Statistics and Probability Commons^™

An Approach For Dealing With Statuses Of Non-Statistically Significant Interactions Between Treatments, Zakaria M. Sawan

Journal of Modern Applied Statistical Methods

A field experiment on cotton yield resulted in a non-statistically significant interaction. An approach for follow-up examination between treatments based on least significant difference values was suggested to identify the effect regardless of insignificance. It was found that the classical formula used in calculating the significance of interactions suffers a possible shortage that can be eliminated by applying a suggested revision.

An Application Of Machine Learning Methods To The Derivation Of Exposure-Response Curves For Respiratory Outcomes, Ekaterina Eliseeva, Alan E. Hubbard, Ira B. Tager

U.C. Berkeley Division of Biostatistics Working Paper Series

Analyses of epidemiological studies of the association between short-term changes in air pollution and health outcomes have not sufficiently discussed the degree to which the statistical models chosen for these analyses reflect what is actually known about the true data-generating distribution. We present a method to estimate population-level ambient air pollution (NO2) exposure-health (wheeze in children with asthma) response functions that is not dependent on assumptions about the data-generating function that underlies the observed data and which focuses on a specific scientific parameter of interest (the marginal adjusted association of exposure on probability of wheeze, over a grid of possible …

Section Abstracts: Statistics

Virginia Journal of Science

Abstracts of the Statistics Section for the 91st Annual Virginia Journal of Science Meeting, May 2013

Analyzing And Solving Non-Linear Stochastic Dynamic Models On Non-Periodic Discrete Time Domains, Gang Cheng

Masters Theses & Specialist Projects

Stochastic dynamic programming is a recursive method for solving sequential or multistage decision problems. It helps economists and mathematicians construct and solve a huge variety of sequential decision making problems in stochastic cases. Research on stochastic dynamic programming is important and meaningful because stochastic dynamic programming reflects the behavior of the decision maker without risk aversion; i.e., decision making under uncertainty. In the solution process, it is extremely difficult to represent the existing or future state precisely since uncertainty is a state of having limited knowledge. Indeed, compared to the deterministic case, which is decision making under certainty, the stochastic …

The Torsion Angle Of Random Walks, Mu He

Masters Theses & Specialist Projects

In this thesis, we study the expected mean of the torsion angle of an n-step
equilateral random walk in 3D. We consider the random walk is generated within a confining sphere or without a confining sphere: given three consecutive vectors ^→e₁ , ^→e₂ , and ^→e₃ of the random walk then the vectors ^→e₁ and ^→e₂ define a plane and the vectors ^→e₂ and ^→e₃ define a second plane. The angle between the two planes is called the torsion angle of the three vectors. Algorithms are …

Penalized Smoothed Partial Rank Estimator For The Nonparametric Transformation Survival Model With High-Dimensional Covariates, Wei Dai, Yi Li

The University of Michigan Department of Biostatistics Working Paper Series

Microarray technology has the potential to lead to a better understanding of biological processes and diseases such as cancer. When failure time outcomes are also available, one might be interested in relating gene expression profiles to the survival outcome such as time to cancer recurrence or time to death. This is statistically challenging because the number of covariates greatly exceeds the number of observations. While the majority of work has focused on regularized Cox regression model and accelerated failure time model, they may be restrictive in practice. We relax the model assumption and and consider a nonparametric transformation model that …

Applications Of Bayesian Statistics In Fluvial Bed Load Transport, Mark L. Schmelter

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The science of fluvial sediment transport studies the processes involved in the movement of river sediments. It is commonly understood that when rivers flood they have a great capacity to move sand, gravel, and even larger cobbles and boulders. This process is not only limited to the big floods that usually attract so much attention, but also the more common river flows play a very important role in forming a river. As engineers and scientists, we like to be able to develop equations and relationships that describe some natural phenomenon—in this case, fluvial sediment transport. While we are able to …

Empirical Properties Of Functional Regression Models And Application To High-Frequency Financial Data, Xi Zhang

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Functional data analysis (FDA) has grown into a substantial field of statistical research, with new methodology, numerous useful applications and interesting novel theoretical developments. My dissertation focuses on the empirical properties of functional regression models and their application to financial data. We start from testing the empirical properties of forecasts with the functional autoregressive models based on simulated and real data. We define intraday returns and consider their prediction from such returns on a market index. This is an extension to intraday data of the Capital Asset Pricing model. Finally we investigate multifactor functional models and assess their suitability for …

Existence And Multiplicity Results On Standing Wave Solutions Of Some Coupled Nonlinear Schrodinger Equations, Rushun Tian

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Coupled nonlinear Schrodinger equations (CNLS) govern many physical phenomena, such as nonlinear optics and Bose-Einstein condensates. For their wide applications, many studies have been carried out by physicists, mathematicians and engineers from different respects. In this dissertation, we focused on standing wave solutions, which are of particular interests for their relatively simple form and the important roles they play in studying other wave solutions. We studied the multiplicity of this type of solutions of CNLS via variational methods and bifurcation methods.

Variational methods are useful tools for studying differential equations and systems of differential equations that possess the so-called variational …

Statistical Algorithms For Optimal Experimental Design With Correlated Observations, Chang Li

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The first part of my dissertation demonstrates that a modified simulated annealing algorithm can successfully determine highly efficient D-optimal designs for second order polynomial regression for a variety of correlated error structures.

In the second part, I solved weak universal optimal block designs for the nearest neighbor correlation structure and multiple block sizes, for the hub correlation structure with any block size, and for circulant correlation with odd block size.

In the third part, we propose an improved Particle Swarm Optimization (PSO) algorithm with time varying parameters. Then combining the theorem of decision making and PSO, we innovated nested PSO …

Level Crossing Times In Mathematical Finance, Ofosuhene Osei

Electronic Theses and Dissertations

Level crossing times and their applications in finance are of importance, given certain threshold levels that represent the "desirable" or "sell" values of a stock. In this thesis, we make use of Wald's lemmas and various deep results from renewal theory, in the context of finance, in modelling the growth of a portfolio of stocks. Several models are employed .

The Association Of Diet And Physical Activity With Stroke Mortality Results From The Adventist Health Study-1, Tahereh Zamansani

Loma Linda University Electronic Theses, Dissertations & Projects

Stroke is one of the leading causes of death and disability, with major global public health implications. Stroke ranks No. 4 among all causes of death, behind heart disease, cancer, and chronic lower respiratory disease (CLRD). Stroke accounts for almost 1 of every 18 deaths in the United States. Women accounted for 60.6% of stroke deaths. Death certificate data show that the mean age at stroke death was 79.6 years; males had a younger mean age (76.3) than females.

There is still a great scientific uncertainty among researchers and epidemiologists about the magnitude of any preventive effect, mechanisms of action …

Conceptual Distinction Between The Critical P Value And The Type I Error Rate In Permutation Testing, Richard B. Anderson

Journal of Modern Applied Statistical Methods

To counter past assertions that permutation testing is not distribution-free, this article clarifies that the critical p value (alpha) in permutation testing is not a Type I error rate and that a test's validity is independent of the concept of Type I error.

A Response To Anderson's (2013) Conceptual Distinction Between The Critical P Value And Type I Error Rate In Permutation Testing, Fortunato Pesarin, Stefano Bonnini

Journal of Modern Applied Statistical Methods

Pesarin and Bonnini respond to Anderson's (2013) Conceptual Distinction between the Critical p value and Type I Error Rate in Permutation Testing

A Monte Carlo Simulation Of The Robust Rank-Order Test Under Various Population Symmetry Conditions, William T. Mickelson

Journal of Modern Applied Statistical Methods

The Type I Error Rate of the Robust Rank Order test under various population symmetry conditions is explored through Monte Carlo simulation. Findings indicate the test has difficulty controlling Type I error under generalized Behrens-Fisher conditions for moderately sized samples.

Constructing A More Powerful Test In Two-Level Block Randomized Designs, Spyros Konstantopoulos

Journal of Modern Applied Statistical Methods

A more powerful test is proposed for the treatment effect in two-level block randomized designs where random assignment takes place at the first level. When clustering at the second level is assumed to be known, the proposed test produces higher estimates of power than the typical test.

Bayesian Inference Of Pair-Copula Constriction For Multivariate Dependency Modeling Of Iran’S Macroeconomic Variables, M. R. Zadkarami, O. Chatrabgoun

Journal of Modern Applied Statistical Methods

Bayesian inference of pair-copula constriction (PCC) is used for multivariate dependency modeling of Iran’s macroeconomics variables: oil revenue, economic growth, total consumption and investment. These constructions are based on bivariate t-copulas as building blocks and can model the nature of extreme events in bivariate margins individually. The model parameter was estimated based on Markov chain Monte Carlo (MCMC) methods. A MCMC algorithm reveals unconditional as well as conditional independence in Iran’s macroeconomic variables, which can simplify resulting PCC’s for these data.

Using The Bootstrap For Estimating The Sample Size In Statistical Experiments, Maher Qumsiyeh

Journal of Modern Applied Statistical Methods

Efron’s (1979) Bootstrap has been shown to be an effective method for statistical estimation and testing. It provides better estimates than normal approximations for studentized means, least square estimates and many other statistics of interest. It can be used to select the active factors - factors that have an effect on the response - in experimental designs. This article shows that the bootstrap can be used to determine sample size or the number of runs required to achieve a certain confidence level in statistical experiments.

The X-Alter Algorithm: A Parameter-Free Method Of Unsupervised Clustering, Thomas Laloë, Rémi Servien

Journal of Modern Applied Statistical Methods

Using quantization techniques, Laloë (2010) defined a new clustering algorithm called Alter. This L¹-based algorithm is shown to be convergent but suffers two major flaws. The number of clusters, K, must be supplied by the user and the computational cost is high. This article adapts the X-means algorithm (Pelleg & Moore, 2000) to solve both problems.

Estimating Heterogeneous Intra-Class Correlation Coefficients In Dyadic Ecological Momentary Assessment, Emily A. Blood, Leslie A. Kalish, Lydia A. Shrier

Journal of Modern Applied Statistical Methods

A method is described for estimating and testing predictors for influence on the variance of momentary behaviors in dyadic ecological momentary assessment data. Results show that the method allows intraclass correlations of momentary observations from two members of the same couple to vary by observation-level, individual-level and couple-level predictors.