Physical Sciences and Mathematics Commons^™

Statistical Methods With A Focus On Joint Outcome Modeling And On Methods For Fire Science, Da Zhong Xi

Electronic Thesis and Dissertation Repository

Understanding the dynamics of wildfires contributes significantly to the development of fire science. Challenges in the analysis of historical fire data include defining fire dynamics within existing statistical frameworks, modeling the duration and size of fires as joint outcomes, identifying the how fires are grouped into clusters of subpopulations, and assessing the effect of environmental variables in different modeling frameworks. We develop novel statistical methods to consider outcomes related to fire science jointly. These methods address these challenges by linking univariate models for separate outcomes through shared random effects, an approach referred to as joint modeling. Comparisons with existing …

A Treatise Of Pd-Lgd Correlation Modelling, Wisdom S. Avusuglo Wsa

Electronic Thesis and Dissertation Repository

The provision in Paragraph 468 of Basel II Framework Document for calculating loss given default (LGD) requires that parameters used in Pillar I of Basel II capital estimations must be reflective of economic downturn conditions so that relevant risks are accounted for. This provision is based on the fact that the probability of default (PD) and LGD correlations are not captured in the proposed formula for estimating economic capital. To help quantify economic downturn LGD, the Basel Committee proposed establishing a functional relationship between long-run and downturn LGD.

To the best of our knowledge, the current proposed models that map …

Ranking Comments: An Entropy-Based Method With Word Embedding Clustering, Yuyang Zhang

Electronic Thesis and Dissertation Repository

Automatically ranking comments by their relevance plays an important role in text mining and text summarization area. In this thesis, firstly, we introduce a new text digitalization method: the bag of word clusters model. Unlike the traditional bag of words model that treats each word as an independent item, we group semantic-related words as clusters using pre-trained word2vec word embeddings and represent each comment as a distribution of word clusters. This method can extract both semantic and statistical information from texts. Next, we propose an unsupervised ranking algorithm that identifies relevant comments by their distance to the “ideal” comment. The …

Renewable-Energy Resources, Economic Growth And Their Causal Link, Yiyang Chen

Electronic Thesis and Dissertation Repository

This thesis examines the presence and strength of predictive causal relationship between re-newable energy prices and economic growth. We look for evidence by investigating the cases of Norway, New Zealand, and Canada’s two provinces of Alberta and Ontario. The usual vectorautoregressive model (VAR) and its various improved versions still assume constant parametersover time. We devise a Markov-switching VAR (MS-VAR) model in order to accommodate the observed time-dependent causal relation changes. Our proposed modelling approach is induced by the hidden Markov model methodologies in terms of an online parameter estimationthrough recursive filtering. The parameters of the MS-VAR model are governed by …

Classification-Based Method For Estimating Dynamic Treatment Regimes, Junwei Shen

Electronic Thesis and Dissertation Repository

Dynamic treatment regimes are sequential decision rules dictating how to individualize treatments to patients based on evolving treatments and covariate history. In this thesis, we investigate two methods of estimating dynamic treatment regimes. The first method extends outcome weighted learning from two-treatments to multi-treatments and allows for negative treatment outcome. We show that under two different sets of assumptions, the Fisher consistency can be maintained. The second method estimates treatment rules by a neural classification tree. A weighted squared loss function is defined to approximate the indicator function to maintain the smoothness. A method of tree reconstruction and pruning is …

Extensions Of Classification Method Based On Quantiles, Yuanhao Lai

Electronic Thesis and Dissertation Repository

This thesis deals with the problem of classification in general, with a particular focus on heavy-tailed or skewed data. The classification problem is first formalized by statistical learning theory and several important classification methods are reviewed, where the distance-based classifiers, including the median-based classifier and the quantile-based classifier (QC), are especially useful for the heavy-tailed or skewed inputs. However, QC is limited by its model capacity and the issue of high-dimensional accumulated errors. Our objective of this study is to investigate more general methods while retaining the merits of QC.

We present four extensions of QC, which appear in chronological …

Generalized 4/2 Factor Model, Yuyang Cheng

Electronic Thesis and Dissertation Repository

We investigate portfolio optimization, risk management, and derivative pricing for a factor stochastic model that considers the 4/2 stochastic volatility on the common/systematic factor as well as on the intrinsic factor. This setting allows us to capture stochastic volatility and stochastic covariation among assets. The model is also a generalization of existing models in the literature as it includes the mean reverting property and spillover effect to capture wider types of financial assets. At a theoretical level we identify conditions for well-defined changes of measure. A quasi-closed form solution within a 4/2 structured model is obtained for a portfolio optimization …

Issues Related To Framing And Interpretation Of Studies In The Orthopaedic Literature, Shgufta Docter

Electronic Thesis and Dissertation Repository

In research, appropriate statistical interpretation and methodology are essential to conduct quality work. To interpret results, p-values are frequently used in isolation, but this is insufficient as treatment effects, confidence intervals (CIs), and clinically important thresholds should also be reported. Further, the equality, superiority, non-inferiority, and equivalence frameworks have critical differences not well delineated in current literature. We conducted a systematic review of studies published in high-impact orthopaedic journals and examined a) how well studies interpreted the results of patient-reported outcome measures, and b) whether a consistent framework was used throughout studies. We found that the majority of studies do …

Edge-Cloud Iot Data Analytics: Intelligence At The Edge With Deep Learning, Ananda Mohon M. Ghosh

Electronic Thesis and Dissertation Repository

Rapid growth in numbers of connected devices, including sensors, mobile, wearable, and other Internet of Things (IoT) devices, is creating an explosion of data that are moving across the network. To carry out machine learning (ML), IoT data are typically transferred to the cloud or another centralized system for storage and processing; however, this causes latencies and increases network traffic. Edge computing has the potential to remedy those issues by moving computation closer to the network edge and data sources. On the other hand, edge computing is limited in terms of computational power and thus is not well suited for …

Point Process Modelling Of Objects In The Star Formation Complexes Of The M33 Galaxy, Dayi Li

Electronic Thesis and Dissertation Repository

In this thesis, Gibbs point process (GPP) models are constructed to study the spatial distribution of objects in the star formation complexes of the M33 galaxy. The GPP models circumvent the limitations of the two-point correlation function employed in the current astronomy literature by naturally accounting for the inhomogeneous distribution of these objects. The spatial distribution of these objects serves as a sensitive probe in understanding the star formation process, which is crucial in understanding the formation of galaxies and the Universe. The objects under study include the CO filament structure, giant molecular clouds (GMCs) and young stellar cluster candidates …

A Visual Analytics System For Investigating Multimorbidity Using Supervised Machine Learning, Maede Sadat Nouri

Electronic Thesis and Dissertation Repository

Patterns of multimorbidity are complex and difficult to summarise using static visualization techniques like tables and charts. We present a visual analytics system with the goal of facilitating the process of making sense of data collected from patients with multimorbidity. The system reveals underlying patterns in the data visually and interactively, which enables users to easily assess both prevalence and correlation estimates of different chronic diseases among multimorbid patients with varying characteristics. To do so, the system uses count-based conditional probability, binary logistic regression, softmax regression and decision tree models to dynamically compute and visualize prevalence and correlation estimates for …

Visualization And Joint Analysis Of Monitored Multivariate Spatio-Temporal Data With Applications To Forest Fire Modelling And Sports Analytics, Devan Becker

Electronic Thesis and Dissertation Repository

This thesis develops and applies novel techniques for the study of complex data structures with applications to wildland fire analytics and sports analytics. We consider situations where different models share information, including many different variables recorded simultaneously in aerial wildland fire fighting, how the frequency and severity of wildland fires are related, and how the shot locations of hockey players can be decomposed into spatial components that are shared across different players.

The first study analyzes flight patterns while fighting a wildland fire using several outlier detection techniques. These techniques applied several definitions of ``outlier'' to determine whether or not …