Bingroup2: Statistical Tools For Infection
Identification Via Group Testing,
2023
University of Nebraska-Lincoln
Bingroup2: Statistical Tools For Infection Identification Via Group Testing, Christopher R. Bilder, Brianna D. Hitt, Brad J. Biggerstaff, Joshua M. Tebbs, Christopher S. Mcmahan
Department of Statistics: Faculty Publications
Group testing is the process of testing items as an amalgamation, rather than separately, to determine the binary status for each item. Its use was especially important during the COVID-19 pandemic through testing specimens for SARS-CoV-2. The adoption of group testing for this and many other applications is because members of a negative testing group can be declared negative with potentially only one test. This subsequently leads to significant increases in laboratory testing capacity. Whenever a group testing algorithm is put into practice, it is critical for laboratories to understand the algorithm’s operating characteristics, such as the expected number of …
Good Practices And Common Pitfalls In Climate Time Series Changepoint
Techniques: A Review,
2023
University of California, Santa Cruz
Good Practices And Common Pitfalls In Climate Time Series Changepoint Techniques: A Review, Robert B. Lund, Claudie Beaulieu, Rebecca Killick, Qiqi Lu, Xueheng Shi
Department of Statistics: Faculty Publications
Climate changepoint (homogenization) methods abound today, with a myriad of techniques existing in both the climate and statistics literature. Unfortunately, the appropriate changepoint technique to use remains unclear to many. Further complicating issues, changepoint conclusions are not robust to perturbations in assumptions; for example, allowing for a trend or correlation in the series can drastically change changepoint conclusions. This paper is a review of the topic, with an emphasis on illuminating the models and techniques that allow the scientist to make reliable conclusions. Pitfalls to avoid are demonstrated via actual applications. The discourse begins by narrating the salient statistical features …
A Nonparametric Test For Comparing Survival Functions Based On Restricted Distance Correlation,
2023
University of Arkansas, Fayetteville
A Nonparametric Test For Comparing Survival Functions Based On Restricted Distance Correlation, Quinyang Zhang
Mathematical Sciences Faculty Publications and Presentations
In this article, we propose an omnibus test for comparing two survival functions under non-proportional hazards. The test statistic is based on a product-limit estimate of the restricted distance correlation, which is closely related to the L2 distance between survival curves. The strong consistency is established under mild regularity conditions. Our simulation studies show that the new test has satisfactory power under proportional hazard and various non-proportional hazards settings including delayed treatment effect, diminishing effect, and crossing survival curves; therefore, it can be a competitive alternative to the existing omnibus tests such as Kolmogorov-Smirnov test, Cramer-von Mises test, two-stage …
(R2060) An M/G/1 Retrial Queue With Recurrent Customers, General Retrial Times And Working Vacation,
2023
Annamalai University
(R2060) An M/G/1 Retrial Queue With Recurrent Customers, General Retrial Times And Working Vacation, S. Pazhani Bala Murugan, A. Jeba Pauline Veronica
Applications and Applied Mathematics: An International Journal (AAM)
In this article, we analyze an M/G/1 retrial queue with recurrent customers, general retrial times and working vacation. In this model, we use two types of customers. They are recurrent customers who rejoin the retrial queue after completion of their service and transit customers who leaves the system once their service complete. All the service times and retrial times for transit customers follows general distribution, retrial time for recurrent customers and working vacation time of the server are assumed to have an exponential distribution and also service time of the recurrent customers follows general distribution. We have used working vacation …
Models Of Shared Care For The Management Of Psychotic Disorder After First Diagnosis In Ontario.,
2023
Western University
Models Of Shared Care For The Management Of Psychotic Disorder After First Diagnosis In Ontario., Joshua C. Wiener, Rebecca Rodrigues, Jennifer N S Reid, Kelly K. Anderson
Epidemiology and Biostatistics Publications
OBJECTIVE: To describe the provision of care for young people following first diagnosis of psychotic disorder.
DESIGN: Retrospective cohort study using health administrative data.
SETTING: Ontario.
PARTICIPANTS: People aged 14 to 35 years with a first diagnosis of nonaffective psychotic disorder in Ontario between 2005 and 2015 (N=39,449).
MAIN OUTCOME MEASURES: Models of care, defined by psychosis-related service contacts with primary care physicians and psychiatrists during the 2 years after first diagnosis of psychotic disorder.
RESULTS: During the 2-year follow-up period, 29% of the cohort received only primary care, 30% received only psychiatric care, and 32% received both primary and …
Analyses Of Effect Indices Across Single-Case Research Designs In Counseling,
2023
University of Arkansas, Fayetteville
Analyses Of Effect Indices Across Single-Case Research Designs In Counseling, Cian L. Brown
Graduate Theses and Dissertations
Single case research design (SCRD) is a common methodology used across clinical disciplines to determine treatments effectiveness by comparing treatment conditions to baseline conditions in individual cases, usually among researchers working with smaller samples. Although popular within behavioral disciplines such as special education and behavioral analysis, studies have begun to emerge in counseling. However, guidance and current understanding of the use of SCRD in counseling is limited. A content analysis of counseling journals from 2003 to 2014 yielded only 7 studies using SCRD. In 2015, the flagship counseling journal, Journal of Counseling and Development, published a special issue on the …
Generalized Ratio-Product Cum Regression Variance Estimator In Two-Phase Sampling,
2023
Department of Statistics, Binyaminu Usman Polytechnic, Hadejia, Nigeria.
Generalized Ratio-Product Cum Regression Variance Estimator In Two-Phase Sampling, Isah Muhammad
CBN Journal of Applied Statistics (JAS)
This study develops a flexible and efficient generalized ratio-product cum regression type estimator of population variance utilizing auxiliary variable in two-phase sampling that incorporates the properties of ratio-type and product-type estimators. The properties of the estimator were derived using first order approximation. The theoretical conditions under which the precision and the flexibility of the estimator is better than some classical estimators are also provided. Empirical evidence from five real datasets suggests that the proposed estimator outperforms the classical variance, ratio variance, product, and exponential ratio type estimators in terms of precision and efficiency. The estimator can be utilized to provide …
Modelling The Naira Exchange Rate Dependence Using Static And Time-Varying Copula,
2023
Nigeria Deposit Insurance Corporation
Modelling The Naira Exchange Rate Dependence Using Static And Time-Varying Copula, Kabir Katata
CBN Journal of Applied Statistics (JAS)
This paper examines the dependence structure of different currencies versus the Nigerian Naira using constant and time-varying copula. Daily Naira/USD, Naira/Yuan, Naira/Pound, and Naira/Euro exchange rates from 23 December 2011 to 12 May 2020 were utilised. We fitted eight constant and time-varying copula families using the exchange rate standardised residuals. The study finds that the Naira exchange rate may be estimated with student t-copula, Symmetrized Joe-Clayton (SJC), or Rotated Gumbel copula models and Autoregressive (AR)– Glosten Jagannathan RunkleGeneralized Autoregressive Conditional Heteroscedastic (GJR-GARCH) (1,1) models with skewed t residuals for margins. The Naira exchange rate returns is timevarying, tail-dependent, and asymmetric. …
External Debt Pass-Through To Inflation In Nigeria,
2023
Department of Economics, Benue State University, Makurdi
External Debt Pass-Through To Inflation In Nigeria, Emmanuel A. Asue, James V. Ikyaator
CBN Journal of Applied Statistics (JAS)
This study examines external debt pass-through to inflation in Nigeria using annual data from 1981 to 2020 based on structural vector autoregressive (SVAR) model. The results reveal that an increase in external debt service leads to a significant depreciation of the exchange rate, which leads to a contemporaneous increase in inflation, while the direct response of inflation to external debt is statistically not significant. The impulse response confirms these results. The forecast error variance decomposition depicts that future values of official exchange rate depend on external debt, inflation and external debt service. The study recommends that the Nigerian government should …
Financial Inclusion And Poverty Reduction In Nigeria: The Role Of Microfinance Institutions,
2023
Department of Economics, Federal University Lafia, Nasarawa State
Financial Inclusion And Poverty Reduction In Nigeria: The Role Of Microfinance Institutions, Okwudili W. Ugwuoke, Oliver E. Ogbonna, Aye-Agele Freeman
CBN Journal of Applied Statistics (JAS)
This study investigates the role of microfinance institutions as a vehicle for driving financial inclusion and alleviating poverty in Nigeria using the EFinA 2018 household survey data. The probit model, propensity score matching, and average treatment effect methods are applied for the analyses. The study finds that financial inclusion driven by access to, and usage of products/services provided by microfinance institutions reduces poverty. The study recommends among others the need for increased access to microfinance products/services and an integrated poverty reduction policies that identifies microfinance institutions as a critical enabler
Bayesian Strategies For Propensity Score Estimation In Causal Inference.,
2023
University of Louisville
Bayesian Strategies For Propensity Score Estimation In Causal Inference., Uthpala I. Wanigasekara
Electronic Theses and Dissertations
Causal inference is a method used in various fields to draw causal conclusions based on data. It involves using assumptions, study designs, and estimation strategies to minimize the impact of confounding variables. Propensity scores are used to estimate outcome effects, through matching methods, stratification, weighting methods, and the Covariate Balancing Propensity Score method. However, they can be sensitive to estimation techniques and can lead to unstable findings. Researchers have proposed integrating weighing with regression adjustment in parametric models to improve causal inference validity. The first project focuses on Bayesian joint and two-stage methods for propensity score analysis. Propensity score modeling …
Applications Of Causal Inference Methods For The Estimation Of Effects Of Bone Marrow Transplant And Prescription Drugs On Survival Of Aplastic Anemia Patients,
2023
Chapman University
Applications Of Causal Inference Methods For The Estimation Of Effects Of Bone Marrow Transplant And Prescription Drugs On Survival Of Aplastic Anemia Patients, Yesha M. Patel
Computational and Data Sciences (PhD) Dissertations
This dissertation provides an in-depth exploration into the treatment effectiveness for aplastic anemia using causal inference methods, structured around three pivotal research papers. Each paper contributes to a nuanced understanding of treatment impacts, specifically focusing on bone marrow transplantation (BMT) and prescription drugs, and the identification of optimal treatment strategies.
The first paper, "Causal Inference Analysis for Assessing the Effect of Bone Marrow Transplantation on the One-Year Survival of Adult and Pediatric Aplastic Anemia Patients," sets the foundation. It examines the short-term effectiveness of BMT in both adult and pediatric patients, providing crucial insights into how this treatment affects survival …
Metrics For Comparison Of Complex Networks,
2023
University of Texas at El Paso
Metrics For Comparison Of Complex Networks, Clarissa Reyes
Open Access Theses & Dissertations
Heuristic network statistics are used as a preliminary approach to identify change across networks. In networks where there is known node correspondence (KNC), conventional network comparison methods include taking a norm of the difference matrix, or calculating dissimilarity measures like DeltaCon and cut distance. Since different KNC measures provide varying insight to the network comparison problem, we propose employing Rank Score Characteristic Functions (RSCFs) and the rank-score process as a method for reaching a consensus when ranking quantified change across multiple pairs of networks â?? which is particularly useful for ranking change across subpopulations or subgraphs. Additionally, we propose a …
Foundations Of Memory Capacity In Models Of Neural Cognition,
2023
California Polytechnic State University, San Luis Obispo
Foundations Of Memory Capacity In Models Of Neural Cognition, Chandradeep Chowdhury
Master's Theses
A central problem in neuroscience is to understand how memories are formed as a result of the activities of neurons. Valiant’s neuroidal model attempted to address this question by modeling the brain as a random graph and memories as subgraphs within that graph. However the question of memory capacity within that model has not been explored: how many memories can the brain hold? Valiant introduced the concept of interference between memories as the defining factor for capacity; excessive interference signals the model has reached capacity. Since then, exploration of capacity has been limited, but recent investigations have delved into the …
Random Variable Spaces: Mathematical Properties And An Extension To Programming Computable Functions,
2023
Chapman University
Random Variable Spaces: Mathematical Properties And An Extension To Programming Computable Functions, Mohammed Kurd-Misto
Computational and Data Sciences (PhD) Dissertations
This dissertation aims to extend the boundaries of Programming Computable Functions (PCF) by introducing a novel collection of categories referred to as Random Variable Spaces. Originating as a generalization of Quasi-Borel Spaces, Random Variable Spaces are rigorously defined as categories where objects are sets paired with a collection of random variables from an underlying measurable space. These spaces offer a theoretical foundation for extending PCF to natively handle stochastic elements.
The dissertation is structured into seven chapters that provide a multi-disciplinary background, from PCF and Measure Theory to Category Theory with special attention to Monads and the Giry Monad. The …
Wavelet Compression As An Observational Operator In Data Assimilation Systems For Sea Surface Temperature,
2023
University of New Orleans, New Orleans
Wavelet Compression As An Observational Operator In Data Assimilation Systems For Sea Surface Temperature, Bradley J. Sciacca
LSU New Orleans Theses and Dissertations
The ocean remains severely under-observed, in part due to its sheer size. Containing nearly billion of water with most of the subsurface being invisible because water is extremely difficult to penetrate using electromagnetic radiation, as is typically used by satellite measuring instruments. For this reason, most observations of the ocean have very low spatial-temporal coverage to get a broad capture of the ocean’s features. However, recent “dense but patchy” data have increased the availability of high-resolution – low spatial coverage observations. These novel data sets have motivated research into multi-scale data assimilation methods. Here, we demonstrate a new assimilation approach …
Enhanced Market Timing: Long Short-Term Memory Neural Network For Optimal Entry And Exit In Stock Market,
2023
University at Albany, State University of New York
Enhanced Market Timing: Long Short-Term Memory Neural Network For Optimal Entry And Exit In Stock Market, Jerome Chinua Hall
Legacy Theses & Dissertations (2009 - 2024)
This thesis investigates applying a Long Short-Term Memory (LSTM) Neural Network for forecasting optimal times to enter and exit the stock market. Given the inherent imbalance in the dataset, where most days are not opportune for market actions, and the challenge of predicting such infrequent occurrences, we will employ a five-day window before and after the identified optimal market entry or exit time. A prediction is considered correct if it is within this five-day interval. The model was trained on historical S&P 500 data, using features such as exponential and simple moving averages of the closing price, the ten-day percentage …
Radiation Exposure Calibration Of The Al2o3:C With Radium-226 And Cesium-137 Using The Osl Method,
2023
Clemson University
Radiation Exposure Calibration Of The Al2o3:C With Radium-226 And Cesium-137 Using The Osl Method, Selma Tepeli Aydin
All Theses
Optically stimulated luminescence (OSL) dosimetry was utilized to calibrate Al2O3:C powder dosimeters, available commercially as the nanoDot® from Landauer Inc., and compare the dosimeter response to radium-226 (226Ra) and cesium-137 (137Cs). The signal from the OSL was quantified using a microSTARii® OSL reader also produced by Landauer Inc. Dose-response curves were developed for 226Ra and 137Cs experiments (5 dosimeters each) at thirteen absorbed doses. Individual dosimeter response was tracked by serial number. Linear regression analysis was performed to determine if there were significant differences between the intercepts of the …
The Impact Of Neighborhood Socioeconomic Disadvantage On Operative Outcomes After Single-Level Lumbar Fusion,
2023
Harvard Medical School
The Impact Of Neighborhood Socioeconomic Disadvantage On Operative Outcomes After Single-Level Lumbar Fusion, Grace Y. Ng, Ritesh Karsalia, Ryan S. Gallagher, Austin J. Borja, Jianbo Na, Scott Mcclintock, Neil R. Malhotra
Mathematics Faculty Publications
INTRODUCTION: The relationship between socioeconomic status and neurosurgical outcomes has been investigated with respect to insurance status or median household income, but few studies have considered more comprehensive measures of socioeconomic status. This study examines the relationship between Area Deprivation Index (ADI), a comprehensive measure of neighborhood socioeconomic disadvantage, and short-term postoperative outcomes after lumbar fusion surgery. METHODS: 1861 adult patients undergoing single-level, posterior-only lumbar fusion at a single, multihospital academic medical center were retrospectively enrolled. An ADI matching protocol was used to identify each patient's 9-digit zip code and the zip code-associated ADI data. Primary outcomes included 30- and …
Estimating Financial And Environmental Risk: Some New Developments And Comparison Study.,
2023
Clemson University
Estimating Financial And Environmental Risk: Some New Developments And Comparison Study., Fnu Kamronnaher
All Dissertations
This dissertation delves into the concept of risk, specifically focusing on two prominent categories: financial risk and environmental risk.
Financial risk is the probability of unfavorable outcomes of an investment while environmental risk refers to the possible harm to the environment resulting from extreme weather events. More specifically, risk is the high (low) quantiles of the distribution of variables of interest. \\ To quantify and assess uncertainties in financial and environmental risk, robust and reliable methodologies are needed. The aim of this dissertation is to develop some risk assessment methods and compare them with the widely used methodologies in both …
