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Fact Sheet, Yale University Office Of Institutional Research

Fact Sheets

No abstract provided.

Fractional Anisotropic Diffusion For Noise Reduction In Magnetic Resonance Images, Jonathan Blackledge, Matthew Blackledge

Articles

We extend the method of anisotropic diffusion for noise reduction in digital images to the case when the diffusion processes are non-Gaussian and Levy distributed. This yields a fractional diffusion equation characterised by the Levy index. A solution to this equation is considered and a numerical algorithm developed. The algorithm is then applied as a case study to the problem of reducing noise in magnetic resonance imaging. The focus of this study is on diffusion weighted images which have low signal-to-noise ratios.

Economic Risk Assessment Using The Fractal Market Hypothesis, Jonathan Blackledge, Marek Rebow

Conference papers

This paper considers the Fractal Market Hypothesi (FMH) for assessing the risk(s) in developing a financial portfolio based on data that is available through the Internet from an increasing number of sources. Most financial risk management systems are still based on the Efficient Market Hypothesis which often fails due to the inaccuracies of the statistical models that underpin the hypothesis, in particular, that financial data are based on stationary Gaussian processes. The FMH considered in this paper assumes that financial data are non-stationary and statistically self-affine so that a risk analysis can, in principal, be applied at any time scale …

Encryption Using Deterministic Chaos, Jonathan Blackledge, Nikolai Ptitsyn

Articles

The concepts of randomness, unpredictability, complexity and entropy form the basis of modern cryptography and a cryptosystem can be interpreted as the design of a key-dependent bijective transformation that is unpredictable to an observer for a given computational resource. For any cryptosystem, including a Pseudo-Random Number Generator (PRNG), encryption algorithm or a key exchange scheme, for example, a cryptanalyst has access to the time series of a dynamic system and knows the PRNG function (the algorithm that is assumed to be based on some iterative process) which is taken to be in the public domain by virtue of the Kerchhoff-Shannon …

The Joint Distribution Of Bivariate Exponential Under Linearly Related Model, Norou Diawara, Kumer Pial Das

Mathematics & Statistics Faculty Publications

In this paper, fundamental results of the joint distribution of the bivariate exponential distributions are established. The positive support multivariate distribution theory is important in reliability and survival analysis, and we applied it to the case where more than one failure or survival is observed in a given study. Usually, the multivariate distribution is restricted to those with marginal distributions of a specified and familiar lifetime family. The family of exponential distribution contains the absolutely continuous and discrete case models with a nonzero probability on a set of measure zero. Examples are given, and estimators are developed and applied to …

Numerical Analysis Of Non-Constant Pure Rate Of Time Preference: A Model Of Climate Policy, Tomoki Fujii, Larry Karp

Research Collection School Of Economics

When current decisions affect welfare in the far-distant future, as with climate change, the use of a declining pure rate of time preference (PRTP) provides potentially important modeling flexibility. The difficulty of analyzing models with non-constant PRTP limits their application. We describe and provide software (available online) to implement an algorithm to numerically obtain a Markov perfect equilibrium for an optimal control problem with non-constant PRTP. We apply this software to a simplified version of the numerical climate change model used in the Stern Review. For our calibration, the policy recommendations are less sensitive to the PRTP than widely believed.

Comparison And Application Of Three Decorrelation Methods Pca, Maf And Acdc, Jacqueline Ferreira

Theses : Honours

Geostatistics is a branch of applied mathematics that deals with spatially correlated data. Analysing and modelling spatially correlated data can be difficult and time consuming, especially for a multivariate data set. One of the techniques used to make analysis and modelling easier involves decorrelation, whereby a linear transformation on the sample variables is used to associate the spatially correlated variables with a set of decorrelated factors which are statistically and spatially independent. PCA was one of the first multivariate techniques and is mostly used as a data reduction technique. A popular alternative decorrelation technique often used in the mining industry …

Impact Of Higher Education Workplace Relations Requirements On Nteu Membership Density, Tulsi Laxman Panchani

Theses : Honours

The National Tertiary Education Union (NTEU) is the only union working entirely in tertiary education around Australia. The union has over twenty four thousand members comprising of academic and general staff. NTEU maintains membership records at three levels, national, state and branch. The information collected includes gender, age group, employment type and work classification. In late April 2005, Higher Education Workplace Relations Requirements (HEWRRs) legislation was introduced by the Australian government. This legislation imposed restrictions on the interaction between the universities and the union and also curtailed an automatic involvement of the union in the resolution of workplace issues. The …

Statistical Analysis Of Wastewater Remediation And Bio-Fuels Production Of Algae, Jay D. Jones

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

The Logan city wastewater treatment system consists of a series of seven large aerated ponds (460 acres) that biologically treats 15 million gallons per day of wastewater from Logan city and six other communities. Tighter regulations of allowed phosphorus levels in the effluent have recently been implemented due to environmental concerns of a downstream reservoir. The Biological Engineering program at Utah State University, the Bio-fuels Center, the Utah Water Research Laboratory (UWRL) and the city of Logan are working together to remediate the wastewater treatment system using microalgae. Algal growth requires the uptake of phosphorus. Thus, phosphorus in the effluent …

Assessing North American Influenza Dynamics With Hierarchical Spatio-Temporal Models, Jessica Anderson

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

We present a general statistical modeling framework to characterize continental-level influenza dynamics in the United States for the purposes of examining state-level epidemiological sources and sinks. The methods we describe depend directly on state-level influenza data that are updated weekly and available on the internet. Advances in search engine query analysis have provided powerful new tools for collecting epidemiological data and, when used in conjunction with sophisticated statistical models, allow for the identification and quantification of the flow of influenza across the continental United States. Our proposed methods, when conditioned on this comprehensive search query product, can provide unprecedented scientific …

A Comparison Of Prediction Methods Of Functional Autoregressive Time Series, Devin Didericksen

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Functional data analysis (FDA) is a relatively new branch of statistics that has seen a lot of expansion recently. With the advent of computer processing power and more efficient software packages we have entered the beginning stages of applying FDA methodology and techniques to data. Part of this undertaking should include an empirical assessment of the effectiveness of some of the tools of FDA, which are sound on theoretical grounds. In a small way, this project helps advance this objective.

This work begins by introducing FDA, scalar prediction techniques, and the functional autoregressive model of order one - FAR(1). Two …

Assessing The Precision And Accuracy In A Small Sample Of Actical Devices, Peter Sherick

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Actigraphy is an increasingly popular approach in medicine to assess patient activity levels in a variety of scenarios. The devices are essentially accelerometers encased in a write-watch type assembly. This project sought to determine the device precision and accuracy for the Actical model. In a sample of four Acticals, it was found that intra-device variability was minimal. However, one device was found to be statistically biased in comparison to the other three. This bias could have adverse effects on aggregated or magnitude dependent data analysis. Also, inter-device comparisons may be problematic.

Canonical Correlation Analysis For Longitudinal Data, Raymond Mccollum

Mathematics & Statistics Theses & Dissertations

Data (multivariate data) on two sets of vectors commonly occur in applications. Statistical analysis of these data is usually done using a canonical correlation analysis (CCA). Occurrence of these data at multiple occasions or conditions leads to longitudinal multivariate data for a CCA. We address the problem of canonical correlation analysis on longitudinal data when the data have a Kronecker product covariance structure. Using structured correlation matrices we model the dependency of repeatedly observed data. Recent work of Srivastava, Nahtman, and von Rosen (2008) developed an iterative algorithm to determine the maximum likelihood estimate of the Kronecker product covariance structure …

Investigating An Optimal Decision Point For Probability Bounds Analysis Models When Used To Estimate Remedial Soil Volumes Under Uncertainty At Hazardous Waste Sites, Charles O. Dankwah

Walden Dissertations and Doctoral Studies

Hazardous waste site remediation cost estimation requires a good estimate of the contaminated soil volume. The United States Environmental Protection Agency (U.S. EPA) currently uses deterministic point values to estimate soil volumes but the literature suggests that probability bounds analysis (PBA) is the more accurate method to make estimates under uncertainty. The underlying statistical theory is that they are more accurate than deterministic estimates because probabilistic estimates account for data uncertainties. However, the literature does not address the problem of selecting an optimal decision point from the interval-valued PBA estimates. The purpose of this study was to identify the optimal …

Analysis Of Models For Longitudinal And Clustered Binary Data, Weiming Yang

Mathematics & Statistics Theses & Dissertations

This dissertation deals with modeling and statistical analysis of longitudinal and clustered binary data. Such data consists of observations on a dichotomous response variable generated from multiple time or cluster points, that exhibit either decaying correlation or equi-correlated dependence. The current literature addresses modeling the dependence using an appropriate correlation structure, but ignores the feasible bounds on the correlation parameter imposed by the marginal means.

The first part of this dissertation deals with two multivariate probability models, the first order Markov chain model and the multivariate probit model, that adhere to the feasible bounds on the correlation. For both the …

Observer-Dependent Model For Analyzing Subjective Parameters In Epidemiology, Milad Zarei

Open Access Theses & Dissertations

Although medical technologies for preventing the contagion and spread of infectious diseases have improved steadily throughout the last century, new infectious diseases are still emerging and spreading swiftly. The modeling of infectious disease spread is crucial in addressing the lack of predictive ability in epidemiology. Managing the spread of infectious diseases requires processing quantitative epidemiological data and the ability to capture the dynamics of the infectious disease in order to provide a measure of control.

In this thesis, I have introducing cognitive biases in diseases spread modeling. For the first time, to the author's knowledge, the human subjective experience has …

Scrap Reduction Model: By Combination Of Dmaic And Design Of Experiments, Anoop J. Randive

Open Access Theses & Dissertations

This project deals with the experimentation which took place at a cable manufacturing company. The thesis describes and summarizes the various strategies and techniques that has been applied and practiced for scrap reduction. DMAIC and Six Sigma Technology has been proven very help full in order to reduce scrap to a major extent. DMAIC help to identify areas in process where extra expense exist, identify the biggest impact factor related production expenses, introduce appropriate measurement system, optimize process and reduce production cost and time. Many issues were detected by the production, such as a lack of a unified procedure for …

Modeling Residential Foreclosures In Kent County, Kaitlyn Ratkowiak

Student Summer Scholars Manuscripts

Residential Foreclosures in Kent County have become commonplace in the past few years. In this project, we hope to analyze data on foreclosures since 2004 to learn more about the mounting crisis, with the hope that we can identify neighborhoods at risk of foreclosures and its associated consequences.

Mean Survival Time From Right Censored Data, Ming Zhong, Kenneth R. Hess

COBRA Preprint Series

A nonparametric estimate of the mean survival time can be obtained as the area under the Kaplan-Meier estimate of the survival curve. A common modification is to change the largest observation to a death time if it is censored. We conducted a simulation study to assess the behavior of this estimator of the mean survival time in the presence of right censoring.

We simulated data from seven distributions: exponential, normal, uniform, lognormal, gamma, log-logistic, and Weibull. This allowed us to compare the results of the estimates to the known true values and to quantify the bias and the variance. Our …

Analysis Of Transient Growth In Iterative Learning Control Using Pseudospectra, Douglas A. Bristow, John R. Singler

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In this paper we examine the problem of transient growth in Iterative Learning Co ntrol (ILC). Transient growth is generally avoided in design by using robust monotonic convergence (RMC) criteria. However, RMC leads to fundamental performance limitations. We consider the possibility of allowing safe transient growth in ILC algorithms as a means to circumvent these limitations. Here the pseudospectra is used for the first time to study transient growth in ILC. Basic properties of the pseudospectra that are relevant to the ILC problem are presented. Two ILC design problems are considered and examined using pseduospectra. The pseudospectra provides new results …

An Adaptive Bayesian Approach To Dose-Response Modeling, Thomas J. Leininger

Theses and Dissertations

Clinical drug trials are costly and time-consuming. Bayesian methods alleviate the inefficiencies in the testing process while providing user-friendly probabilistic inference and predictions from the sampled posterior distributions, saving resources, time, and money. We propose a dynamic linear model to estimate the mean response at each dose level, borrowing strength across dose levels. Our model permits nonmonotonicity of the dose-response relationship, facilitating precise modeling of a wider array of dose-response relationships (including the possibility of toxicity). In addition, we incorporate an adaptive approach to the design of the clinical trial, which allows for interim decisions and assignment to doses based …

Development And Implementation Of High-Throughput Snpgenotyping In Barley, Serdar Bozdag, Timothy J. Close, Prasanna R. Bhat, Stefano Lonardi, Yonghui Wu, Nils Rostoks, Luke Ramsay, Arnis Druka, Nils Stein, Jan T. Svensson, Steve Wanamaker, Mikeal L. Roose, Matthew J. Moscou, Shiaoman Chao, Rajeev K. Varshney, Peter Szucs, Kazuhiro Sato, Patrick M. Hayes, David E. Matthews, Andris Kleinhofs, Gary J. Muehlbauer, Joseph Deyoung, David F. Marshall, Kavitha Madishetty, Raymond D. Fenton, Pascal Condamine, Andreas Graner, Robbie Waugh

Mathematics, Statistics and Computer Science Faculty Research and Publications

Background

High density genetic maps of plants have, nearly without exception, made use of marker datasets containing missing or questionable genotype calls derived from a variety of genic and non-genic or anonymous markers, and been presented as a single linear order of genetic loci for each linkage group. The consequences of missing or erroneous data include falsely separated markers, expansion of cM distances and incorrect marker order. These imperfections are amplified in consensus maps and problematic when fine resolution is critical including comparative genome analyses and map-based cloning. Here we provide a new paradigm, a high-density consensus genetic map of …

Approximating Stationary Statistical Properties, Xiaoming Wang

Mathematics and Statistics Faculty Research & Creative Works

It is well-known that physical laws for large chaotic dynamical systems are revealed statistically. Many times these statistical properties of the system must be approximated numerically. the main contribution of this manuscript is to provide simple and natural criterions on numerical methods (temporal and spatial discretization) that are able to capture the stationary statistical properties of the underlying dissipative chaotic dynamical systems asymptotically. the result on temporal approximation is a recent finding of the author, and the result on spatial approximation is a new one. Applications to the infinite Prandtl number model for convection and the barotropic quasi-geostrophic model are …

Random Walks With Elastic And Reflective Lower Boundaries, Lucas Clay Devore

Masters Theses & Specialist Projects

No abstract provided.

The Development Of An Advanced Filial Therapy Model, Amy Cathleen Wickstrom

Loma Linda University Electronic Theses, Dissertations & Projects

This study sought to develop an advanced filial therapy model by examining the experiences of seven parents who participated in a preliminary advanced filial therapy intervention. These parents had previously completed a 10-week basic filial therapy model called Child Parent Relationship Therapy. A phenomenological qualitative design was employed, wherein data was obtained from parent playtime notes, researcher field notes, group process transcriptions, and focus groups. Parent experiences of the intervention were examined from a systems-relational lens, and four categories emerged, which include relational epiphanies, enhanced understanding of the playtimes, model format, and skill development. Additionally, a variety of themes were …

Optimal Filtering Of An Advertising Production System With Deteriorating Items, Lakhdar Aggoun, Ali Benmerzouga, Lotfi Tadj

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, we consider an integrated stochastic advertising-production system in the case of a duopoly. Two firms spend certain amounts to advertise some product. The expenses processes evolve according to the jumps of two homogeneous, finite-state Markov chains. We assume that the items in stock may be subject to deterioration and the deterioration parameter is assumed to be random.

The Program Evaluation Standards Applied For Metaevaluation Purposes: Investigating Interrater Reliabiity And Implications For Use, Lori A. Wingate

Dissertations

Metaevaluation is the evaluation of evaluation. Metaevaluation may focus particular evaluation cases, evaluation systems, or the discipline overall. Leading scholars within the discipline consider metaevaluation to be a professional imperative, demonstrating that evaluation is a reflexive enterprise. Various criteria have been set forth for what constitutes excellence in evaluation. In the context of educational program evaluation, the dominant criteria are the Program Evaluation Standards, developed by the developed by the Joint Committee on Standards for Educational Evaluation.

There has been widespread acceptance and application of the Program Evaluation Standards, and their use is advocated by major organizations and several of …

Using Labeled Data To Evaluate Change Detectors In A Multivariate Streaming Environment, Albert Y. Kim, Caren Marzban, Donald B. Percival, Werner Stuetzle

Statistical and Data Sciences: Faculty Publications

We consider the problem of detecting changes in a multivariate data stream. A change detector is defined by a detection algorithm and an alarm threshold. A detection algorithm maps the stream of input vectors into a univariate detection stream. The detector signals a change when the detection stream exceeds the chosen alarm threshold. We consider two aspects of the problem: (1) setting the alarm threshold and (2) measuring/comparing the performance of detection algorithms. We assume we are given a segment of the stream where changes of interest are marked. We present evidence that, without such marked training data, it might …

U.S. Chamber Of Commerce Liability Survey: Inaccurate, Unfair, And Bad For Business, Theodore Eisenberg

Cornell Law Faculty Publications

The U.S. Chamber of Commerce uses its Survey of State Liability to criticize judiciaries and seek legal change but no detailed evaluation of the survey’s quality exists. This article presents evidence that the survey is substantively inaccurate and methodologically flawed. It incorrectly characterizes state law; respondents provide less than 10 percent correct answers for objectively verifiable responses. It is internally inconsistent; a state threatened with judicial hellhole status ranked first in the survey while venues not on the list ranked lower. The absence of correlation between survey rankings and observable activity suggests that other factors drive the rankings. Two factors …

Fully Exponential Laplace Approximation Em Algorithm For Nonlinear Mixed Effects Models, Meijian Zhou

Department of Statistics: Dissertations, Theses, and Student Research

Nonlinear mixed effects models provide a flexible and powerful platform for the analysis of clustered data that arise in numerous fields, such as pharmacology, biology, agriculture, forestry, and economics. This dissertation focuses on fitting parametric nonlinear mixed effects models with single- and multi-level random effects. A new, efficient, and accurate method that gives an error of order O(1/n²), fully exponential Laplace approximation EM algorithm (FELA-EM), for obtaining restricted maximum likelihood (REML) estimates in nonlinear mixed effects models is developed. Sample codes for implementing FELA-EM algorithm in R are given. Simulation studies have been conducted to evaluate …