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 “"Models, Statistical"”.
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Computer aided reliability based design of ring-stiffened cylindrical shells under external pressure
… results were compiled, corresponding to machined models failing by elastic General Instability. Finite Element (FE) meshes were validated in view of mesh studies and experimental results and further used in parametric studies. The effect of boundary conditions on the elastic General Instability …
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La flessibilizzazione del mercato del lavoro italiano, conseguenze economiche ed occupazionali per le giovani coorti
… dimension. As regard methods, we apply FE panel models, statistical matching and multivariate analyses. Low wage and earnings transitions are analyzed using ECHP dataset and applying RE logit estimations. Moreover, the occupational consequences of atypical job (versus unemployment) are …
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Fault detection, isolation, and recovery for autonomous parafoils
… generated from observers and other system models. Statistical methods are applied to evaluate these residuals and determine whether a fault has occurred, given a priori knowledge of how the system behaves in the presence of faults. This work develops fault recovery strategies that are …
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CompactCities : analyzing the urban spatial structure in cities with growth restrictions
… claims based on literature review, economic models, statistical tools, and by generating hypothetical transport scenarios. Based on this analysis, I conclude that high-density development by itself has little significant association with the benefits claimed above. Further growth control …
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Shape and Function Analysis in Large Cardiac MRI Datasets
… on the problem of comparing the mathematical models derived from these images. This is often termed building an atlas of the heart which, in this context, represents a collection of maps or compendiumof knowledge derived from a population of models. Statistical atlases are important because …
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Bayesian Spatial Analysis of High Throughput Sequencing Data
The past decade has witnessed the development and wide use of high-throughput sequencing data in biology. The recent advancement of RNA Sequencing (RNA-Seq) coupled with other molecular technologies such as methylated RNA immunoprecipitation (MeRIP) and spatial barcoding has delivered more …
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Theoretical epidemiology analysis of Plague, Polio, and Covid-19 outbreak
… overview of the different types of mathematical models utilized in infectious disease modeling, focusing on their application in studying the spread of complex diseases such as Plague, Polio, and Covid-19. Mathematical models can capture the intricacies of disease transmission by incorporating …
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Cortical thickness estimation of the proximal femur from multi-view dual-energy X-ray absorptiometry
… accomplishes the same task by deforming statistical shape and thickness models, both trained using Principal Component Analysis (PCA). Three training cohorts are used to investigate (a) the estimation efficacy as a function of the diversity in the training set and (b) the possibility of …
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How much compliance is enough? Examining the effect of different definitions of compliance on estimates of treatment efficacy in randomized controlled trials.
… Based on principal stratification, these models classify subjects who receive an adequate amount of the treatment as potential compliers and compares them to control subjects who have an equal probability of being classified as compliers if they had been randomized to treatment. No studies …
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Development of a Numerical Model to Analyze the Condition of Prestressed Concrete Cylinder Pipe (PCCP)
… by scholars and engineers in developing models to evaluate the condition of PCCP. There are mainly two types of models: statistical models, and numerical models using finite element method. Statistical models consider only a few factors, such as pipe age and failure rate, to predict the …
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Finding a Better Confidence Interval for a Single Regression Changepoint Using Different Bootstrap Confidence Interval Procedures
<p>Recently a number of papers have been published in the area of regression changepoints but there is not much literature concerning confidence intervals for regression changepoints. The purpose of this paper is to find a better bootstrap confidence interval for a single regression changepoint. …
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An Individualized Allocation Algorithm for Use with Bayesian Hierarchical Models
Statistical models have widespread use in data science, and while some datasets can be mod- eled well using one model other applications may require multiple models to accurately capture mechanisms within different subgroups of the dataset. Which subjects are assigned to each model in turn impacts …
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Confidence Interval for the Mean of a Beta Distribution
<p>Statistical inference for the mean of a beta distribution has become increasingly popular in various fields of academic research. In this study, we developed a novel statistical model from likelihood-based techniques to evaluate various confidence interval techniques for the mean of a beta …
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Wald Confidence Intervals for a Single Poisson Parameter and Binomial Misclassification Parameter When the Data is Subject to Misclassification
<p>This thesis is based on a Poisson model that uses both error-free data and error-prone data subject to misclassification in the form of false-negative and false-positive counts. We present maximum likelihood estimators (MLEs), Fisher's Information, and Wald statistics for Poisson rate parameter …
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PERFORMANCE OF THE TWO SAMPLE LIKELIHOOD RATIO TEST UNDER A NESTED DIRICHLET: A SIMULATION STUDY
… 2 outlines the Dirichlet and Nested Dirichlet models and the associated likelihood ratio test (LRT) framework. Chapter 3 presents a simulation study to evaluate the Type I error performance of the LRT under varying sample sizes, mean vectors, and precision parameters, providing insight into its …
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Macroeconomic Forecasting: Statistically Adequate, Temporal Principal Components
… indicators. At the outset, PCA is viewed as a statistical model derived from the reparameterization of the Multivariate Normal model in Spanos (1986). To motivate a PCA forecasting framework prioritizing sound model assumptions, it is demonstrated, through simulation experiments, that model …
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Examination and Comparison of the Performance of Common Non-Parametric and Robust Regression Models
… of Common Non-Parametric and Robust Regression Models</p> <p>By</p> <p>Gregory Frank Malek</p> <p>Stephen F. Austin State University, Masters in Statistics Program,</p> <p>Nacogdoches, Texas, U.S.A.</p> <p><a href="mailto:g_m_2002@live.com">g_m_2002@live.com</a></p> <p>This work investigated …
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Generalized Weibull and Inverse Weibull Distributions with Applications
… are introduced. The GNMW contains several sub-models including the new modified Weibull (NMW), generalized modified Weibull (GMW), modified Weibull (MW), Weibull (W) and exponential (E) distributions, just to mention a few. The class of WPIW distributions contains several models such as: …
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