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 34 for “"Generalized Additive Models"”.
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Penalized Regression Methods with Application to Generalized Linear Models, Generalized Additive Models, and Smoothing
Recently, penalized regression has been used for dealing problems which found in maximum likelihood estimation such as correlated parameters and a large number of predictors. The main issues in this regression is how to select the optimal model. In this thesis, Schall’s algorithm is proposed as an …
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Modelling sea surface temperature using generalized additive models for location scale and shape by boosting with autocorrelation
… data lead to incomplete information over time. Generalized additive models by boosting with location scale and shape (gamboostLSS) can be applied to overcome this problem. Moreover, they also deal with sparsity, irregular peaks, and autocorrelation in the data. We propose in this thesis extended …
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Predicting the Effects of Sedative Infusion on Acute Traumatic Brain Injury Patients
… relied upon linear and logistic regression models to address clinical research questions mostly because they produce highly interpretable results [1, 2]. These results contain valuable statistics such as p-values, coefficients, and odds ratios that provide healthcare professionals with …
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Distribution and abundance of Cape hakes (Merluccius capensis and Merluccius paradoxus) in relation to environmental variation in the Southern Benguela system
… Information Systems (GIS) techniques and Generalized Additive Models (GAM), nonparametric regressions without the assumptions of normality or linearity of traditional regression methods, were used to test the hypothesis that trends in hake (M. paradoxus and M. capensis) distribution and …
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Comparative Analysis of Machine Learning Models for ERCOT Short Term Load Forecasting
… machine learning (ML) and deep learning (DL) models for short-term load forecasting (STLF) in the Electric Reliability Council of Texas (ERCOT) grid. A dual comparative approach is employed, evaluating models based on temporal features alone as well as in combination with actual and forecasted …
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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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Identifying patients at high risk of death with novel computational biomarkers
… metrics have traditionally been based on simple models that incorporate various aspects of the medical history, presenting signs and symptoms, and lab values. More sophisticated methods, such as those based on signal processing and machine learning, form an attractive platform to build improved …
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Validation of Criteria Used to Predict Warfarin Dosing Decisions
… mathematical criteria for clinical agreement. Generalized additive models with smoothing spline estimates were calculated for each of the 14 criteria and compared to the smoothing spline estimate for the method using actual physician decisions (considered the "gold standard"). The area between …
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The ACEWEM computational laboratory : an integrated agent-based and statistical modelling framework for experimental designs of repeated power auctions
… optimisation learning algorithm based upon the Generalized Additive Models for Location Scale and Shape statistical framework. The ACEWEM framework, which integrates the agent-based modelling paradigm with formal statistical methods to represent better real-world decision rules, is designed to …
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Groundfish species diversity and assemblage structure in Icelandic waters during a period of rapid warming (1996-2007)
… og ára voru könnuð með GAM líkönum (generalized additive models). Fjögur meginsamfélög með útbreiðslu í suðvestur-djúpi, norður-djúpi, suður landgrunni og með víða útbreiðslu á landgrunni voru greind með klasagreiningu. Samfélög í köldum sjó djúpt norður af landinu voru óbreytt á …
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The Effects of Metronomic and Maximum-Tolerated Dose Chemotherapy in Colorectal Cancer Angiogenesis: A Combined Approach Using Endoscopic Diffuse Reflectance Spectroscopy and mRNA Expression
… MTD-treated tumors. In Chapter 3, we presented generalized additive models as an appropriate methodology to analyze the non-linear trends in longitudinal data that are commonly found in biomedical research. In Chapter 4, we sought to provide molecular context to the observed changes in perfusion …
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NBA Machine Learning for Game Outcome Prediction
… modeling, nonlinear extensions such as generalized additive models, and more granular possession-level or tracking-based data.
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Spatial Patterns and Correlates of Lower Respiratory Tract Illnesses in Children from Drakenstein, Western Cape
… and Kullddorf spatial scan statistics. Finally, generalized additive models were used to identify socio-demographic factors associated with pneumonia and wheeze. Results: A total of 947 children were included in analysis, with 406 cases of wheeze and 466 cases of pneumonia. Overall, cases and …
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Long-term spatiotemporal water quality and phytoplankton dynamics in Severn Sound, Ontario: a delisted great lakes area of concern
… differences and inherent data variability. Generalized Additive Mixed Models showed decreases in total phytoplankton biovolume and different significant drivers across seven major phytoplankton divisions. Permutational Multivariate Analysis of Variance (PERMANOVA) revealed that station, …
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Oligotrophication of downwind boreal lakes caused by oil sands-derived enhanced nutrient deposition
… unaffected reference region. Common trends from generalized additive models indicated that all algal groups declined after 1980 in P-limited lakes receiving deposition, coinciding with industrial intensification of the AOSR. In contrast, total algal abundance (as β-carotene and declining C/N …
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STATISTICAL METHODS FOR ANALYSIS OF HIGH-DIMENSIONAL NEUROIMAGING DATA
… brain characteristics and improve predictive models. Our second contribution serves to increase reproducibility and generalizability in neuroimaging data analyses. Neuroimaging data collected from multiple batches, such as different scanners, are increasingly necessary to obtain large sample …
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The environmental factors determining temporal distributions of cetaceans in Mossel Bay, South Africa
… Indian Ocean humpback dolphin (Sousa plumbea). Generalized additive models (GAM) were used to model the sighting rate of the common cetacean species in the area, by relating sighting rate to the environmental variables. Cow-calf groups and adults-only groups were modelled separately for humpback …
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Feeding Ecology of Invasive Catfishes in Chesapeake Bay Subestuaries
… plant and animal material. Logistic regression models reveal that Blue Catfish undergo significant ontogenetic diet shifts to piscivory at larger sizes (P<0.01) though the lengths at which these shifts occur varies by river system (500 – 900 mm total length; TL). Over 60% of Blue Catfish …
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An Evaluation of the Effects of Climate Variability on the Size of Wild North American Duck Eggs from 1859-2010
… varied by species from 0-8.7%. A set of a-priori generalized additive models were used to explore the correlations between egg metrics (i.e., length, width, and volume) and spring (March, April and May) weather, Palmer Drought Severity Index values, EPA ecological region, and year. Egg volume of …
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Bioenergetic and ecological consequences of diet variability in Atlantic croaker Micropogonias undulatus
… within the population and to the ecosystem. Generalized additive models revealed that the biomass of anchovy explained some of the variability in croaker occurrence and abundance in Chesapeake Bay. However, physical factors, specifically temperature, salinity, and seasonal dynamics were …
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