Sparse Model Selection Using Information Complexity, 2022 University of Tennessee, Knoxville
Sparse Model Selection Using Information Complexity, Yaojin Sun
Doctoral Dissertations
This dissertation studies and uses the application of information complexity to statistical model selection through three different projects. Specifically, we design statistical models that incorporate sparsity features to make the models more explanatory and computationally efficient.
In the first project, we propose a Sparse Bridge Regression model for variable selection when the number of variables is much greater than the number of observations if model misspecification occurs. The model is demonstrated to have excellent explanatory power in high-dimensional data analysis through numerical simulations and real-world data analysis.
The second project proposes a novel hybrid modeling method that utilizes a mixture …
Penalized Estimation Of Autocorrelation, 2022 Clemson University
Penalized Estimation Of Autocorrelation, Xiyan Tan
All Dissertations
This dissertation explored the idea of penalized method in estimating the autocorrelation (ACF) and partial autocorrelation (PACF) in order to solve the problem that the sample (partial) autocorrelation underestimates the magnitude of (partial) autocorrelation in stationary time series. Although finite sample bias corrections can be found under specific assumed models, no general formulae are available. We introduce a novel penalized M-estimator for (partial) autocorrelation, with the penalty pushing the estimator toward a target selected from the data. This both encapsulates and differs from previous attempts at penalized estimation for autocorrelation, which shrink the estimator toward the target value of zero. …
Deep Depression Prediction On Longitudinal Data Via Joint Anomaly Ranking And Classification, 2022 Singapore Management University
Deep Depression Prediction On Longitudinal Data Via Joint Anomaly Ranking And Classification, Guansong Pang, Ngoc Thien Anh Pham, Emma Baker, Rebecca Bentley, Anton Van Den Hengel
Research Collection School Of Computing and Information Systems
A wide variety of methods have been developed for identifying depression, but they focus primarily on measuring the degree to which individuals are suffering from depression currently. In this work we explore the possibility of predicting future depression using machine learning applied to longitudinal socio-demographic data. In doing so we show that data such as housing status, and the details of the family environment, can provide cues for predicting future psychiatric disorders. To this end, we introduce a novel deep multi-task recurrent neural network to learn time-dependent depression cues. The depression prediction task is jointly optimized with two auxiliary anomaly …
Intra-Hour Solar Forecasting Using Cloud Dynamics Features Extracted From Ground-Based Infrared Sky Images, 2022 University of New Mexico
Intra-Hour Solar Forecasting Using Cloud Dynamics Features Extracted From Ground-Based Infrared Sky Images, Guillermo Terrén-Serrano
Electrical and Computer Engineering ETDs
Due to the increasing use of photovoltaic systems, power grids are vulnerable to the projection of shadows from moving clouds. An intra-hour solar forecast provides power grids with the capability of automatically controlling the dispatch of energy, reducing the additional cost for a guaranteed, reliable supply of energy (i.e., energy storage). This dissertation introduces a novel sky imager consisting of a long-wave radiometric infrared camera and a visible light camera with a fisheye lens. The imager is mounted on a solar tracker to maintain the Sun in the center of the images throughout the day, reducing the scattering effect produced …
Are Long-Period Exoplants Around Cool Stars More Common Than We Thought?, 2022 Louisiana State University and Agricultural and Mechanical College
Are Long-Period Exoplants Around Cool Stars More Common Than We Thought?, Emily Jane Safron
LSU Doctoral Dissertations
The Kepler mission has been the catalyst for discovery of nearly 5,000 confirmed and candidate exoplanets. The majority of these candidates orbit Sun-like stars, and have orbital periods comparable to or shorter than that of the Earth, due to the selection bias inherent in the transit method and the limitations of automated transit search algorithms. We aim to develop a richer understanding of the population of exoplanets around the lowest-mass stars, the M spectral type. We are particularly interested in exoplanets with long orbital periods, which are difficult or impossible to find using standard transit search algorithms. In our study, …
Impact Of Loss To Follow-Up And Time Parameterization In Multiple-Period Cluster Randomized Trials And Assessing The Association Between Institution Affiliation And Journal Publication, 2022 University of Massachusetts Amherst
Impact Of Loss To Follow-Up And Time Parameterization In Multiple-Period Cluster Randomized Trials And Assessing The Association Between Institution Affiliation And Journal Publication, Jonathan Moyer
Doctoral Dissertations
Difference-in-difference cluster randomized trials (CRTs) use baseline and post-test measurements. Standard power equations for these trials assume no loss to follow-up. We present a general equation for calculating treatment effect variance in difference-in-difference CRTs, with special cases assuming loss to follow-up with replacement of lost participants and loss to follow-up with no replacement but retaining the baseline measurements of all participants. Multiple-period CRTs can represent time as continuous using random coefficients (RC) or categorical using repeated measures ANOVA (RM-ANOVA) analytic models. Previous work recommends the use of RC over RM-ANOVA for CRTs with more than two periods because RC exhibited …
Liquidity Commonality With Factor Models, 2022 The Graduate Center, City University of New York
Liquidity Commonality With Factor Models, Ernesto Garcia Iii
Dissertations, Theses, and Capstone Projects
Market microstructure research has recently devoted attention to a phenomenon called commonality in liquidity. In this dissertation, I will analyze commonality in liquidity using a novel factor model approach and a generalized definition of commonality in liquidity. This analysis will show that commonality in liquidity is rarely a marketwide phenomenon and is mostly restricted to stocks with a large market capitalization. Additionally, commonality in liquidity is a very recent phenomenon whose appearance coincides with a rise in passive investing after the Dotcom Bubble burst and, more so, after the 2008 Financial Crisis. I will present evidence that suggests commonality in …
Slices Of The Big Apple: A Visual Explanation And Analysis Of The New York City Budget, 2022 The Graduate Center, City University of New York
Slices Of The Big Apple: A Visual Explanation And Analysis Of The New York City Budget, Joanne Ramadani
Dissertations, Theses, and Capstone Projects
As a component of government, budgets are fundamental not only to improving the quality of a shared society, but also to understanding what our government officials consider to be their priorities. However, most budgets can be difficult to understand, using terms that are not familiar to people who have not studied finance or economics. To that end, Slices of the Big Apple is an interactive, centralized narrative website that uses visualizations at its core in order to: 1) facilitate a holistic understanding of the New York City government budget for NYC residents; and 2) conduct a five-year analysis of Community …
Realtime Event Detection In Sports Sensor Data With Machine Learning, 2022 University of New Hampshire, Durham
Realtime Event Detection In Sports Sensor Data With Machine Learning, Mallory Cashman
Honors Theses and Capstones
Machine learning models can be trained to classify time series based sports motion data, without reliance on assumptions about the capabilities of the users or sensors. This can be applied to predict the count of occurrences of an event in a time period. The experiment for this research uses lacrosse data, collected in partnership with SPAITR - a UNH undergraduate startup developing motion tracking devices for lacrosse. Decision Tree and Support Vector Machine (SVM) models are trained and perform with high success rates. These models improve upon previous work in human motion event detection and can be used a reference …
Estimating The Statistics Of Operational Loss Through The Analyzation Of A Time Series, 2022 Virginia Commonwealth University
Estimating The Statistics Of Operational Loss Through The Analyzation Of A Time Series, Maurice L. Brown
Theses and Dissertations
In the world of finance, appropriately understanding risk is key to success or failure because it is a fundamental driver for institutional behavior. Here we focus on risk as it relates to the operations of financial institutions, namely operational risk. Quantifying operational risk begins with data in the form of a time series of realized losses, which can occur for a number of reasons, can vary over different time intervals, and can pose a challenge that is exacerbated by having to account for both frequency and severity of losses. We introduce a stochastic point process model for the frequency distribution …
Lake Huron Shoreline Analysis, 2022 Wilfrid Laurier University
Lake Huron Shoreline Analysis, Shubham Satish Nandanwar
Theses and Dissertations (Comprehensive)
Lake Huron is a popular tourist destination and is home to several businesses and residents. Since the shoreline is dynamic and is subject to change over the years due to several factors such as a change in water level, soil type, human encroachment, etc., these locations tend to encounter floods due to increased water levels and wind speed. This causes erosion and loss to the properties along the shoreline.
This study is based on two areas of interest named Pinery Provincial Park and Sauble Beach which are located on the shoreline of Lake Huron where Pinery Provincial Park is a …
Análisis De Los Días De Mora Para La Cartera De Un Producto Financiero En Colombia, Una Aproximación A Partir De Las Series De Tiempo (2013 - 2018), 2022 Universidad de La Salle, Bogotá
Análisis De Los Días De Mora Para La Cartera De Un Producto Financiero En Colombia, Una Aproximación A Partir De Las Series De Tiempo (2013 - 2018), Eleny Kottaridis Fernandez
Economía
La morosidad sobre la cartera de consumo evidencia un patrón que debe ser considerado en la toma de decisiones de las entidades financieras para una adecuada administración del riesgo crediticio teniendo en cuenta su alta volatilidad. En efecto, un desempeño económico desfavorable relacionado con algunos sectores financieros, las bajas tasas de crecimiento económico y mayores niveles de desempleo, incrementa la probabilidad del incumplimiento de las obligaciones de los hogares debido a la menor capacidad de pago por la reducción de sus ingresos. De acuerdo con estos impactos, las entidades financieras necesitan contar con mecanismos para abordar el pronóstico sobre el …
Predicting Power Using Time Series Analysis Of Power Generation And Consumption In Texas, 2021 Southern Methodist University
Predicting Power Using Time Series Analysis Of Power Generation And Consumption In Texas, Joshua Eysenbach, Bodie Franklin, Andrew J. Larsen, Joel Lindsey
SMU Data Science Review
Due to the recent power events in Texas, power forecasting has been brought national attention. Accurate demand forecasting is necessary to be sure that there is adequate power supply to meet consumer's needs. While Texas has a forecasting model created by the Electricity Reliability Council of Texas (ERCOT), constant efforts are required to ensure that the model stays at the state-of-the-art and is producing the most reliable forecasts possible. This research seeks to provide improved short- and medium-term forecasting models, bringing in state-of-the-art deep learning models to compare to ERCOT’s forecasts. A model that is more accurate than ERCOT’s own …
Ecological Risk Assessment For The Temperate Demersal Elasmobranch Resource, 2021 Department of Primary Industries and Regional Development, Western Australia
Ecological Risk Assessment For The Temperate Demersal Elasmobranch Resource, Department Of Primary Industries And Regional Development, Western Australia
Fisheries research reports
No abstract provided.
2021 Assessment Of The Status Of The West Coast Demersal Scalefish Resource, 2021 Department of Primary Industries and Regional Development WA
2021 Assessment Of The Status Of The West Coast Demersal Scalefish Resource, David V. Fairclough, Sybrand Alex Hesp, Ainslie Denham, Emily A. Fisher, Rachel Marks, Karina L. Ryan, Elaine Lek, Rhys Allen, Brett M. Crisafulli
Fisheries research reports
A recovery program for the West Coast Demersal Scalefish Resource was introduced between late 2007 and early 2010, based on the maintenance of retained catches of demersal species (overall suite and each indicator species) by both the commercial and recreational sectors below 50% of the catches reported in 2005/06 (original catch recovery benchmarks).
Catch reductions were aimed at reducing exploitation levels (F, long-term fishing mortality of the key indicator species’ stocks) to below the threshold reference point (F = M, the natural mortality rate), which would then allow stocks to recover to above the …
2021 Assessment Of The Status Of The West Coast Demersal Scalefifish Resource, 2021 Department of Primary Industries and Regional Development WA
2021 Assessment Of The Status Of The West Coast Demersal Scalefifish Resource, David Fairclough, E. A. Fisher, Sybrand Alex Hesp, Ainslie Denham, Rachel Marks
Fisheries research reports
No abstract provided.
Otoliths Of South-Western Australian Fish: A Photographic Catalogue, 2021 DPIRD
Otoliths Of South-Western Australian Fish: A Photographic Catalogue, Chris Dowling, Kim Smith, Elain Lek, Joshua Brown
Fisheries research reports
No abstract provided.
Squid And Cuttlefish Resources Of Western Australia, 2021 Department of Primary Industries and Regional Development Western Australia
Squid And Cuttlefish Resources Of Western Australia, Daniel Yeoh, Danielle J. Johnston Phd, David C. Harris
Fisheries research reports
No abstract provided.
Bayesian Variable Selection Strategies In Longitudinal Mixture Models And Categorical Regression Problems., 2021 University of Louisville
Bayesian Variable Selection Strategies In Longitudinal Mixture Models And Categorical Regression Problems., Md Nazir Uddin
Electronic Theses and Dissertations
In this work, we seek to develop a variable screening and selection method for Bayesian mixture models with longitudinal data. To develop this method, we consider data from the Health and Retirement Survey (HRS) conducted by University of Michigan. Considering yearly out-of-pocket expenditures as the longitudinal response variable, we consider a Bayesian mixture model with $K$ components. The data consist of a large collection of demographic, financial, and health-related baseline characteristics, and we wish to find a subset of these that impact cluster membership. An initial mixture model without any cluster-level predictors is fit to the data through an MCMC …
Multiple Baseline Interrupted Time Series: Describing Changes In New Mexico Medicaid Behavioral Health Home Patients’ Care, 2021 University of New Mexico
Multiple Baseline Interrupted Time Series: Describing Changes In New Mexico Medicaid Behavioral Health Home Patients’ Care, Jessica Reno
Mathematics & Statistics ETDs
In 2016, the CareLink New Mexico behavioral health homes program began enrolling Medicaid recipients with the goal of increasing care coordination, improving access to services, and decreasing long-term costs of care for adults with serious mental illness (SMI) and children with severe emotional disturbance (SED). To evaluate these aims, a retrospective interrupted time series study using Medicaid claims data was designed. First, a comparable subset of non-enrolled individuals was selected from the pool of Medicaid recipients with SMI or SED using propensity score matching. Then, segmented regression was applied to three outcomes: total Medicaid charges, number of outpatient behavioral health …