Statistics and Probability Commons^™

Comparison Of Policies Text On Information Technology Of China And The United States, Bolin Hua, Shihui Wu

Journal of Scientific Information Research

[Purpose/significance]Information technology plays an important role in the comprehensive national power, whose development is closely associated with the government's guidance and support. It's under this background that China and the United States launched a series of policies to promote the development of information technology. Discovering the differences between China and the US's policies is of great significance for us to improve our strategic planning for future development.[Method/process]This study presents China and the US's most important policies on information technology in chronological order, and mines the policies' text via the co-word networks and the LDA model.[Result/conclusion]Reveal common concerns and different focuses …

การเปรียบเทียบการทำนายทิศทางของราคาหุ้นไทยโดยใช้ตัวแบบ Random Forests, Xgboost และ Lightgbm, สาธิตา ไชยมหา

Chulalongkorn University Theses and Dissertations (Chula ETD)

การศึกษานี้มีวัตถุประสงค์เพื่อทำนายทิศทางของหุ้นไทย โดยทำการทดลองเปรียบเทียบเครื่องมือทางสถิติด้วยตัวแบบ Random Forests, XGBoost และ LightGBM โดยใช้ตัวแปรค่าของข้อมูลก่อนหน้า (Lag Features) เพียงอย่างเดียว ข้อมูลตัวชี้วัด (Indicators) ของหุ้นเพียงอย่างเดียว และ ข้อมูลตัวชี้วัด (Indicators) ของหุ้นร่วมกับข้อมูลก่อนหน้า (Lag Features) กับทั้ง 3 ตัวแบบ ด้วยวิธีการปรับแต่งไฮเปอร์พารามิเตอร์ระหว่างการปรับให้เหมาะสมแบบเบย์ (Bayesian Search) และการค้นหาแบบสุ่ม (Random Search) ในการทำนายทิศทางหุ้นล่วงหน้า 1, 3, 5,10, 15, 30, 60, 90 และ 180 วัน โดยศึกษาหุ้นทั้งหมด 8 ตัวที่ต่างอุตสาหกรรม ดังนี้ เกษตรและอุตสาหกรรมอาหาร (AGRO) สินค้าอุปโภคบริโภค (CONSUMP) ธุรกิจการเงิน (FINCIAL) สินค้าอุตสาหกรรม (INDUS) อสังหาริมทรัพย์และก่อสร้าง (PROPCON) ทรัพยากร (RESOURC) บริการ (SERVICE) เทคโนโลยี (TECH) ข้อมูลราคาหุ้นจาก finance.yahoo.com ปี ค.ศ. 2014-2023 โดยเลือกหุ้นที่มีมูลค่าสูงสุดจากแต่ละกลุ่มอุตสาหกรรม ซึ่งขั้นตอนการแบ่งข้อมูลออกเป็นข้อมูลชุดฝึกฝน (Training Set) และข้อมูลชุดทดสอบ (Test Set) และทำการแบ่ง K-Fold Cross-Validation ทั้งหมด 5 Fold และวัดผลตัวแบบด้วยค่าความแม่นยำ (Accuracy), Precision, Recall, F1-Score และ AUC จากการศึกษาพบว่า ตัวแบบ Random Forests, XGBoost และ LightGBM มีผลลัพธ์การทำนายใกล้เคียงกันในแต่ละชุดตัวแปร และวิธีวิธีการปรับแต่งไฮเปอร์พารามิเตอร์ระหว่างการปรับให้เหมาะสมแบบเบย์ (Bayesian Search) และการค้นหาแบบสุ่ม (Random Search) ให้ผลลัพธ์ใกล้เคียงกันในแต่ละตัวแบบ …

Thai Language Sentiment Analysis With A Hybrid Method On Wangchanberta-Cnn-Bilstm, Kasidhit Suraratchai

Chulalongkorn University Theses and Dissertations (Chula ETD)

Understanding emotions conveyed in text, especially in non-global languages such as Thai, sentiment analysis is particularly important in Thailand. However, this endeavor faces challenges due to variations in text length, which significantly impact sentiment analysis outcomes. Previous research has employed neural network and machine learning models in the process from research [2] and [7], yet each model specializes in different aspects, making comprehensive sentiment analysis coverage unattainable. Recent research [13], has delved into hybrid models like CNN-BiLSTM and BiLSTM-CNN. Although they demonstrate efficacy, their performance still varies across different datasets. For instance, CNN-BiLSTM excels with short sentences by considering surrounding …

Identifying Potential Consequences Of Use Of A Measure Through Stakeholder Interviews, Melissa G. Kuhn, Joanna K. Garner, Shanan L. Chappell, Linda Bol

STEMPS Faculty Publications

The advent of Messick’s Contemporary Validity Theory (1994) led researchers in survey and measure design to develop and standardize qualitative and quantitative methods of collecting evidence for the validity of psychological instruments. However, one aspect of this theory, consequential validity, has few agreed-upon evidence-gathering methods (Furr & Bachrach, 2014). This study added a blueprint-driven interview method of collecting forecasted consequences of use of an instrument into the overall process of developing a measure of outreach impact on undergraduate engineering students (Authors, in press). The method, which included a purposeful sampling of end-users, is illustrated with thematically presented results. Potential implications …

Statistical Intervals For Neural Network And Its Relationship With Generalized Linear Model, Sheng Yuan

Theses and Dissertations--Statistics

Neural networks have experienced widespread adoption and have become integral in cutting-edge domains like computer vision, natural language processing, and various contemporary fields. However, addressing the statistical aspects of neural networks has been a persistent challenge, with limited satisfactory results. In my research, I focused on exploring statistical intervals applied to neural networks, specifically confidence intervals and tolerance intervals. I employed variance estimation methods, such as direct estimation and resampling, to assess neural networks and their performance under outlier scenarios. Remarkably, when outliers were present, the resampling method with infinitesimal jackknife estimation yielded confidence intervals that closely aligned with nominal …

Probabilistic Methods For Inferring The Order Of Pathway Alterations During Carcinogenesis And Cancer Subtype Classification, Menghan Wang

Theses and Dissertations--Statistics

Carcinogenesis is a complex process involving somatic mutations in a number of key biological pathways. Studying cancer evolution is an important task which contributes to better understanding of cancer biology and facilitates identification of new therapeutic targets. We focus on two important questions in cancer evolution. The first question is to delineating the temporal order of pathway mutations during tumorigenesis. And the other question is to cluster patients into biologically meaningful cancer subtypes. We present new statistical methods to 1)leverage functional annotations of mutations to enhance estimation of the order of pathway mutations during carcinogenesis, 2) incorporate intra-tumoral heterogeneity information …

Tolerance Intervals For Various Regression Models, Xitong Zhou

Theses and Dissertations--Statistics

Among statistical intervals, confidence intervals and prediction intervals are well-known and commonly used. In many applications, the problem becomes finding an interval that covers at least a certain proportion $P$ of the population for a characteristic of interest with a specified confidence level $(1-\alpha)$. And such interval is named a $P$-content, $(1-\alpha)$-confidence Tolerance Interval (TI). The topic of the dissertation is the utility of tolerance intervals for various regression models. We begin with a discussion of tolerance intervals for linear and nonlinear regression models. We then propose a bootstrap method of constructing TIs for Tobit regression to deal with censored …

High Dimensional Data Analysis: Variable Screening And Inference, Lei Fang

Theses and Dissertations--Statistics

This dissertation focuses on the problem of high dimensional data analysis, which arises in many fields including genomics, finance, and social sciences. In such settings, the number of features or variables is much larger than the number of observations, posing significant challenges to traditional statistical methods.

To address these challenges, this dissertation proposes novel methods for variable screening and inference. The first part of the dissertation focuses on variable screening, which aims to identify a subset of important variables that are strongly associated with the response variable. Specifically, we propose a robust nonparametric screening method to effectively select the predictors …

Novel Modelling And Inference Considerations Involving The Exponentially-Modified Gaussian Distribution, Yanxi Li

Theses and Dissertations--Statistics

The exponentially-modified Gaussian (EMG) distribution is well-suited for analyzing data with positive skewness due to its characteristic positive skew from the exponential component. Despite its popularity in various fields, the EMG distribution has only been analyzed for univariate data without any regression settings. To address this limitation, we developed a generalized EMG regression model with covariates by assigning parametric functional forms to some or all of the parameters in the EMG distribution that vary with values of the covariates. To further perform data-clustering on observation points, we propose a competing regression model where the error structure is assumed to be …

Finite Mixtures Of Mean-Parameterized Conway-Maxwell-Poisson Models, Dongying Zhan

Theses and Dissertations--Statistics

For modeling count data, the Conway-Maxwell-Poisson (CMP) distribution is a popular generalization of the Poisson distribution due to its ability to characterize data over- or under-dispersion. While the classic parameterization of the CMP has been well-studied, its main drawback is that it is does not directly model the mean of the counts. This is mitigated by using a mean-parameterized version of the CMP distribution. In this work, we are concerned with the setting where count data may be comprised of subpopulations, each possibly having varying degrees of data dispersion. Thus, we propose a finite mixture of mean-parameterized CMP distributions. An …

Methodologies And Computational Tools For Zero-Inflated Discrete Weibull Models, Peng Yeh

Theses and Dissertations--Statistics

Count data with excess zeros is common in many fields, such as ecology, healthcare, and insurance. Excess zeros data are often causing the inaccurate fit from the count models. While zero-inflated models have been developing for over two decades, one should also consider a more flexible model that can handle the excess zeros and further over- or under-dispersion. In this talk, we discuss zero-inflated discrete Weibull model and some novel computational contributions. The flexibility and competitiveness of the ZIDW model are illustrated by simulation studies and a real data analysis. We also investigate the performance of the proposed model through …

Striving For Appropriate Antibiotic Use: A Biomarker Initiative, And Outcomes Associated With Azithromycin Exposure, Amanda Gusovsky

Theses and Dissertations--Pharmacy

The introduction of antibiotics into clinical practice is considered the greatest medical breakthrough of the 20^thcentury. However, the use of antibiotics can contribute to the development of resistance. In the United States (U.S.), approximately 2.8 million people are infected with antibiotic-resistant bacteria each year, and more than 35,000 people die as a result. Moreover, some antibiotics are known to cause cardiac side effects including QT prolongation, hypotension, and ventricular arrythmias. The U.S. Centers for Disease Control and Prevention (CDC) defines appropriate antibiotic use as the effort to use “the right antibiotic, at the right dose, for the right …

Clustering Hospital Performance Using Group-Based Multi-Trajectory Modeling With Singular Bayesian Information Criterion, Gaixin Du

Theses and Dissertations--Epidemiology and Biostatistics

Hospital performance is complex and patient-experience oriented. Currently, the Centers for Medicare and Medicaid Services (CMS) evaluate hospitals yearly with a single score of one to five ("Star Rating") using composite measures from five domains. However, a single composite score cannot fully describe it, and alternative measures should be considered. Healthcare quality improvement needs long-term data to validate effectiveness. Group-based multi-trajectory modeling (GBMTM) estimates probabilities of latent group membership based on longitudinal profiles from multiple outcomes. We use GBMTM to identify groups of hospitals with similar performance in SAS PROC TRAJ.

We downloaded Medicare-eligible hospitals (N=5,111) that provided patient care …

Potential Alzheimer's Disease Plasma Biomarkers, Taylor Estepp

Theses and Dissertations--Epidemiology and Biostatistics

In this series of studies, we examined the potential of a variety of blood-based plasma biomarkers for the identification of Alzheimer's disease (AD) progression and cognitive decline. With the end goal of studying these biomarkers via mixture modeling, we began with a literature review of the methodology. An examination of the biomarkers with demographics and other health factors found evidence of minimal risk of confounding along the causal pathway from biomarkers to cognitive performance. Further study examined the usefulness of linear combinations of biomarkers, achieved via partial least squares (PLS) analysis, as predictors of various cognitive assessment scores and clinical …

Economics Of Maple Syrup Production In Kentucky, Bobby Thapa

Theses and Dissertations--Forestry and Natural Resources

Maple syrup production is traditionally associated with New England regions in the United States, but there is growing interest in expanding it to other regions with suitable environmental conditions, including Kentucky. This study presents an in-depth analysis of the potential production and economic impacts of maple syrup in Kentucky using a multi-method approach. First, the study applies a stochastic production model to assess the effects of climatic and tree variables on maple syrup yield. The results reveal that several variables, including the number of maple trees, taps, temperatures, tapping season length, and time, significantly affect maple syrup yield. Second, input-output …

The Impact Of Subjective Risk Analysis On Real Estate Prices In The Nisqually Region Following The 2001 Nisqually Earthquake, Ryan Espedal

All Master's Theses

Earthquakes are an environmental hazard that pose great risks to communities almost every day. With earthquakes, the main cause of concern is physical destruction of property, however, there are also psychological effects that are researched and discussed much less. In 2001, the Nisqually area of western Washington experienced a substantial earthquake that produced minimal physical damage but caused a significant decrease in real estate prices. Studying single-family homes from 1986-2012, this research utilizes hedonic property models to measure the change in consumer’s subjective risk calculations with reference to real estate purchases after the Nisqually earthquake, measure the relationship between earthquake …

Beginner's Analysis Of Financial Stochastic Process Models, David Garcia

HMC Senior Theses

This thesis explores the use of geometric Brownian motion (GBM) as a financial model for predicting stock prices. The model is first introduced and its assumptions and limitations are discussed. Then, it is shown how to simulate GBM in order to predict stock price values. The performance of the GBM model is then evaluated in two different periods of time to determine whether it's accuracy has changed before and after March 23, 2020.

A Method For Quantifying Individual Decision Thresholds Of Latent Print Examiners, Amanda Luby

Mathematics & Statistics Faculty Works

In recent years, ‘black box’ studies in forensic science have emerged as the preferred way to provide information about the overall validity of forensic disciplines in practice. These studies provide aggregated error rates over many examiners and comparisons, but errors are not equally likely on all comparisons. Furthermore, inconclusive responses are common and vary across examiners and comparisons, but do not fit neatly into the error rate framework. This work introduces Item Response Theory (IRT) and variants for the forensic setting to account for these two issues. In the IRT framework, participant proficiency and item difficulty are estimated directly from …

An Exploration Of Parameter Duality In Statistical Inference, Suzanne Thornton, M. Xie

Mathematics & Statistics Faculty Works

Well-known debates among statistical inferential paradigms emerge from conflicting views on the notion of probability. One dominant view understands probability as a representation of sampling variability; another prominent view understands probability as a measure of belief. The former generally describes model parameters as fixed values, in contrast to the latter. We propose that there are actually two versions of a parameter within both paradigms: a fixed unknown value that generated the data and a random version to describe the uncertainty in estimating the unknown value. An inferential approach based on CDs deciphers seemingly conflicting perspectives on parameters and probabilities.

The Chains That Bind: Gender, Disability, Race, And It Accommodations, Eleanor T. Loiacono, Shiya Cao

Statistical and Data Sciences: Faculty Books

This chapter explores intersectionality of gender, disability, and race relevant to Information Technology (IT) accommodations and employment. More specifically, we investigate individuals’ experiences and differences in receiving IT accommodations as an organizational diversity intervention that helps disabled employees integrate into the workplace. The goal of this chapter is to seek a better understanding of individual differences in the accommodation process and how to empower disabled women in the workplace. To do so, by applying the Individual Differences Theory of Gender and IT (IDTGIT), we focus on the experiences disabled men and women have with regard to IT accommodations as well …

System For Scanning And Monitoring Science And Technology Policy Texts Of Us And Eu, Dahai Yu, Aofei Chang, Bolin Hua, Hongguang Wang, Wenjiao Zheng

Journal of Scientific Information Research

[Purpose/significance]Science and technology policy plays a guiding role in the development of science and technology. Whether science and technology policies are efficient and reasonable has an important impact on the rapid development of science and technology. In order to help decision-makers grasp the latest international scientific and technological layout, planning and policy guidance more quickly, especially to track and analyze the scientific, and technological policies of major developed countries in Europe and the United States, grab analyze and mine the corresponding scientific and technological policy texts in real time, has of great significance in the current international environment.[Method/process]This research designed …

Odd Solutions To Systems Of Inequalities Coming From Regular Chain Groups, Daniel Slilaty

Mathematics and Statistics Faculty Publications

Hoffman’s theorem on feasible circulations and Ghouila-Houry’s theorem on feasible tensions are classical results of graph theory. Camion generalized these results to systems of inequalities over regular chain groups. An analogue of Camion’s result is proved in which solutions can be forced to be odd valued. The obtained result also generalizes the results of Pretzel and Youngs as well as Slilaty. It is also shown how Ghouila-Houry’s result can be used to give a new proof of the graph- coloring theorem of Minty and Vitaver.

Carnivore And Ungulate Occurrence In A Fire-Prone Region, Sara J. Moriarty-Graves

Cal Poly Humboldt theses and projects

Increasing fire size and severity in the western United States causes changes to ecosystems, species’ habitat use, and interspecific interactions. Wide-ranging carnivore and ungulate mammalian species and their interactions may be influenced by an increase in fire activity in northern California. Depending on the fire characteristics, ungulates may benefit from burned habitat due to an increase in forage availability, while carnivore species may be differentially impacted, but ultimately driven by bottom-up processes from a shift in prey availability. I used a three-step approach to estimate the single-species occupancy of four large mammal species: mountain lion (Puma concolor), coyote …

Eeg-Based Spanish Language Proficiency Classification: An Eeg Power Spectrum And Cross-Spectrum Analysis, Blaise Xavier O'Mara, Skyler Baumer

Honors Theses and Capstones

Second language proficiency may be predicted with electrophysiological techniques. In a machine learning application, this electrophysiological data may be used for language instructors and language students to assess their language learning. This study identifies how electroencephalogram (EEG) power spectrum and cross spectrum data of the brain cortex relates to Spanish second language (L2) proficiency of 20 Spanish language students of varying proficiency levels at the University of New Hampshire. The two metrics for assessing cortical power and processing were event-related desynchronization (ERD)—a measure of relative change in power—of the alpha (8-12 Hz) brain frequency band, and alpha and beta (13-30Hz) …

Occurrence Of Per- And Polyfluoroalkyl Substances (Pfas) In New Hampshire Biosolids, Katherine A. Wieck

Honors Theses and Capstones

Per- and polyfluoroalkyl substances (PFAS) are a group of over 4,000 compounds used in the manufacturing of products including aqueous film forming foams for firefighting, stain repellents, waterproofing agents, and nonstick cookware since their initial development in the 1940s. The long fluorinated carbon chain structure of PFAS causes chemical and thermal stability, and thus resistance to biodegradation. Biosolids produced at wastewater facilities for uses such as agricultural land-applied compost and fertilizer for lawns and athletic fields, as well as sludge disposed in landfills can cause contamination of groundwater and surface water. This poses a significant threat to human and environmental …

Wilcoxon-Mann-Whitney Effects For Clustered Data: Informative Cluster Size, Changrui Liu

Theses and Dissertations--Statistics

In recent research, there has been a growing interest in understanding the impact of informative cluster size (ICS) on statistical inference for clustered data. In the non-parametric context, the problem for testing equality of distribution functions has been the main consideration. We are aiming to develop inferential procedures for the Wilcoxon-Mann-Whitney effect, also known as the non-parametric relative effect, involving two or more groups. Computationally, results from both simulated and real-world data have shown promising results that our proposed tests effectively account for ICS and they particularly outperform other methods in the literature designed for ignorable cluster sizes. The applications …

An Assessment Of "Long-Thin" Airline Routes: Network Structure And Emissions Implications For Environmental Policy, Porter Burns

All Master's Theses

The purpose of this research was to define, map, and quantify the network and environmental implications of “long-thin” routes (LTRs) – a route structure that has been discussed in the aviation industry but not formally studied in literature. LTRs were defined through the use of global OAG scheduling data from 1998 to 2018 to identify trends in air traffic growth and network dynamics. Flights were separated into seven aircraft class sizes (e.g., 75–150 seats, 150–225 seats) to measure LTRs at multiple scales. Routes were considered “long” if the stage length was at or above the 75^th percentile in each …

Recurrent Event Data Analysis With Mismeasured Covariates, Ravinath Alahakoon Mudiyanselage

Doctoral Dissertations

"Consider a study with n units wherein every unit is monitored for the occurrence of an event that can recur with random end of monitoring. At each recurrence, p concomitant variables associated to the event recurrence are recorded with q (q ≤ p) collected with errors. Of interest in this dissertation is the estimation of the regression parameters of event time regression models accounting for the covariates. To circumvent the problem of bias and consistency associated with model's parameter estimation in the presence of measurement errors, we propose inference for corrected estimating functions with well-behaved roots under additive measurement errors …

Expectile Neural Networks For Genetic Data Analysis Of Complex Diseases, Jinghang Lin, Xiaoran Tong, Chenxi Li, Qing Lu

Biostatistics Faculty Publications

The genetic etiologies of common diseases are highly complex and heterogeneous. Classic methods, such as linear regression, have successfully identified numerous variants associated with complex diseases. Nonetheless, for most diseases, the identified variants only account for a small proportion of heritability. Challenges remain to discover additional variants contributing to complex diseases. Expectile regression is a generalization of linear regression and provides complete information on the conditional distribution of a phenotype of interest. While expectile regression has many nice properties, it has rarely been used in genetic research. In this paper, we develop an expectile neural network (ENN) method for genetic …

Joint Probability Analysis Of Extreme Precipitation And Water Level For Chicago, Illinois, Anna Li Holey

Dissertations, Master's Theses and Master's Reports

A compound flooding event occurs when there is a combination of two or more extreme factors that happen simultaneously or in quick succession and can lead to flooding. In the Great Lakes region, it is common for a compound flooding event to occur with a high lake water level and heavy rainfall. With the potential of increasing water levels and an increase in precipitation under climate change, the Great Lakes coastal regions could be at risk for more frequent and severe flooding. The City of Chicago which is located on Lake Michigan has a high population and dense infrastructure and …