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.
Results
Showing 1 to 12 of 12 for “"Resampling Techniques"”.
-
Aplicação de técnicas estatísticas de reamostragem em hidrologia
… Both Bootstrap and Jackknife are called Resampling Methods. The Bootstrap is applied to decide the amount of information needed for modeling the one hundred year flood. It is shown that the resampling techniques are reasonably accurate methods and can be applied to define confidence …
-
Reassessment of the Red Drum Stock in Mississippi Coastal Waters: The Role of Ages 3-5 Year-Class Fish
… estimates. These findings attest to the value of resampling techniques and sensitivity analysis when choosing appropriate precautionary reference points and investigating the integrity of data collection methods.</p>
-
Impact of Specification Changes on Chloride Induced Corrosion Service Life of Virginia Bridge Decks
… deterministic model using statistical computing techniques, including resampling techniques such as the parametric and simple bootstrap. Emphasis was placed on the diffusion portion of the diffusion-cracking model, but advances can be readily included for the time for corrosion deterioration …
-
Testing for Structural Change: Evaluation of the Current Methodologies, a Misspecification Testing Perspective and Applications
… unique, I develop a testing procedure using a resampling scheme which is based on a Maximum Entropy replication algorithm. The proposed misspecification testing procedure relies on resampling techniques to enhance the informational content of the observed data in an attempt to capture …
-
Service Life Modeling of Virginia Bridge Decks
… corrosion of the reinforcing steel. Monte Carlo resampling techniques were used to integrate the statistical nature of the input variables into the model. This is an improvement on previous deterministic models in that the effect of highly variable input parameters is reflected in the service …
-
The Testing and Verification of a Nanomembrane Based Pressure Sensor for Small-Scale Underwater Pressure Measurements
… and analyzed with selected filtering and resampling techniques to eliminate background noises. First, the sensors were calibrated to ensure their linearity and to determine their pressure sensitivities. Then, using bench-top testing rigs and a water tunnel, the sensor performance was …
-
Predictive Modelling Approach to Data-Driven Computational Preventive Medicine
… machine-learning methods, data preprocessing techniques, models’ training estimation and optimisation, and performance evaluation, yielding a novel computational data-driven framework, Octopus. Midway through this research, this thesis advances research in preventive medicine and data mining …
-
THE CRISIS OF LOCAL JOURNALISM: DEATH BY A THOUSAND PAPER CUTS
… class imbalance in the data through various resampling techniques, the analysis finds that Random Forest combined with SMOTEENN is the strongest performer. The most significant predictor is the interaction between population density and GDP, highlighting how economic vulnerability intersects …
-
Evaluating Factors Contributing to Crash Severity Among Older Drivers: Statistical Modeling and Machine Learning Approaches
… statistical methods and machine learning techniques to dissect this critical issue from multiple angles. The initial study within the dissertation employs multilevel ordinal logistic regression to assess crash severity among older drivers, revealing the complex interplay of various factors …
-
Novel Statistical Methods for Mediation Analysis with High-dimensional Omics Mediators
… distribution, eliminating the need for resampling techniques like bootstrapping. The proposed method achieves coverage probability comparable to existing methods while significantly improving computational efficiency. Next, a novel meta-analysis framework is developed to estimate the …
-
Frequentist-Bayesian Hybrid Tests in Semi-parametric and Non-parametric Models with Low/High-Dimensional Covariate
… is treated through Fourier transformation. Resampling techniques are applied to construct the empirical distribution of test statistic to reduce the effect of non-normal distribution. A simulation study suggests our approach performs better than the alternative method, the Adaptive Neyman …
-
Analysis and Prediction of the Commuting Mode Choices in England Using Bayesian Networks
… model’s stability is validated using bootstrap resampling techniques, different data sources, and temporal segmentation of the National Travel Survey dataset, ensuring the reliability of the proposed network structure. This may also shed light on potential improvements in population synthesis BN …