To improve …
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Stochastic chaos and thermodynamic phase transitions : theory and Bayesian estimation algorithms
… techniques based on Volterra series modeling and Bayesian non-linear filtering to distinguish between dynamic noise and measurement noise. We quantify how much of the system's ergodic behavior can be attributed to intrinsic deterministic dynamical properties vis-a-vis inevitable extrinsic noise …
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K-distribution fading models for Bayesian estimation of an underwater acoustic channel
Current underwater acoustic channel estimation techniques generally apply linear MMSE estimation. This approach is optimal in a mean square error sense under the assumption that the impulse response fluctuations are well characterized by Gaussian statistics, leading to a Rayleigh distributed …
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Bayesian Estimation of Material Properties in Case of Correlated and Insufficient Data
… to the field of experimental mechanics. Bayesian approaches as Markov-chain Monte Carlo (MCMC) methods demonstrated to be reliable and suitable tools to process data, describing probability distributions and uncertainty bounds for investigated parameters in absence of explicit inverse …
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K-distribution fading models for Bayesian estimation of an underwater acoustic channel
Current underwater acoustic channel estimation techniques generally apply linear MMSE estimation. This approach is optimal in a mean square error sense under the assumption that the impulse response fluctuations are well characterized by Gaussian statistics, leading to a Rayleigh distributed …
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Reliable Prediction Intervals and Bayesian Estimation for Demand Rates of Slow-Moving Inventory
Application of multisource feedback (MSF) increased dramatically and became widespread globally in the past two decades, but there was little conceptual work regarding self-other agreement and few empirical studies investigated self-other agreement in other cultural settings. This study developed a …
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Bayesian estimation of restricted latent class models: Extending priors, link functions, and structural models
… and applications. We begin by developing novel Bayesian methodology that uses a less restrictive monotonicity condition when estimating the underlying latent structure and attributes. Under the formulation, we make further enhancements by extending the framework to the logit-link function …
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Autonomous Aerial Localization of Radioactive Point Sources via Recursive Bayesian Estimation and Contour Analysis
… interest. Two algorithms—a grid-based recursive Bayesian estimator and a novel radiation contour analysis method—are presented to estimate the position of radioactive sources using simple gross gamma ray event count data from a nondirectional radiation detector. The latter procedure also …
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Exploiting Signals of Opportunity for High-Precision PNT: Optimized Bayesian Estimation Across 5G and LEO Networks
… architecture is currently hindered by profound estimation and geometric bottlenecks. In the terrestrial domain, the measurement quality of 5G signals fluctuates drastically due to rapidly changing spatial geometry, varying signal-to-noise ratios (SNR), and kinematic Doppler shifts, frequently …
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A Comparison of Bayesian Estimation Techniques in a Multidimensional Two-Parameter Partial Credit Item Response Model
<p>Bayesian estimation methods have shown better performance than the traditional Marginal Maximum Likelihood (MML) estimation method for parameter estimation in relatively simple item response models. However, extant literature is lacking on the investigation of Bayesian parameter estimation …
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Bayesian estimation of stochastic volatility models with fat tails and correlated errors applied to the South African financial market
… we apply Markov Chain Monte Carlo methods in the Bayesian framework to estimate Stochastic Volatility models using South African financial market data. A single move Gibbs sampler is used to sample parameters from the posterior distribution. Volatility is used as measure of an asset's risk. It is …
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Interferometry in diffusive systems: Theory, limitation to its practical application and its use in Bayesian estimation of material properties
… reservoir layer between two impermeable layers. Bayesian statistical inversion of the data obtained by interferometry was then used to estimate the fluid diffusivity (and permeability) along with associated uncertainties. The inversion results determined the estimated model parameters in the form …
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A tripartite study on Bayesian estimation of photosynthetically active radiation, impacts of future climate, and adaptation strategies on crop production: a spatial model framework for the Eastern Kansas River Basin
… model accuracy, while also documenting new estimation methods. The ultimate goal of this dissertation is to develop climate change adaptation strategies for rainfed and irrigated maize production in EKSRB using a combination of county-level and fine-scale spatial protocols. We quantified …
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A Bayesian solution to non-convergence of crossed random effects models
… and stimuli; however, maximum likelihood estimation (MLE) and restricted maximum likelihood (REML) estimation often encounter convergence problems, which in turn lead to researchers fitting simpler models (e.g., only random intercepts). If the random effect structure is too simple, tests …
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Essays on the Bayesian inequality restricted estimation
Bayesian estimation has gained ground after Markov Chain Monte Carlo process made it possible to sample from exact posterior distributions. This research aims at contributing to the ongoing debate about the relative virtues of the Frequentist and Bayesian theories by concentrating on the …
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