Physical Sciences and Mathematics Commons^™

How Often Versus How Long: The Interplay Of Contact Frequency And Relationship Duration In Customer Perceptions Of Service Relationship Strength, Peter Danaher, Tracey Dagger, Brian Gibbs

Peter Danaher

This study investigates the effects of customer contact frequency and relationship duration on customer-reported relationship strength (CRRS). Although relationships are understood to develop through an incremental process of time and encounters, exactly how frequency and duration interactively influence CRRS is not known. We embed our analysis of these two relationship-quantity variables within a larger model that considers the effects of relationship-quality variables—commitment, trust and satisfaction—on CRRS. We additionally control for customer demographics and service type. Using a fully national sample of 591 service consumers, we find that both contact frequency and relationship duration have a positive effect on CRRS, and …

Priors For A Bayesian Analysis Of Extreme Values, Sally Wood, Julian Wang

Sally Wood

This article proposes a new prior specification for a Bayesian analysis of the k largest order statistics model. We show that using Jeffreys priors for the end-point and shape parameters of the k largest order statistics model leads to biased estimates of the shape parameter for small to medium sample sizes and to the posterior mode of the end-point being equal to the most extreme observed value. We propose a conjugate prior for the shape parameter and a prior for the end-point which removes the posterior mode at the most extreme observed value while remaining uninformative for values of the …

Computer Intensive Methods Lecture 1, Shuangge Ma

Shuangge Ma

No abstract provided.

Detection Of Gene Pathways With Predictive Power For Breast Cancer Prognosis, Shuangge Ma

Shuangge Ma

Prognosis of breast cancer is of great scientific and practical interest. Biomedical studies suggest that clinical and environmental risk factors do not have satisfactory predictive power for prognosis. Multiple gene profiling studies have been conducted, searching for predictive genomic measurements. Genes have the inherent pathway structure, where pathways are composed of multiple genes with similar biological functions. The goal of this study is to identify gene pathways with predictive power for breast cancer prognosis. Although multiple pathway analysis methods are available, they have certain drawbacks and are not suitable for the proposed analysis. In this article, we develop a new …

Worldwide Variation In The Doubling Time Of Alzheimer's Disease Incidence Rates, Kathryn Ziegler-Graham, Ron Brookmeyer, Elizabeth Johnson, H. Michael Arrighi

Ron Brookmeyer

Background The doubling time is the number of chronological years for the age-specific incidence rate to double in magnitude. Doubling times describe the rate of increase of the risk of Alzheimer's disease (AD) with advancing age. Estimates of doubling times of AD assist in understanding disease etiology and forecasting future disease prevalence. The objective of this study was to investigate regional and gender differences in the doubling of AD age-specific incidence rates.

Methods We identified all studies in the peer review literature that reported age-specific incidence rates for AD. We modeled the logarithm of the incidence rate as a linear …

Bayesian Identification, Selection And Estimation Of Functions In High-Dimensional Additive Models, Anastasios Panagiotelis, Michael Smith

Michael Stanley Smith

In this paper we propose an approach to both estimate and select unknown smooth functions in an additive model with potentially many functions. Each function is written as a linear combination of basis terms, with coefficients regularized by a proper linearly constrained Gaussian prior. Given any potentially rank deficient prior precision matrix, we show how to derive linear constraints so that the corresponding effect is identified in the additive model. This allows for the use of a wide range of bases and precision matrices in priors for regularization. By introducing indicator variables, each constrained Gaussian prior is augmented with a …

Bayesian Density Forecasting Of Intraday Electricity Prices Using Multivariate Skew T Distributions, Anastasios Panagiotelis, Michael Smith

Michael Stanley Smith

Electricity spot prices exhibit strong time series properties, including substantial periodicity, both inter-day and intraday serial correlation, heavy tails and skewness. In this paper we capture these characteristics using a first order vector autoregressive model with exogenous effects and a skew t distributed disturbance. The vector is longitudinal, in that it comprises observations on the spot price at intervals during a day. A band two inverse scale matrix is employed for the disturbance, as well as a sparse autoregressive coefficient matrix. This corresponds to a parsimonious dependency structure that directly relates an observation to the two immediately prior, and the …

Teacher's Solutions Manual For Yates, Moore And Starnes's The Practice Of Statistics, Brad Hartlaub

Brad Hartlaub

Optimum Healthcare Image Smoothing And Restoration Based On The Two-Dimensional Arma Model, Terry O'Neill, Jack Penm, Johathan Penm

Terry O'Neill

Confidence Intervals For Biomarker-Based Human Immunodeficiecny Virus Incidence Estimates And Differences Using Prevalent Data, Ron Brookmeyer, S Cole, H Chu

Ron Brookmeyer

Prevalent biological specimens can be used to estimate human immunodeficiency virus (HIV) incidence using a two-stage immunologic testing algorithm that hinges on the average time, say T, between testing HIV positive on highly and less sensitive enzyme immunoassays. Common approaches to confidence interval (CI) estimation for this incidence measure have included (1) ignoring the random error in T or (2) employing a Bonferroni adjustment to the box method. The authors present alternative Monte Carlo-based CIs for this incidence measure, as well as CIs for the biomarker-based incidence difference; standard approaches to CIs are typically appropriate for the incidence ratio. Using …

Multiple Regression, Brad Hartlaub

Brad Hartlaub

A Mathematical Regression Of The U.S. Gross Private Domestic Investment 1959-2001, Byron E. Bell

Byron E. Bell

SUMMARY OF PROJECT What did I do? A study of the role the U.S. stock markets and money markets have possibly played in the Gross Private Domestic Investment (GPDI) of the United States from the year 1959 to the year 2001 and I created a Multiple Linear Regression Model (MLRM).

Foreign Exchange Intervention By The Bank Of Japan: Bayesian Analysis Using A Bivariate Stochastic Volatility Model, Michael Smith, Andrew Pitts

Michael Stanley Smith

A bivariate stochastic volatility model is employed to measure the effect of intervention by the Bank of Japan (BOJ) on daily returns and volume in the USD/YEN foreign exchange market. Missing observations are accounted for, and a data-based Wishart prior for the precision matrix of the errors to the transition equation that is in line with the likelihood is suggested. Empirical results suggest there is strong conditional heteroskedasticity in the mean-corrected volume measure, as well as contemporaneous correlation in the errors to both the observation and transition equations. A threshold model is used for the BOJ reaction function, which is …

Network Structure And Inter-Organizational Knowledge Sharing Capability, Samaddar Subhashish, Jennifer Priestley

Jennifer L. Priestley

No abstract is currently available.

Knowledge Transfer In Multi-Organizational Networks: Influence Of Causal And Outcome Ambiguities, Jennifer Priestley

Jennifer L. Priestley

Informed by the general concept of ambiguity related to knowledge transfer, we first identify and develop the concept of outcome ambiguity as to explain the ambiguity related to inter-organizational knowledge transfer among network firms, which, we argue, is not addressed by the well-established concept of causal ambiguity [34] [46]. Based upon this discussion, we develop the first two of our six hypotheses. Subsequently, we discuss two types of inter-organizational networks and how causal ambiguity and outcome ambiguity would be expected to behave within these network types. This discussion will form the basis for the remaining four of our six hypotheses. …

Inferring Information Frequency And Quality, Douglas G. Steigerwald, John Owens

Douglas G. Steigerwald

We develop a microstructure model that, in contrast to previous models, allows one to estimate the frequency and quality of private information. In addition, the model produces stationary asset price and trading volume series. We find evidence that information arrives frequently within a day and that this information is of high quality. The frequent arrival of information, while in contrast to previous microstructure model estimates, accords with nonmodel-based estimates and the related literature testing the mixture-of-distributions hypothesis. To determine if the estimates are correctly reflecting the arrival of latent information, we estimate the parameters over half-hour intervals within the day. …

Modeling The Optimum Duration Of Antibiotic Prophylaxis In An Anthrax Outbreak, Ron Brookmeyer, Elizabeth Johnson, Robert Bollinger

Ron Brookmeyer

A critical consideration in effective and measured public health responses to an outbreak of inhalational anthrax is the optimum duration of antibiotic prophylaxis. We develop a competing-risks model to address the duration of antibiotic prophylaxis and the incubation period that accounts for the risks of spore germination and spore clearance. The model predicts the incubation period distribution, which is confirmed by empirical data. The optimum duration of antibiotic prophylaxis depends critically on the dose of inhaled spores. At high doses, we show that exposed persons would need to remain on antibiotic prophylaxis for at least 4 months, and considerable morbidity …

Statistical Models And Bioterrorism: Application To The U.S. Anthrax Outbreak, Ron Brookmeyer, Natalie Blades

Ron Brookmeyer

In the fall of 2001 an outbreak of inhalational anthrax occurred in the United States that was the result of bioterrorism. Letters contaminated with anthrax spores were sent through the postal system. In response to the outbreak, public health officials treated over 10,000 persons with antibiotic prophylaxis in the hopes of preventing further morbidity and mortality. No persons receiving the antibiotics subsequently developed disease. The question arises as to how many cases of disease may actually have been prevented by the public health intervention of antibiotic prophylaxis. A statistical model is developed to answer this question by relating to the …

Assessment Of Model Development Techniques And Evaluation Methods For Binary Classification In The Credit Industry, Satish Nargundkar, Jennifer Priestley

Jennifer L. Priestley

We examine and compare the most prevalent modeling techniques in the credit industry, Linear Discriminant Analysis, Logistic Analysis and the emerging technique of Neural Network modeling. K-S Tests and Classification Rates are typically used in the industry to measure the success in predictive classification. We examine those two methods and a third, ROC Curves, to determine if the method of evaluation has an influence on the perceived performance of the modeling technique. We found that each modeling technique has its own strengths, and a determination of the “best” depends upon the evaluation method utilized and the costs associated with misclassification.

Absorptive Capacity, Causal Ambiguity And Outcome Ambiguity: The Network Effect And Knowledge Transfer Difficulty Among Four Network Forms, Subhashish Samaddar, Jennifer Priestley

Jennifer L. Priestley

No abstract is currently available.

Bayesian Modelling And Forecasting Of Intra-Day Electricity Load, Remy Cottet, Michael Smith

Michael Stanley Smith

With the advent of wholesale electricity markets there has been renewed focus on intra-day electricity load forecasting. This paper employs a multi-equation regression model with a diagonal first order stationary vector autoregresson (VAR) for modeling and forecasting intra-day electricity load. The correlation structure of the disturbances to the VAR and the appropriate subset of regressors are explored using Bayesian model selection methodology. The full spectrum of finite sample inference is obtained using a Bayesian Markov chain Monte Carlo sampling scheme. This includes the predictive distribution of load and the distribution of the time and level of daily peak load, something …

Prevention Of Inhalational Anthrax In The U.S. Outbreak, Ron Brookmeyer, Natalie Blades

Ron Brookmeyer

No abstract provided.

Statistics For Logisticians, Caroline Lubert

Caroline P Lubert

No abstract provided.

A Bayesian Approach To Bivariate Nonparametric Regression, Michael Smith, Robert Kohn

Michael Stanley Smith

No abstract provided.

Nonparametric Regression Using Bayesian Variable Selection, Michael Smith, Robert Kohn

Michael Stanley Smith

No abstract provided.

Finite Sample Performance Of Robust Bayesian Regression, Michael Smith, Sheather Simon, Kohn Robert

Michael Stanley Smith

No abstract provided.

Aids Epidemiology: A Quantitative Approach, Ron Brookmeyer, Mitchell Gail

Ron Brookmeyer

This comprehensive work confronts the problems that are unique to AIDS research and unites them under a single conceptual framework. It focuses on methods for the design and analysis of epidemiologic studies, the natural history of AIDS and the transmission of HIV, methods for tracking and projecting the course of the epidemic, and statistical issues in therapeutic trials. The various methods of monitoring and forecasting this disease receive comprehensive treatment. These methods include back-calculation, which the authors developed; interpretation of survey data on HIV prevalence; mathematical models for HIV transmission; and approaches that combine different types of epidemiological data. Much …

Reconstruction And Future Trends Of The Aids Epidemic In The United States, Ron Brookmeyer

Ron Brookmeyer

There has been considerable uncertainty in estimates of past and current human immunodeficiency virus (HIV) infection rates in the United States. Statistical estimates of historical infection rates can be obtained from acquired immunodeficiency syndrome (AIDS) incidence data and the incubation period. However, this approach is subject to a number of sources of uncertainty and two other approaches, epidemic models of HIV transmission and surveys of HIV prevalence, are used to corroborate and refine the statistical estimates. Analyses suggest the HIV infection rate in the United States grew rapidly in the early 1980s, peaked in the mid-1980s, and subsequently declined markedly. …

The Minimum Size Of The Aids Epidemic In The United States, Ron Brookmeyer, Mitchell Gail

Ron Brookmeyer

A new method based on the reported incubation period of transfusion-associated AIDS was used to estimate the number of AIDS cases likely to arise in the USA among those infected before 1986. Between 1986 and 1991 102 000 new cases are projected, with a total cumulative incidence of 135 000 AIDS cases. These estimates do not account for new infections after 1985 nor very long incubation periods and are thus the smallest numbers to be expected. Even if new infections can be effectively prevented, the epidemic will be five times larger than the number of cases observed so far.