A Note On The Inefficiency Of Competitive Markets For Quality Goods, 2016 Iowa State U
A Note On The Inefficiency Of Competitive Markets For Quality Goods, John R. Schroeter
This note describes and investigates an equilibrium model of a service market in which customers search among many firms for ones offering acceptable combinations of money price and expected waiting time. Although neither firms nor customers possess market power, the noncooperative equilibrium of the model is inefficient: Forcing customers to be more selective in their choices of suppliers can produce Pareto improvements in welfare. This result is due to an externality, in queue accession decisions, which others have identified in related contexts..
Effects Of Energy Price Rises, Energy Constraints, And Energy Minimization On Crop And Livestock Production Activities, John A. Miranowski
During past periods of cheap fossil fuels and abundant agricultural production, farmers and society in general displayed limited interest in energy costs and in crop and livestock production residuals. The events of the 1970's, including rising energy prices, restricted energy supplies, and growing awareness of the Impact of confined livestock feeding on world food supplies, have given rise to interest in new and old technologies that con serve energy use in agriculture and to the need for adjustments in current agricultural production practices.
Dynamic Duopoly Theory And Rational Expectations, 2016 Iowa State University
Dynamic Duopoly Theory And Rational Expectations, Harvey E. Lapan
The determination of equilibrium prices and quantities in an oligopolistic market has been a troublesome problem for economic theory# The intrinsic nature of the problem is the interdependence of firms - the profit level of any firm depends upon not only aggregate demand and its own output level, but also on the output level of other firms. Thus, each firm, in choosing its own output level, needs to make some behavioral assumption —or conjecture - about how other firms will respond to these changes in output.
Modeling Consumption With Limited Dependent Variables: Applications To Pork And Cheese, 2016 University of Illinois at Urbana-Champaign
Modeling Consumption With Limited Dependent Variables: Applications To Pork And Cheese, Steven T. Yen, Helen H. Jensen
The double-hurdle and infrequency-of-purchase models are applied to pork and cheese consumption using the 1987-88 Nationwide Food Consumption Survey data. Own-price effects on the probability and level of consumption are negative and significant for both pork and cheese, while income and cross-price effects are not significant.
Estimated Correlations Among Days For The Combined 1989-91 Csfii, 2016 Iowa State University
Estimated Correlations Among Days For The Combined 1989-91 Csfii, Alicia L. Carriquiry, Wayne A. Fuller, Juan José Goyeneche, Helen H. Jensen
Data obtained from dietary intake surveys are often used to estimate the proportion of the population with insufficient (or excessive) intake of certain dietary components. The authors present a two-step method for obtaining smooth estimates of day-to-day correlations for nutrient intake, and their standard errors, when dietary data are collected on consecutive days.
Takens Theorem With Singular Spectrum Analysis Applied To Noisy Time Series, 2016 East Tennessee State University
Takens Theorem With Singular Spectrum Analysis Applied To Noisy Time Series, Thomas K. Torku
Electronic Theses and Dissertations
The evolution of big data has led to financial time series becoming increasingly complex, noisy, non-stationary and nonlinear. Takens theorem can be used to analyze and forecast nonlinear time series, but even small amounts of noise can hopelessly corrupt a Takens approach. In contrast, Singular Spectrum Analysis is an excellent tool for both forecasting and noise reduction. Fortunately, it is possible to combine the Takens approach with Singular Spectrum analysis (SSA), and in fact, estimation of key parameters in Takens theorem is performed with Singular Spectrum Analysis. In this thesis, we combine the denoising abilities of SSA with the Takens ...
Examining Cost Functionality And Optimization: A Case Study On Testing The Reasonableness Of New Aircraft Using Historical Aircraft Data, 2016 Washington University in St. Louis
Examining Cost Functionality And Optimization: A Case Study On Testing The Reasonableness Of New Aircraft Using Historical Aircraft Data, Katherine Jozefiak
Arts & Sciences Electronic Theses and Dissertations
When pursuing business by competing for government contracts, proving the submitted price is reasonable is often required. This proof is called a test of reasonableness. This study analyzes data from historical aircraft programs in relation of a new aircraft program in order to demonstrate the estimated cost of the new program is reasonable. The purpose of this study is to investigate three questions. Is the new program cost reasonable using current industry and government parameters? Is it better to look at programs from a total cost perspective or break the total cost into subcategory levels? Finally, this study applies a ...
Construction Of Pair-Wise Balanced Design, 2016 Manonmaniam Sundaranar University
Construction Of Pair-Wise Balanced Design, Rajarathinam Arunachalam, Mahalakshmi Sivasubramanian, Dilip Kumar Ghosh
Journal of Modern Applied Statistical Methods
A new procedure for construction of pair wise balanced design with equal replication and un-equal block sizes based on factorial design have been evolved. Numerical illustration also provided. It was found that the constructed pair wise balanced design was found to be universal optimal.
Implementing Propensity Score Matching With Network Data: The Effect Of Gatt On Bilateral Trade, 2016 Universitat Pompeu Fabra
Implementing Propensity Score Matching With Network Data: The Effect Of Gatt On Bilateral Trade, Luca De Benedictis, Bruno Arpino, Alessandra Mattei
Luca De Benedictis
Predicting Financial Distress: A Comparison Of Survival Analysis And Decision Tree Techniques, Adrian Gepp, Kuldeep Kumar
Financial distress and then the consequent failure of a business is usually an extremely costly and disruptive event. Statistical financial distress prediction models attempt to predict whether a business will experience financial distress in the future. Discriminant analysis and logistic regression have been the most popular approaches, but there is also a large number of alternative cutting - edge data mining techniques that can be used. In this paper, a semi-parametric Cox survival analysis model and non-parametric CART decision trees have been applied to financial distress prediction and compared with each other as well as the most popular approaches. This analysis ...
Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, 2016 Fox Chase Cancer Center
Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang
COBRA Preprint Series
Non-negative matrix factorization (NMF) is a widely used machine learning algorithm for dimension reduction of large-scale data. It has found successful applications in a variety of fields such as computational biology, neuroscience, natural language processing, information retrieval, image processing and speech recognition. In bioinformatics, for example, it has been used to extract patterns and profiles from genomic and text-mining data as well as in protein sequence and structure analysis. While the scientific performance of NMF is very promising in dealing with high dimensional data sets and complex data structures, its computational cost is high and sometimes could be critical for ...
Models For Hsv Shedding Must Account For Two Levels Of Overdispersion, 2016 University of Washington - Seattle Campus
Models For Hsv Shedding Must Account For Two Levels Of Overdispersion, Amalia Magaret
UW Biostatistics Working Paper Series
We have frequently implemented crossover studies to evaluate new therapeutic interventions for genital herpes simplex virus infection. The outcome measured to assess the efficacy of interventions on herpes disease severity is the viral shedding rate, defined as the frequency of detection of HSV on the genital skin and mucosa. We performed a simulation study to ascertain whether our standard model, which we have used previously, was appropriately considering all the necessary features of the shedding data to provide correct inference. We simulated shedding data under our standard, validated assumptions and assessed the ability of 5 different models to reproduce the ...
A Structural Equation Model Correlating Success In Engineering With Academic Variables For Community College Transfer Students, Marcia Laugerman, Mack Shelley
Mack C Shelley II
Student Enrollment and Engagement through Connections is a collaboration between a large Midwestern university and in-state community colleges (CCs) to increase success of transfers into engineering. This study explores predictors of completing a BS in engineering for CC transfers through a structural equation model. The model was estimated using academic variables from both institutions. The dataset includes 472 in-state CC transfer students admitted to the College of Engineering between 2002 and 2005. The model fits the data well (χ2=74.254, df=30, p<0.0001; RMSE=0.056, Comparative Fit Index=0.984, chi-square/df ratio=2.475). First ...
Development In Normal Mixture And Mixture Of Experts Modeling, 2016 University of Kentucky
Development In Normal Mixture And Mixture Of Experts Modeling, Meng Qi
Theses and Dissertations--Statistics
In this dissertation, first we consider the problem of testing homogeneity and order in a contaminated normal model, when the data is correlated under some known covariance structure. To address this problem, we developed a moment based homogeneity and order test, and design weights for test statistics to increase power for homogeneity test. We applied our test to microarray about Down’s syndrome. This dissertation also studies a singular Bayesian information criterion (sBIC) for a bivariate hierarchical mixture model with varying weights, and develops a new data dependent information criterion (sFLIC).We apply our model and criteria to birth- weight ...
Multi-State Models With Missing Covariates, 2016 University of Kentucky
Multi-State Models With Missing Covariates, Wenjie Lou
Theses and Dissertations--Statistics
Multi-state models have been widely used to analyze longitudinal event history data obtained in medical studies. The tools and methods developed recently in this area require the complete observed datasets. While, in many applications measurements on certain components of the covariate vector are missing on some study subjects. In this dissertation, several likelihood-based methodologies were proposed to deal with datasets with different types of missing covariates efficiently when applying multi-state models.
Firstly, a maximum observed data likelihood method was proposed when the data has a univariate missing pattern and the missing covariate is a categorical variable. The construction of the ...
Space-Time Modelling Of Emerging Infectious Diseases: Assessing Leptospirosis Risk In Sri Lanka, 2016 Wilfrid Laurier University
Space-Time Modelling Of Emerging Infectious Diseases: Assessing Leptospirosis Risk In Sri Lanka, Cameron C F Plouffe
Theses and Dissertations (Comprehensive)
In this research, models were developed to analyze leptospirosis incidence in Sri Lanka and its relation to rainfall. Before any leptospirosis risk models were developed, rainfall data were evaluated from an agro-ecological monitoring network for producing maps of total monthly rainfall in Sri Lanka. Four spatial interpolation techniques were compared: inverse distance weighting, thin-plate splines, ordinary kriging, and Bayesian kriging. Error metrics were used to validate interpolations against independent data. Satellite data were used to assess the spatial pattern of rainfall. Results indicated that Bayesian kriging and splines performed best in low and high rainfall, respectively. Rainfall maps generated from ...
Predicting Higher Education Graduation Rates From Institutional Characteristics And Resource Allocation, 2015 Iowa State University
Predicting Higher Education Graduation Rates From Institutional Characteristics And Resource Allocation, Florence Hamrick, John Schuh, Mack Shelley
Mack C Shelley II
This study incorporated institutional characteristics (e.g., Carnegie type, selectivity) and resource allocations (e.g., instructional expenditures, student affairs expenditures) into a statistical model to predict undergraduate graduation rates. Instructional expenditures, library expenditures, and a number of institutional classification variables were significant predictors of graduation rates. Based on these results, recommendations as well as warranted cautions are included about allocating academic financial resources to optimize graduation rates
Confidence Intervals For The Population Mean Tailored To Small Sample Sizes, With Applications To Survey Sampling, 2015 Center for AIDS Prevention Studies, Department of Medicine, University of California, San Francisco
Confidence Intervals For The Population Mean Tailored To Small Sample Sizes, With Applications To Survey Sampling, Michael Rosenblum, Mark Van Der Laan
Michael Rosenblum MD
The validity of standard confidence intervals constructed in survey sampling is based on the central limit theorem. For small sample sizes, the central limit theorem may give a poor approximation, resulting in confidence intervals that are misleading. We discuss this issue and propose methods for constructing confidence intervals for the population mean tailored to small sample sizes. We present a simple approach for constructing confidence intervals for the population mean based on tail bounds for the sample mean that are correct for all sample sizes. Bernstein's inequality provides one such tail bound. The resulting confidence intervals have guaranteed coverage ...
Using Regression Models To Analyze Randomized Trials: Asymptotically Valid Hypothesis Tests Despite Incorrectly Specified Models, 2015 Division of Biostatistics, School of Public Health, University of California, Berkeley
Using Regression Models To Analyze Randomized Trials: Asymptotically Valid Hypothesis Tests Despite Incorrectly Specified Models, Michael Rosenblum, Mark Van Der Laan
Michael Rosenblum MD
Regression models are often used to test for cause-effect relationships from data collected in randomized trials or experiments. This practice has deservedly come under heavy scrutiny, since commonly used models such as linear and logistic regression will often not capture the actual relationships between variables, and incorrectly specified models potentially lead to incorrect conclusions. In this paper, we focus on hypothesis test of whether the treatment given in a randomized trial has any effect on the mean of the primary outcome, within strata of baseline variables such as age, sex, and health status. Our primary concern is ensuring that such ...
A Statistical Model For The Prediction Of Dissolved Oxygen Dynamics And The Potential For Hypoxia In The Mississippi Sound And Bight, 2015 University of Southern Mississippi
A Statistical Model For The Prediction Of Dissolved Oxygen Dynamics And The Potential For Hypoxia In The Mississippi Sound And Bight, Andreas Moshogianis
Hypoxia events occur when dissolved oxygen concentrations fall below the minimum threshold (dissolved oxygen concentrations < 2 mg O2 L-1) necessary to avoid respiratory distress among aquatic organisms. In the Mississippi Sound and Bight, hypoxia is most prevalent from late-spring through late summer. Since hypoxia events can have dramatic effects on coastal fisheries, the spatial and temporal magnitude of hypoxia presents a clear threat to the productive fisheries in the northern Gulf of Mexico. Long-term hydrographic data were collected from eight sampling stations on a monthly basis from January 2009 to December 2011 along a cross-shelf transect from the mouth of Bay ...