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 25 for “"generalized additive model"”.
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Bayesian generalized additive model selection
Generalized additive models (GAMs) offer a parsimonious, flexible and interpretable framework for regression, particularly when handling a large numbers of candidate predictors. This thesis addresses the GAM variable selection problem: categorizing each candidate predictor's effect type to be …
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Spatiotemporal Generalized Additive Model: Investigating Weather-Related Road Crashes in Southern Finland
… Many types of statistical and machine learning models seek to quantify the relationship between different meteorological parameters and accident risk. This thesis presents a spatiotemporal generalized additive model to explain which weather conditions increase the risk of a crash in the Finnish …
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Scalable black-box model explainability through low-dimensional visualizations
… visual intuitive explanations for how black-box models work. The first is a projection pursuit-based method that seeks to provide data-point specific explanations. The second is a generalized additive model approach that seeks to explain the model on a more holistic level, enabling users to …
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Spatio-temporal data modeling with applications to weather and disease
… cases, it is beneficial to use spatio-temporal modeling to account for trends and the correlation of nearby observations. This thesis explores applications to spatio-temporal modeling. First, a method is developed to model the marginal distribution of spatial extreme values at a large scale …
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Fast and stable smoothing spline analysis of variance models for large samples with applications to electroencephalography data analysis
… smoothing spline analysis of variance (SSANOVA) model are computationally expensive, making a generalized additive model (GAM) the preferred method for multivariate smoothing. In this thesis, I propose various approximations and algorithms to stabilize and speed-up the fitting of two-way (or …
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Modelling the spatial distribution of three marine fish species in the southern Benguela
… from scientific trawl surveys, this study used Generalized Additive Model (GAM) and Krigging with External Drift (KED) statistical techniques to determine the spatial distribution of three marine fish species of commercial interest: Merluccius capensis, Merluccius paradoxus, and Thyrsites atun, …
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Peatland burning identification among other wildfires across different ecozones in Canada
… Mann-Whitney U test, K-means clustering, and generalized additive model (GAM) to identify the contribution of peat presence to fire behaviors. Key findings demonstrate that fires on peatland are significantly more intense, longer-lasting, and associated with higher carbon emissions. Even …
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Computational, statistical and graph-theoretical methods for disease mapping and cluster detection
… based on time-series data, we introduce a generalized additive model that maintains constant specificity on various time scales.
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The prison of online performance: social achievement goals as a buffer between social media and digital stress
… and social purposes. Data were analyzed using a Generalized Additive Model (GAM) to account for non-linear and interactive effects. Findings revealed that DEM significantly moderated the relationship between SMU and approval anxiety, with higher DEM associated with greater anxiety as SMU …
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Predicting Spatial Variability of Soil Organic Carbon in Delmarva Bays
… (1) accuracy of topographic-based non-linear models for predicting SOC; and (2) the effect of analytic strategies and soil condition on performance of spectral-based models for predicting SOC. SOC data came from 28 agriculturally converted Delmarva Bays sampled down to 1 meter. R2 was used as …
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Developing robust statistical scoring methods for use in child assessment tools
… classical methods including generalised linear models, simple sum, Z-score, Log Age Ratio and Item Response Theory scoring methods in this child development context using binary responses only was carried out. While evaluating the pros and cons of each method, extensions to the current scoring …
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Scientific Acoustic Data from Commercial Fishing Vessels: Eastern Bering Sea Walleye Pollock (Theragra chalcogramma)
… that was used in a spatially explicit depletion model to examine the temporal and spatial intensity of the winter fishery and found that fishery exploitation rates inside Steller sea lion critical habitat was higher than outside. The lack of comprehensive survey data on pollock distribution in …
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Next-Generation Intelligent Portfolio Management
… framework that leverages Transformer-based models and Large Language Models (LLMs) to enhance return predictions and sentiment extraction from extensive financial texts coupled with robust DRL trading agents to optimize portfolio performance. We introduce an adaptive retrieval-augmented …
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An investigation of spatial-temporal diel changes in Loligo reynaudii catch rates in the commercial squid jig fishery of South Africa
… distribution: this study employed statistical modelling to specifically investigate whether, on the commercial squid jig fishing grounds of South Africa, there is: (1) an effect of diel period on chokka CPUE; (2) seasonal variation in any effects of diel period on CPUE; and (3) spatial …
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Conceptual, algorithmic, and statistical exploration of relations between runoff generation, stream geomorphology, and watershed topography in West Texas
… ordinary and innocuous highway bridge. 2. A Generalized Additive Model (GAM) for Stream Discharge and Velocity Estimation from Stream Geomorphology A discussion of work that was inspired by and resulted from discussions between the author and colleagues from various universities and from the …
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Változószelekciós algoritmusok vizsgálata általánosított additív modellekben – Egy új, hibrid metaheurisztika elemzése
… arra, hogy a legpontosabb becslést szolgáltató modellekben a használt magyarázóváltozók hatásai az eredményváltozóra nehezen, vagy egyáltalán nem visszafejthetők. Viszont, bizonyos gyakorlati szituációkban a gépi tanulás legfontosabb eredménye nem feltétlenül a minél pontosabb becslés …
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Cluster-enhanced Ensemble Learning for Mapping Surface Ozone in China
… elbow method. Next, various ensemble learning models, including penalized linear models (LASSO), multi-layer perceptron neural networks (MLP), random forests (RF), LightGBM, XGBoost, and CatBoost, are applied to simulate ozone concentrations. Hyperparameters are optimized via randomized grid …
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Improving Clinical Prediction Models with Statistical Representation Learning
… compromise the validity of standard predictive models which often expect clean and complete data. As such, alleviating the negative impacts of real-world data challenges is of great significance and constitutes the overarching goal of this dissertation, which investigates novel strategies to (i) …
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Bayesian sparsity learning with variational automatic relevance determination
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-03-28 without embargo terms
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