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Statistical Analysis Of Wastewater Remediation And Bio-Fuels Production Of Algae, Jay D. Jones 2010 Utah State University

Statistical Analysis Of Wastewater Remediation And Bio-Fuels Production Of Algae, Jay D. Jones

All Graduate Plan B and other Reports

The Logan city wastewater treatment system consists of a series of seven large aerated ponds (460 acres) that biologically treats 15 million gallons per day of wastewater from Logan city and six other communities. Tighter regulations of allowed phosphorus levels in the effluent have recently been implemented due to environmental concerns of a downstream reservoir. The Biological Engineering program at Utah State University, the Bio-fuels Center, the Utah Water Research Laboratory (UWRL) and the city of Logan are working together to remediate the wastewater treatment system using microalgae. Algal growth requires the uptake of phosphorus. Thus, phosphorus in the effluent ...


Assessment Of Utah Bankruptcies By Census Tracts: A Spatial Statistical Approach, Kenneth Pena 2010 Utah State University

Assessment Of Utah Bankruptcies By Census Tracts: A Spatial Statistical Approach, Kenneth Pena

All Graduate Plan B and other Reports

There are two questions raised when looking at the spatial pattern of the rate of bankruptcies in Utah: (i) are there similarities between the bankruptcy data in adjacent census tracts and (ii) can local cluster and outliers be identified within the data? Specifically, are there similar rates of bankruptcies in bordering census tracts and are there any localized areas of interest where we find extremely high or extremely low rates of bankruptcies? This study uses spatial statistics to perform tests for spatial autocorrelation to address these two questions. It also looks at commonalities in the clusters and differences in the ...


Numerical Solution Of The Five-Moment Ideal Two-Fluid Equations In One Dimension, Marcus Scott 2010 Utah State University

Numerical Solution Of The Five-Moment Ideal Two-Fluid Equations In One Dimension, Marcus Scott

All Graduate Plan B and other Reports

Plasmas are frequently treated as a single conducting fluid and modeled using the equations of magnetohydrodynamics. However, this regime works better for low-frequency plasmas. High-frequency plasmas may be modeled using the principles of kinetic theory. For plasmas with frequencies between these two extremes, a two-fluid approach can yield better results. In 2006, Ammar Hakim mathematically modeled a plasma with a set of equations called the five-moment ideal two-fluid equations. An attempt is made reproduce those results. A derivation of this set of equations by taking moments of the Boltzmann equation is presented. Electric and magnetic fields contribute to the source ...


Assessing North American Influenza Dynamics With Hierarchical Spatio-Temporal Models, Jessica Anderson 2010 Utah State University

Assessing North American Influenza Dynamics With Hierarchical Spatio-Temporal Models, Jessica Anderson

All Graduate Plan B and other Reports

We present a general statistical modeling framework to characterize continental-level influenza dynamics in the United States for the purposes of examining state-level epidemiological sources and sinks. The methods we describe depend directly on state-level influenza data that are updated weekly and available on the internet. Advances in search engine query analysis have provided powerful new tools for collecting epidemiological data and, when used in conjunction with sophisticated statistical models, allow for the identification and quantification of the flow of influenza across the continental United States. Our proposed methods, when conditioned on this comprehensive search query product, can provide unprecedented scientific ...


Assessing The Precision And Accuracy In A Small Sample Of Actical Devices, Peter Sherick 2010 Utah State University

Assessing The Precision And Accuracy In A Small Sample Of Actical Devices, Peter Sherick

All Graduate Plan B and other Reports

Actigraphy is an increasingly popular approach in medicine to assess patient activity levels in a variety of scenarios. The devices are essentially accelerometers encased in a write-watch type assembly. This project sought to determine the device precision and accuracy for the Actical model. In a sample of four Acticals, it was found that intra-device variability was minimal. However, one device was found to be statistically biased in comparison to the other three. This bias could have adverse effects on aggregated or magnitude dependent data analysis. Also, inter-device comparisons may be problematic.


A Comparison Of Prediction Methods Of Functional Autoregressive Time Series, Devin Didericksen 2010 Utah State University

A Comparison Of Prediction Methods Of Functional Autoregressive Time Series, Devin Didericksen

All Graduate Plan B and other Reports

Functional data analysis (FDA) is a relatively new branch of statistics that has seen a lot of expansion recently. With the advent of computer processing power and more efficient software packages we have entered the beginning stages of applying FDA methodology and techniques to data. Part of this undertaking should include an empirical assessment of the effectiveness of some of the tools of FDA, which are sound on theoretical grounds. In a small way, this project helps advance this objective.

This work begins by introducing FDA, scalar prediction techniques, and the functional autoregressive model of order one - FAR(1). Two ...


A K-Mean-Directions Algorithm For Fast Clustering Of Data On The Sphere, Ranjan Maitra, Ivan Peter Ramler 2010 Iowa State University

A K-Mean-Directions Algorithm For Fast Clustering Of Data On The Sphere, Ranjan Maitra, Ivan Peter Ramler

Statistics Publications

A k-means-type algorithm is proposed for efficiently clustering data constrained to lie on the surface of a p-dimensional unit sphere, or data that are mean-zero-unit-variance standardized observations such as those that occur when using Euclidean distance to cluster time series gene expression data using a correlation metric. We also provide methodology to initialize the algorithm and to estimate the number of clusters in the dataset. Results from a detailed series of experiments show excellent performance, even with very large datasets. The methodology is applied to the analysis of the mitotic cell division cycle of budding yeast dataset of ...


Simulating Data To Study Performance Of Finite Mixture Modeling And Clustering Algorithms, Ranjan Maitra, Volodymyr Melnykov 2010 Iowa State University

Simulating Data To Study Performance Of Finite Mixture Modeling And Clustering Algorithms, Ranjan Maitra, Volodymyr Melnykov

Statistics Publications

A new method is proposed to generate sample Gaussian mixture distributions according to prespecified overlap characteristics. Such methodology is useful in the context of evaluating performance of clustering algorithms. Our suggested approach involves derivation of and calculation of the exact overlap between every cluster pair, measured in terms of their total probability of misclassification, and then guided simulation of Gaussian components satisfying prespecified overlap characteristics. The algorithm is illustrated in two and five dimensions using contour plots and parallel distribution plots, respectively, which we introduce and develop to display mixture distributions in higher dimensions. We also study properties of the ...


Census 2010 And Human Services And Community Development, Mark Salling, Jenita McGowan 2010 Cleveland State University

Census 2010 And Human Services And Community Development, Mark Salling, Jenita Mcgowan

Urban Publications

Census 2010 and Human Services and Community Development, Planning & Action, The Center for Community Solutions, Vol. 63, No. 2 (March), 2010, pp 1-4.


Imputation Procedures For American Community Survey Group Quarters Small Area Estimation, Chandra Erdman, Chaitra Nagaraja 2009 Fordham University

Imputation Procedures For American Community Survey Group Quarters Small Area Estimation, Chandra Erdman, Chaitra Nagaraja

Chaitra H Nagaraja

No abstract provided.


Measuring The Hiv/Aids Epidemic: Approaches And Challenges, Ron Brookmeyer 2009 University of California, Los Angeles

Measuring The Hiv/Aids Epidemic: Approaches And Challenges, Ron Brookmeyer

Ron Brookmeyer

In this article, the author reviews current approaches and methods for measuring the scope of the human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) epidemic and their strengths and weaknesses. In recent years, various public health agencies have revised statistical estimates of the scope of the HIV/AIDS pandemic. The author considers the reasons underlying these revisions. New sources of data for estimating HIV prevalence have become available, such as nationally representative probability-based surveys. New technologies such as biomarkers that indicate when persons became infected are now used to determine HIV incidence rates. The author summarizes the main sources of ...


The Effect Of Salvage Therapy On Survival In A Longitudinal Study With Treatment By Indication, Edward Kennedy, Jeremy Taylor, Douglas Schaubel, Scott Williams 2009 University of Pennsylvania

The Effect Of Salvage Therapy On Survival In A Longitudinal Study With Treatment By Indication, Edward Kennedy, Jeremy Taylor, Douglas Schaubel, Scott Williams

Edward H. Kennedy

We consider using observational data to estimate the effect of a treatment on disease recurrence, when the decision to initiate treatment is based on longitudinal factors associated with the risk of recurrence. The effect of salvage androgen deprivation therapy (SADT) on the risk of recurrence of prostate cancer is inadequately described by the existing literature. Furthermore, standard Cox regression yields biased estimates of the effect of SADT, since it is necessary to adjust for prostate-specific antigen (PSA), which is a time-dependent confounder and an intermediate variable. In this paper, we describe and compare two methods which appropriately adjust for PSA ...


Fast Function-On-Scalar Regression With Penalized Basis Expansions, Philip T. Reiss, Lei Huang, Maarten Mennes 2009 New York University

Fast Function-On-Scalar Regression With Penalized Basis Expansions, Philip T. Reiss, Lei Huang, Maarten Mennes

Lei Huang

Regression models for functional responses and scalar predictors are often fitted by means of basis functions, with quadratic roughness penalties applied to avoid overfitting. The fitting approach described by Ramsay and Silverman in the 1990s amounts to a penalized ordinary least squares (P-OLS) estimator of the coefficient functions. We recast this estimator as a generalized ridge regression estimator, and present a penalized generalized least squares (P-GLS) alternative. We describe algorithms by which both estimators can be implemented, with automatic selection of optimal smoothing parameters, in a more computationally efficient manner than has heretofore been available. We discuss pointwise confidence intervals ...


On K4 Of The Gaussian And Eisenstein Integers, Mathieu Dutour Sikiric, Herbert Gangl, Paul Gunnells, Jonathan Hanke, Achill Schürmann, Dan Yasaki 2009 University of Massachusetts - Amherst

On K4 Of The Gaussian And Eisenstein Integers, Mathieu Dutour Sikiric, Herbert Gangl, Paul Gunnells, Jonathan Hanke, Achill Schürmann, Dan Yasaki

Paul Gunnells

Abstract. In this paper we investigate the structure of the algebraic K-groups K4(Z[i]) and K4(Z[ρ]), where i := √ −1 and ρ := (1 + √ −3)/2. We exploit the close connection between homology groups of GLn(R) for n 6 5 and those of related classifying spaces, then compute the former using Voronoi’s reduction theory of positive definite quadratic and Hermitian forms to produce a very large finite cell complex on which GLn(R) acts. Our main results are (i) K4(Z[i]) is a finite abelian 3-group, and (ii) K4(Z[ρ]) is trivial.


A Prospective Cohort Study Of Modifiable Risk Factors For Gestational Diabetes Among Hispanic Women: Design And Baseline Characteristics, Lisa Chasen-Taber, R. T. Fortner, A. Gollenberg, John Buonaccorsi, N. Dole, G. Markenson 2009 University of Massachusetts - Amherst

A Prospective Cohort Study Of Modifiable Risk Factors For Gestational Diabetes Among Hispanic Women: Design And Baseline Characteristics, Lisa Chasen-Taber, R. T. Fortner, A. Gollenberg, John Buonaccorsi, N. Dole, G. Markenson

John Buonaccorsi

OBJECTIVES: Women diagnosed with gestational diabetes mellitus (GDM) are at high risk for future diabetes, with rates of GDM consistently higher in Hispanic than non-Hispanic white women. Currently recognized risk factors for GDM are absent in up to half of affected women, and studies addressing modifiable risk factors for GDM in Hispanic women are sparse. METHODS: Proyecto Buena Salud is an ongoing prospective cohort study of Hispanic women in Massachusetts designed to assess physical activity, psychosocial stress, and GDM risk. Bilingual interviewers recruit prenatal care patients early in pregnancy and assess activity, trait anxiety, perceived stress, and depressive symptoms using ...


Gibbs Sampling For A Bayesian Hierarchical General Linear Model, Alicia A. Johnson, Galin L. Jones 2009 University of Minnesota - Twin Cities

Gibbs Sampling For A Bayesian Hierarchical General Linear Model, Alicia A. Johnson, Galin L. Jones

Alicia A. Johnson

No abstract provided.


The 1905 Einstein Equation In A General Mathematical Analysis Model Of Quasars, Byron E. Bell 2009 DePaul University and Columbia College Chicago

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

Byron E. Bell

No abstract provided.


How A Bayesian Might Estimate The Distribution Of Cronbach’S Alpha From Ordinal-Dynamic Scaled Data A Case Study Measuring Nursing Home Resident Quality Of Life, Byron J. Gajewski, Diane K. Boyle, Sarah Thompson 2009 University of Kansas Medical Center

How A Bayesian Might Estimate The Distribution Of Cronbach’S Alpha From Ordinal-Dynamic Scaled Data A Case Study Measuring Nursing Home Resident Quality Of Life, Byron J. Gajewski, Diane K. Boyle, Sarah Thompson

Diane Kay Boyle PhD, RN, FAAN

We demonstrate the utility of a Bayesian based approach for calculating intervals of Cronbach’s alpha from a psychological instrument having ordinal responses with a dynamic scale. A small number of response options on an instrument will cause traditional-based interval estimates to be biased. Ordinal-based solutions are problematic because there is no clear mechanism for handling the dynamic scale. One way to remedy the bias is to adjust with a Bayesian approach. The Bayesian approach adjusts the bias and allows theoretically simple calculations of Cronbach’s alpha and intervals. We demonstrate the calculations of the Bayesian approach while at the ...


Statistical Modeling Of Agatston Score In Multi-Ethnic Study Of Atherosclerosis (Mesa), Anna Liu, S. Ma, J. Carr, W. Post, R. Kronmal 2009 University of Massachusetts - Amherst

Statistical Modeling Of Agatston Score In Multi-Ethnic Study Of Atherosclerosis (Mesa), Anna Liu, S. Ma, J. Carr, W. Post, R. Kronmal

Anna Liu

The MESA (Multi-Ethnic Study of Atherosclerosis) is an ongoing study of the prevalence, risk factors, and progression of subclinical cardiovascular disease in a multi-ethnic cohort. It provides a valuable opportunity to examine the development and progression of CAC (coronary artery calcium), which is an important risk factor for the development of coronary heart disease. In MESA, about half of the CAC scores are zero and the rest are continuously distributed. Such data has been referred to as “zero-inflated data” and may be described using two-part models. Existing two-part model studies have limitations in that they usually consider parametric models only ...


Bayesian Inference For A Periodic Stochastic Volatility Model Of Intraday Electricity Prices, Michael S. Smith 2009 Melbourne Business School

Bayesian Inference For A Periodic Stochastic Volatility Model Of Intraday Electricity Prices, Michael S. Smith

Michael Stanley Smith

The Gaussian stochastic volatility model is extended to allow for periodic autoregressions (PAR) in both the level and log-volatility process. Each PAR is represented as a first order vector autoregression for a longitudinal vector of length equal to the period. The periodic stochastic volatility model is therefore expressed as a multivariate stochastic volatility model. Bayesian posterior inference is computed using a Markov chain Monte Carlo scheme for the multivariate representation. A circular prior that exploits the periodicity is suggested for the log-variance of the log-volatilities. The approach is applied to estimate a periodic stochastic volatility model for half-hourly electricity prices ...


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