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 20 of 64 for “"Additive models"”.
-
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 …
-
Modelling sea surface temperature using generalized additive models for location scale and shape by boosting with autocorrelation
… 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 gamboostLSS …
-
Nonparametric High-dimensional Models: Sparsity, Efficiency, Interpretability
… model by jointly training simpler base models. It examines three types of ensemble methods: additive models, tree ensembles, and mixtures of experts. Each ensemble method is characterized by a specific structure: additive models can involve base learners with single or pairwise …
-
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 …
-
Falling Down: The Influence Of Traffic Patterns And Availability Of Emergency Medical Service Personnel On The Lethality Of Violent Encounters
… Memphis, TN, Cincinnati, OH, and Richmond, VA. Additive models of logistic regression analysis revealed that fire/rescue availability, firearm use, incidents arising out of arguments, outdoor locations, and victim gender are the most consistent predictors of whether or not a violent incident …
-
Distribution and abundance of Cape hakes (Merluccius capensis and Merluccius paradoxus) in relation to environmental variation in the Southern Benguela system
… 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 abundance are …
-
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 …
-
Array methods in statistics with applications to the modelling and forecasting of mortality
… and show how these methods can be applied in additive models even when the data do not have a standard array structure. Finally we discuss the Lee-Carter model and show how we fulfilled the requirements of the CASE studentship. Our main contributions are: firstly we extend the array methods of …
-
Understanding and supporting pricing decisions using multicriteria decision analysis: an application to antique silver in South Africa
… into this application area. Multi-attribute additive models are constructed, with attribute partial value functions elicited using different methods: directly (bisection methods), indirectly (MACBETH and linear interpolation) and with discrete choice experiments. The applicability and …
-
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 …
-
Practical military applications of timetabling, path planning, and time-varying networks for maximizing mission success and minimizing risk
… under review by Networks. We build a "threat-additive" approach to measuring the risk incurred by a ship navigating a naval minefield. We employ this approach, both as an integer program and as an A* search, to identify minimum-risk paths that may not be found by traditional "edge-additive" …
-
Coastal water level prediction: a comparative study of statistical and machine learning techniques for time series forecasting
… of the influencing factors. Many existing models and projects focus on long-term trends in coastal water levels particularly in terms of climate change and global warming. This project investigated the application of time series analysis with exogenous meteorological variables to the task …
-
Sexual segregation and abundance trend of whale sharks in southern Mozambique
… and most have a strong male bias. Generalised additive models were constructed on a 15-year dataset (2005–2019), from Praia do Tofo, Mozambique, to investigate sexual segregation in relation to environmental conditions. Temporal (year, day of year), and biophysical (sea surface temperature, …
-
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 …
-
Validation of Criteria Used to Predict Warfarin Dosing Decisions
… 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 the criteria …
-
Somatic condition, growth and distribution of Atlantic bluefin tuna (Thunnus thynnus) in the Gulf of Maine
… as a foraging ground. A series of linear and additive models fitted to multiple fishery dependent datasets identified significant declines in the somatic condition of Atlantic bluefin tuna in the Gulf of Maine. Significant changes in the somatic condition of Atlantic herring, increases in the …
-
The ACEWEM computational laboratory : an integrated agent-based and statistical modelling framework for experimental designs of repeated power auctions
… 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 be the …
-
CHANGES IN THE MORPHOLOGY OF WIDGEON GRASS (RUPPIA MARITIMA) WITH THE ONSET OF REPRODUCTION AND IMPACTS ON FISH ASSEMBLAGES AT THE CHANDELEUR ISLANDS, LA
… non-reproductive meadows. Additionally, general additive models were used to predict drivers of fish assemblage metrics. Results indicate that <em>R. maritima</em> was distributed along the entire length of North Chandeleur Island, but reproductive plants were located in the central, protected …
-
Constructing growth reference curves for a cohort of South African children
… semi-parametric methods within the Generalised Additive Models for Location, Scale and Shape (GAMLSS) framework. Various distributions for the growth measurements were compared as well as various curve smoothing approaches for the longitudinal profiles, including cubic splines, fractional …
-
Investigating ecosystem-level effects of gillnet bycatch in Lake Erie: implications for commercial fisheries management
… implications. Three classification tree models, a conditional inference tree and two exhaustive search-based trees, were constructed using the PIS data to estimate the probability of obtaining lake sturgeon bycach under specific environmental and gillnet fishing conditions. Lake sturgeon …
Page 1 of 4