Statistical Models Commons^™

Process Optimization In Freight Forwarding Industry, Xiaohua Shi

World Maritime University Dissertations

No abstract provided.

An Investigation Of Shipping Derivatives Based On Risk Evaluation, Sheng Yang

World Maritime University Dissertations

No abstract provided.

Effectively Selecting A Target Population For A Future Comparative Study, Lihui Zhao, Lu Tian, Tianxi Cai, Brian Claggett, L. J. Wei

Harvard University Biostatistics Working Paper Series

When comparing a new treatment with a control in a randomized clinical study, the treatment effect is generally assessed by evaluating a summary measure over a specific study population. The success of the trial heavily depends on the choice of such a population. In this paper, we show a systematic, effective way to identify a promising population, for which the new treatment is expected to have a desired benefit, using the data from a current study involving similar comparator treatments. Specifically, with the existing data we first create a parametric scoring system using multiple covariates to estimate subject-specific treatment differences. …

Bayesian Phase I Dose Finding In Cancer Trials, Lin Yang

Dissertations and Theses (Open Access)

This dissertation explores phase I dose-finding designs in cancer trials from three perspectives: the alternative Bayesian dose-escalation rules, a design based on a time-to-dose-limiting toxicity (DLT) model, and a design based on a discrete-time multi-state (DTMS) model.

We list alternative Bayesian dose-escalation rules and perform a simulation study for the intra-rule and inter-rule comparisons based on two statistical models to identify the most appropriate rule under certain scenarios. We provide evidence that all the Bayesian rules outperform the traditional ``3+3'' design in the allocation of patients and selection of the maximum tolerated dose.

The design based on a time-to-DLT model …

On The Covariate-Adjusted Estimation For An Overall Treatment Difference With Data From A Randomized Comparative Clinical Trial, Lu Tian, Tianxi Cai, Lihui Zhao, L. J. Wei

Harvard University Biostatistics Working Paper Series

No abstract provided.

General Recognition Theory Extended To Include Response Times: Predictions For A Class Of Parallel Systems, Joseph W. Houpt, James T. Townsend, Noah H. Silbert

Psychology Faculty Publications

No abstract provided.

A Statistical Test For The Capacity Coefficient, Joseph W. Houpt, James T. Townsend

Psychology Faculty Publications

No abstract provided.

From Deep Space 9 To The Gamma Quadrant!, James T. Townsend, Joseph W. Houpt

Psychology Faculty Publications

No abstract provided.

Reduced Bayesian Hierarchical Models: Estimating Health Effects Of Simultaneous Exposure To Multiple Pollutants, Jennifer F. Bobb, Francesca Dominici, Roger D. Peng

Johns Hopkins University, Dept. of Biostatistics Working Papers

Quantifying the health effects associated with simultaneous exposure to many air pollutants is now a research priority of the US EPA. Bayesian hierarchical models (BHM) have been extensively used in multisite time series studies of air pollution and health to estimate health effects of a single pollutant adjusted for potential confounding of other pollutants and other time-varying factors. However, when the scientific goal is to estimate the impacts of many pollutants jointly, a straightforward application of BHM is challenged by the need to specify a random-effect distribution on a high-dimensional vector of nuisance parameters, which often do not have an …

A Unified Approach To Non-Negative Matrix Factorization And Probabilistic Latent Semantic Indexing, Karthik Devarajan, Guoli Wang, Nader Ebrahimi

COBRA Preprint Series

Non-negative matrix factorization (NMF) by the multiplicative updates algorithm is a powerful machine learning method for decomposing a high-dimensional nonnegative matrix V into two matrices, W and H, each with nonnegative entries, V ~ WH. NMF has been shown to have a unique parts-based, sparse representation of the data. The nonnegativity constraints in NMF allow only additive combinations of the data which enables it to learn parts that have distinct physical representations in reality. In the last few years, NMF has been successfully applied in a variety of areas such as natural language processing, information retrieval, image processing, speech recognition …

An Extension Of Sic Predictions To The Wiener Coactive Model, Joseph W. Houpt, James T. Townsend

Psychology Faculty Publications

The survivor interaction contrasts (SIC) is a powerful measure for distinguishing among candidate models of human information processing. One class of models to which SIC analysis can apply are the coactive, or channel summation, models of human information processing. In general, parametric forms of coactive models assume that responses are made based on the first passage time across a fixed threshold of a sum of stochastic processes. Previous work has shown that the SIC for a coactive model based on the sum of Poisson processes has a distinctive down--up--down form, with an early negative region that is smaller than the …

Generalized Bathtub Hazard Models For Binary-Transformed Climate Data, James Polcer

Masters Theses & Specialist Projects

In this study, we use a hazard-based modeling as an alternative statistical framework to time series methods as applied to climate data. Data collected from the Kentucky Mesonet will be used to study the distributional properties of the duration of high and low-energy wind events relative to an arbitrary threshold. Our objectiveswere to fit bathtub models proposed in literature, propose a generalized bathtub model, apply these models to Kentucky Mesonet data, and make recommendations as to feasibility of wind power generation. Using two different thresholds (1.8 and 10 mph respectively), results show that the Hjorth bathtub model consistently performed better …

A Singular Perturbation Approach To The Fitzhugh-Nagumo Pde For Modeling Cardiac Action Potentials., Jeremy Brooks

Undergraduate Honors Theses

The study of cardiac action potentials has many medical applications. Dr. Dennis Noble first used mathematical models to study cardiac action potentials in the 1960s. We begin our study of cardiac action potentials with one form of the Fitzhugh-Nagumo partial differential equation. We use the non-classical method to produce a closed form solution for the decoupled Fitzhugh Nagumo equation. Using voltage recording data of action potentials in a cardiac myocyte and in purkinje fibers, we estimate parameter values for the closed form solution with standard linear and non-linear regression methods. Results are limited, thus leading us to perturb the solution …

A Stochastic Model For Wind Turbine Power Quality Using A Levy Index Analysis Of Wind Velocity Data, Jonathan Blackledge, Eugene Coyle, Derek Kearney

Conference papers

The power quality of a wind turbine is determined by many factors but time-dependent variation in the wind velocity are arguably the most important. After a brief review of the statistics of typical wind speed data, a non- Gaussian model for the wind velocity is introduced that is based on a Levy distribution. It is shown how this distribution can be used to derive a stochastic fractional diusion equation for the wind velocity as a function of time whose solution is characterised by the Levy index. A Levy index numerical analysis is then performed on wind velocity data for both …

Effects Of Inlet Conditions On Diffuser Outlet Performance, Zaccary A. Poots

UNLV Theses, Dissertations, Professional Papers, and Capstones

Building air distribution terminal system designers and system installers require accurate quantitative information on the performance of the installed system to achieve optimum efficiency and levels of human comfort. This requires field installation adjustment values from published ideal pressure loss, air distribution and sound generation installation performance. This study documents the air output performance of different installation configurations of six types of ceiling diffusers and compares the results to performance when installed according to ANSI/ASHRAE Standard 70-2006. A diffuser inlet supply plenum was designed for optimum flow and used to acquire a baseline set of data covering the six types …

Arima Models For Bank Failures: Prediction And Comparison, Fangjin Cui

UNLV Theses, Dissertations, Professional Papers, and Capstones

The number of bank failures has increased dramatically over the last twenty-two years. A common notion in economics is that some banks can become "too big to fail." Is this still a true statement? What is the relationship, if any, between bank sizes and bank failures? In this thesis, the proposed modeling techniques are applied to real bank failure data from the FDIC. In particular, quarterly data from 1989:Q1 to 2010:Q4 are used in the data analysis, which includes three major parts: 1) pairwise bank failure rate comparisons using the conditional test (Przyborowski and Wilenski, 1940); 2) development of the …

A New Perspective On Visual Word Processing Efficiency, Joseph W. Houpt, James T. Townsend

Psychology Faculty Publications

No abstract provided.

Examining The Student Investment Roundtable's Funds, David Hernandez, Uriel Luna

Undergraduate Research Conference

To what extent are the factors of the Fama-French-Factor Asset Pricing Model related to rates of returns of the Stephen F. Austin State University Student Investment Roundtable Fund?

The Fama-French Model is believed to be a major improvement over the ever-popular Capital Asset Pricing Model, CAPM. The Capital Asset Pricing Model uses a single factor beta to compare the excess returns of a portfolio with the excess returns of the market as a whole, but is said to oversimplify the complex market. On the other hand, the Fama-French Model three-factor adds additional factors to the original CAPM equation. The Fama-French …

Nice Guys Finish Fast And Bad Guys Finish Last: Facilitatory Vs. Inhibitory Interaction In Parallel Systems, Ami Eidels, Joseph W. Houpt, Nicholas Altieri, Lei Pei, James T. Townsend

Psychology Faculty Publications

Systems Factorial Technology is a powerful framework for investigating the fundamental properties of human information processing such as architecture (i.e., serial or parallel processing) and capacity (how processing efficiency is affected by increased workload). The Survivor Interaction Contrast (SIC) and the Capacity Coefficient are effective measures in determining these underlying properties, based on response-time data. Each of the different architectures, under the assumption of independent processing, predicts a specific form of the SIC along with some range of capacity. In this study, we explored SIC predictions of discrete-state (Markov process) and continuous-state (Linear Dynamic) models that allow for certain types …

Threshold Regression Models Adapted To Case-Control Studies, And The Risk Of Lung Cancer Due To Occupational Exposure To Asbestos In France, Antoine Chambaz, Dominique Choudat, Catherine Huber, Jean-Claude Pairon, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Asbestos has been known for many years as a powerful carcinogen. Our purpose is quantify the relationship between an occupational exposure to asbestos and an increase of the risk of lung cancer. Furthermore, we wish to tackle the very delicate question of the evaluation, in subjects suffering from a lung cancer, of how much the amount of exposure to asbestos explains the occurrence of the cancer. For this purpose, we rely on a recent French case-control study. We build a large collection of threshold regression models, data-adaptively select a better model in it by multi-fold likelihood-based cross-validation, then fit the …

Estimating Subject-Specific Treatment Differences For Risk-Benefit Assessment With Competing Risk Event-Time Data, Brian Claggett, Lihui Zhao, Lu Tian, Davide Castagno, L. J. Wei

Harvard University Biostatistics Working Paper Series

No abstract provided.

Some Problems And Solutions In The Experimental Science Of Technology: The Proper Use And Reporting Of Statistics In Computational Intelligence, With An Experimental Design From Computational Ethnomusicology, Mehmet Vurkaç

Systems Science Friday Noon Seminar Series

Statistics is the meta-science that lends validity and credibility to The Scientific Method. However, as a complex and advanced Science in itself, Statistics is often misunderstood and misused by scientists, engineers, medical and legal professionals and others. In the area of Computational Intelligence (CI), there have been numerous misuses of statistical techniques leading to the publishing of insupportable results, which, in addition to being a problem in itself, has also contributed to a degree of rift between the Statistics/Statistical Learning community and the Machine Learning/Computational Intelligence community. This talk surveys a number of misuses of statistical inference in CI settings, …

Population Functional Data Analysis Of Group Ica-Based Connectivity Measures From Fmri, Shanshan Li, Brian S. Caffo, Suresh Joel, Stewart Mostofsky, James Pekar, Susan Spear Bassett

Johns Hopkins University, Dept. of Biostatistics Working Papers

In this manuscript, we use a two-stage decomposition for the analysis of func- tional magnetic resonance imaging (fMRI). In the first stage, spatial independent component analysis is applied to the group fMRI data to obtain common brain networks (spatial maps) and subject-specific mixing matrices (time courses). In the second stage, functional principal component analysis is utilized to decompose the mixing matrices into population- level eigenvectors and subject-specific loadings. Inference is performed using permutation-based exact conditional logistic regression for matched pairs data. Simulation studies suggest the ability of the decomposition methods to recover population brain networks and the major direction of …

A Flexible Spatio-Temporal Model For Air Pollution: Allowing For Spatio-Temporal Covariates, Johan Lindstrom, Adam A. Szpiro, Paul D. Sampson, Lianne Sheppard, Assaf Oron, Mark Richards, Tim Larson

UW Biostatistics Working Paper Series

Given the increasing interest in the association between exposure to air pollution and adverse health outcomes, the development of models that provide accurate spatio-temporal predictions of air pollution concentrations at small spatial scales is of great importance when assessing potential health effects of air pollution. The methodology presented here has been developed as part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air), a prospective cohort study funded by the US EPA to investigate the relationship between chronic exposure to air pollution and cardiovascular disease. We present a spatio-temporal framework that models and predicts ambient air pollution by …

Flipping The Winner Of A Poset Game, Adam O. Kalinich '12

Student Publications & Research

Partially-ordered set games, also called poset games, are a class of two-player combinatorial games. The playing field consists of a set of elements, some of which are greater than other elements. Two players take turns removing an element and all elements greater than it, and whoever takes the last element wins. Examples of poset games include Nim and Chomp. We investigate the complexity of computing which player of a poset game has a winning strategy. We give an inductive procedure that modifies poset games to change the nim-value which informally captures the winning strategies in the game. For a generic …

The Doubly Inflated Poisson And Related Regression Models, Manasi Sheth-Chandra

Mathematics & Statistics Theses & Dissertations

Most real life count data consists of some values that are more frequent than allowed by the common parametric families of distributions. For data consisting of only excess zeros, in a seminal paper Lambert (1992) introduced Zero-Inflated Poisson (ZIP) model, which is a mixture model that accounts for the inflated zeros. In this thesis, two Doubly Inflated Poisson (DIP) probability models, DIP (p, λ) and DIP ( p1, p2, λ), are discussed for situations where there is another inflated value k > 0 besides the inflated zeros. The distributional properties such as identifiability, moments, and conditional probabilities …

Stochastic Dynamics Of Gene Transcription, Yan Xie

Theses and Dissertations--Statistics

Gene transcription in individual living cells is inevitably a stochastic and dynamic process. Little is known about how cells and organisms learn to balance the fidelity of transcriptional control and the stochasticity of transcription dynamics. In an effort to elucidate the contribution of environmental signals to this intricate balance, a Three State Model was recently proposed, and the transcription system was assumed to transit among three different functional states randomly.

In this work, we employ this model to demonstrate how the stochastic dynamics of gene transcription can be characterized by the three transition parameters. We compute the probability distribution of …

Some Ratio Type Estimators Under Measurement Errors, Florentin Smarandache, Mukesh Kumar, Rajesh Singh, Ashish K. Singh

Branch Mathematics and Statistics Faculty and Staff Publications

This article addresses the problem of estimating the population mean using auxiliary information in the presence of measurement errors.

Applying Localized Realized Volatility Modeling To Futures Indices, Luella Fu

CMC Senior Theses

This thesis extends the application of the localized realized volatility model created by Ying Chen, Wolfgang Karl Härdle, and Uta Pigorsch to other futures markets, particularly the CAC 40 and the NI 225. The research attempted to replicate results though ultimately, those results were invalidated by procedural difficulties.

Why Is An Einstein Ring Blue?, Jonathan Blackledge

Articles

Albert Einstein predicted the existence of `Einstein rings' as a consequence of his general theory of relativity. The phenomenon is a direct result of the idea that if a mass warps space-time then light (and other electromagnetic waves) will be `lensed' by the strong gravitational field produced by a large cosmological body such as a galaxy. Since 1998, when the first complete Einstein ring was observed, many more complete or partially complete Einstein rings have been observed in the radio and infrared spectra, for example, and by the Hubble Space Telescope in the optical spectrum. However, in the latter case, …