Physical Sciences and Mathematics Commons^™

The Fraud Detection Triangle: A New Framework For Selecting Variables In Fraud Detection Research, Adrian Gepp, Kuldeep Kumar, Sukanto Bhattacharya

Kuldeep Kumar

On The Interpretation Of Multi-Year Estimates Of The American Community Survey As Period Estimates, Chaitra Nagaraja, Tucker Mcelroy

Chaitra H Nagaraja

The rolling sample methodology of the American Community Survey introduces temporal distortions, resulting in Multi-Year Estimates that measure aggregate activity over three or five years. This paper introduces a novel, nonparametric method for quantifying the impact of viewing multi-year estimates as functions of single-year estimates belonging to the same time span. The method is based on examining the changes to confidence interval coverage. As an application of primary interest, the interpretation of a multi-year estimate as the simple average of single-year estimates is a viewpoint that underpins the published estimates of sampling variability. Therefore it is vital to ascertain the …

Financial Statement Fraud Detection Using Supervised Learning Methods (Ph.D. Dissertation), Adrian Gepp

Adrian Gepp

No abstract provided.

Promoting Similarity Of Model Sparsity Structures In Integrative Analysis Of Cancer Genetic Data, Shuangge Ma

Shuangge Ma

In profiling studies, the analysis of a single dataset often leads to unsatisfactory results because of the small sample size. Multi-dataset analysis utilizes information across multiple independent datasets and outperforms single-dataset analysis. Among the available multi-dataset analysis methods, integrative analysis methods aggregate and analyze raw data and outperform meta-analysis methods, which analyze multiple datasets separately and then pool summary statistics. In this study, we conduct integrative analysis and marker selection under the heterogeneity structure, which allows different datasets to have overlapping but not necessarily identical sets of markers. Under certain scenarios, it is reasonable to expect some similarity of identified …

The Lower Ordovician Fillmore Formation Of Western Utah: Storm-Dominated Sedimentation On A Passive Margin., Benjamin Dattilo

Benjamin F. Dattilo

No abstract provided.

Repeat Sales House Price Index Methodology, Chaitra Nagaraja, Lawrence Brown, Susan Wachter

Chaitra H Nagaraja

No abstract provided.

Business Statistics In Practice, Bruce Bowerman, Julie Schermer, Andrew Johnson, Richard O'Connell, Emily Murphree

Andrew M. Johnson

No abstract provided.

Reference Interval Studies: What Is The Maximum Number Of Samples Recommended?, Robert Hawkins, Tony Badrick

Tony Badrick

Background: Little attention has been paid to the maximum number of specimens for reference interval calculation, i.e., the number of specimens beyond which there is no further benefit in reference interval calculation. We present a model for the estimation of the maximum number of specimens for reference interval studies based on setting the 90% confidence interval of the reference limits to be equal to the analyte reporting interval. Methods: Equations describing the bounds on the upper and lower 90% confidence intervals for logarithmically transformed and untransformed data were derived and applied to determine the maximum number of specimens required to …

A Mathematical Model For Estimation Of Fibre, Abhijit Bhattacharya, Kuldeep Kumar

Kuldeep Kumar

Yield estimates of fibre in Jute plants (Capsulanes) are usually obtained on the basis of random samples of plants. These estimates are required by the government for the purpose of planning and policy formulation. Due to time and resource constraint, it becomes quite often difficult to compute yield estimates from samples of large size. In this paper an attempt has been made to propose a method based on Gaussian quadrature to estimate the fibre yield from smaller samples. Identification of plants comprising a smaller sample and corresponding weights to be assigned to the yield of plants included in the smaller …

Business Failure Prediction Using Statistical Techniques: A Review, Adrian Gepp, Kuldeep Kumar

Adrian Gepp

Accurate business failure prediction models would be extremely valuable to many industry sectors, particularly in financial investment and lending. The potential value of such models has been recently emphasised by the extremely cosdy failure of high profile businesses in both Australia and overseas, such as HIH (Australia) and Enron (USA). Consequently, there has been a significant increase in interest in business failure prediction from both industry and academia. Statistical business failure prediction models attempt to predict the failure or success of a business. Discriminant and logit analyses are the most popular approaches, and there are also a large number of …

A Comparison Of Periodic Autoregressive And Dynamic Factor Models In Intraday Energy Demand Forecasting, Thomas Mestekemper, Goeran Kauermann, Michael Smith

Michael Stanley Smith

We suggest a new approach for forecasting energy demand at an intraday resolution. Demand in each intraday period is modeled using semiparametric regression smoothing to account for calendar and weather components. Residual serial dependence is captured by one of two multivariate stationary time series models, with dimension equal to the number of intraday periods. These are a periodic autoregression and a dynamic factor model. We show the benefits of our approach in the forecasting of district heating demand in a steam network in Germany and aggregate electricity demand in the state of Victoria, Australia. In both studies, accounting for weather …

Constructing And Evaluating An Autoregressive House Price Index, Chaitra Nagaraja, Lawrence Brown

Chaitra H Nagaraja

No abstract provided.

An Introduction To Item Response Theory For Health Behavior Researchers, Russell Warne

Russell T Warne

OBJECTIVE:

To introduce item response theory (IRT) to health behavior researchers by contrasting it with classical test theory and providing an example of IRT in health behavior.

METHOD:

Demonstrate IRT by fitting the 2PL model to substance-use survey data from the Adolescent Health Risk Behavior questionnaire (n=1343 adolescents).

RESULTS:

An IRT 2PL model can produce viable substance use scores that differentiate different levels of substance use, resulting in improved precision and specificity at the respondent level.

CONCLUSION:

IRT is a viable option for health researchers who want to produce high-quality scores for unidimensional constructs. The results from our example-although not …

Rejoinder: Estimation Issues For Copulas Applied To Marketing Data, Peter Danaher, Michael Smith

Michael Stanley Smith

Estimating copula models using Bayesian methods presents some subtle challenges, ranging from specification of the prior to computational tractability. There is also some debate about what is the most appropriate copula to employ from those available. We address these issues here and conclude by discussing further applications of copula models in marketing.

Forecasting Television Ratings, Peter Danaher, Tracey Dagger, Michael Smith

Michael Stanley Smith

Despite the state of flux in media today, television remains the dominant player globally for advertising spend. Since television advertising time is purchased on the basis of projected future ratings, and ad costs have skyrocketed, there is increasing pressure to forecast television ratings accurately. Previous forecasting methods are not generally very reliable and many have not been validated, but more distressingly, none have been tested in today’s multichannel environment. In this study we compare 8 different forecasting models, ranging from a naïve empirical method to a state-of-the-art Bayesian model-averaging method. Our data come from a recent time period, 2004-2008 in …

An Autoregressive Approach To House Price Modeling, Chaitra Nagaraja, Lawrence Brown, Linda Zhao

Chaitra H Nagaraja

No abstract provided.

Estimating Confidence Intervals For Eigenvalues In Exploratory Factor Analysis, Ross Larsen, Russell Warne

Russell T Warne

Exploratory factor analysis (EFA) has become a common procedure in educational and psychological research. In the course of performing an EFA, researchers often base the decision of how many factors to retain on the eigenvalues for the factors. However, many researchers do not realize that eigenvalues, like all sample statistics, are subject to sampling error, which means that confidence intervals (CIs) can be estimated for each eigenvalue. In the present article, we demonstrate two methods of estimating CIs for eigenvalues: one based on the mathematical properties of the central limit theorem, and the other based on bootstrapping. References to appropriate …

The 1905 Einstein Equation In A General Mathematical Analysis Model Of Quasars, Byron E. Bell

Byron E. Bell

No abstract provided.

Using Twitter Hash Tags To Demonstrate Basic Concepts From Network Analysis, Matt Bogard

Matt Bogard

Social Network Analysis focuses on finding patterns in interactions between people or entities. These patterns may be described in the form of a network. Network analysis in general has many applications including models of student integration and persistence, business to business supply chains, terrorist cells, or analysis of social media such as Facebook and Twitter. This presentation provides a reference for basic concepts from social network analysis with examples using tweets from Twitter.

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).

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. …

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.

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.