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Articles 1 - 28 of 28
Full-Text Articles in Statistical Models
A Regionalized National Universal Kriging Model Using Partial Least Squares Regression For Estimating Annual Pm2.5 Concentrations In Epidemiology, Paul D. Sampson, Mark Richards, Adam A. Szpiro, Silas Bergen, Lianne Sheppard, Timothy V. Larson, Joel Kaufman
A Regionalized National Universal Kriging Model Using Partial Least Squares Regression For Estimating Annual Pm2.5 Concentrations In Epidemiology, Paul D. Sampson, Mark Richards, Adam A. Szpiro, Silas Bergen, Lianne Sheppard, Timothy V. Larson, Joel Kaufman
UW Biostatistics Working Paper Series
Many cohort studies in environmental epidemiology require accurate modeling and prediction of fine scale spatial variation in ambient air quality across the U.S. This modeling requires the use of small spatial scale geographic or “land use” regression covariates and some degree of spatial smoothing. Furthermore, the details of the prediction of air quality by land use regression and the spatial variation in ambient air quality not explained by this regression should be allowed to vary across the continent due to the large scale heterogeneity in topography, climate, and sources of air pollution. This paper introduces a regionalized national universal kriging …
An Analysis Of Risk Reduction Choices In Dcis Breast Cancer Patients, Lauren Soltesz
An Analysis Of Risk Reduction Choices In Dcis Breast Cancer Patients, Lauren Soltesz
Statistics
The main focus of this paper was to evaluate possible demographic and clinical characteristics associated with a woman’s choice of breast conserving surgery (BCS), unilateral mastectomy (ULM), or bilateral risk reduction mastectomy (BRRM). The cohort consisted of patients presenting to the City of Hope National Medical Center with ductal carcinoma in situ breast cancer who elected to have cancer directed surgery (N=305). Analyses to examine associations of patient characteristics with type of surgery were conducted using a multinomial logistic regression. Results showed that older women were more likely to choose breast conserving surgery over bilateral risk reduction mastectomy than younger …
Stress-Lifetime Joint Distribution Model For Performance Degradation Failure, Quan Sun, Yanzhen Tang, Jing Feng, Paul Kvam
Stress-Lifetime Joint Distribution Model For Performance Degradation Failure, Quan Sun, Yanzhen Tang, Jing Feng, Paul Kvam
Department of Math & Statistics Faculty Publications
The high energy density self-healing metallized film pulse capacitor has been applied to all kinds of laser facilities for their power conditioning systems under several stress levels, such as 23kV, 30kV and 35kV, whose reliability performance and maintenance costs are affected by the reliability of capacitors. Due to the costs and time restriction, how to assess the reliability of highly reliable capacitors under a certain stress level as soon as possible becomes a challenge. Accelerated degradation test provides a way to predict its lifetime and reliability effectively. A model called stress-lifetime joint distribution model and an analysis method based on …
An Economic Alternative To The C Chart, Ryan William Black
An Economic Alternative To The C Chart, Ryan William Black
Graduate Theses and Dissertations
Because the probability of Type I error is not evenly distributed beyond upper and lower three-sigma limits the c chart is theoretically inappropriate for a monitor of Poisson distributed phenomena. Furthermore, the normal approximation to the Poisson is of little use when c is small. These practical and theoretical concerns should motivate the computation of true error rates associated with individuals control assuming the Poisson distribution. An economic alternative to the c chart is described as a statistical model of upward shift from c0 to c1 and the two charts are compared in theory. For a range of c chart …
Finding A Better Confidence Interval For A Single Regression Changepoint Using Different Bootstrap Confidence Interval Procedures, Bodhipaksha Thilakarathne
Finding A Better Confidence Interval For A Single Regression Changepoint Using Different Bootstrap Confidence Interval Procedures, Bodhipaksha Thilakarathne
College of Graduate Studies: Theses & Dissertations
Recently a number of papers have been published in the area of regression changepoints but there is not much literature concerning confidence intervals for regression changepoints. The purpose of this paper is to find a better bootstrap confidence interval for a single regression changepoint. ("Better" confidence interval means having a minimum length and coverage probability which is close to a chosen significance level). Several methods will be used to find bootstrap confidence intervals. Among those methods a better confidence interval will be presented.
An Economic Analysis Of Wine Grape Production In The State Of Connecticut, Jeremy L. Jelliffe
An Economic Analysis Of Wine Grape Production In The State Of Connecticut, Jeremy L. Jelliffe
Master's Theses
The Connecticut Wine and Vineyard industry has grown at a steady 3.9% per year over the past decade (ATTTB, 2009). Economic models estimate that the wineries sub-sector contributes $38 million dollars to the state economy and direct employment of 106 residents (Lopez et al., 2010). Programs to support and foster further growth of the industry and CT farm vineyard culture include the Department of Agriculture’s CT Wine Trail and the annual CT Wine festival (DOAG, 2010). Farmland preservation groups also support vineyard development since grape growing tends to secure tracts of farmland for long periods of time.
Investment analysis for …
Sensitivity Of Limiting Hurricane Intensity To Ocean Warmth, James B. Elsner, Sarah Strazzo, Jill C. Trepanier, Thomas H. Jagger
Sensitivity Of Limiting Hurricane Intensity To Ocean Warmth, James B. Elsner, Sarah Strazzo, Jill C. Trepanier, Thomas H. Jagger
Publications
No abstract provided.
Comparative Analysis Of Dispersion Parameter Estimates In Loglinear Modeling: Applied To E-Commerce Sales And Customer Data, Scott Davis
Statistics
When loglinear models are applied to count data the issue of over-dispersion often arises. Moment and maximum likelihood estimation methods in accounting for over-dispersion are widely used because they allow for model checking tools such as Chi-square, F, and likelihood ratio tests. Here is a comparison between R functions that each uses one method; glm.nb uses MLE, and glm.poisson.disp uses MME. The Index of Dissimilarity and visual model selection (ECDF plots) are also incorporated. These are applied to sales data using product and customer information compiled over the last five years that was generously provided by an e-commerce company.
Retrieval Of Sub-Pixel-Based Fire Intensity And Its Application For Characterizing Smoke Injection Heights And Fire Weather In North America, David Peterson
Retrieval Of Sub-Pixel-Based Fire Intensity And Its Application For Characterizing Smoke Injection Heights And Fire Weather In North America, David Peterson
Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research
For over two decades, satellite sensors have provided the locations of global fire activity with ever-increasing accuracy. However, the ability to measure fire intensity, know as fire radiative power (FRP), and its potential relationships to meteorology and smoke plume injection heights, are currently limited by the pixel resolution. This dissertation describes the development of a new, sub-pixel-based FRP calculation (FRPf) for fire pixels detected by the MODerate Resolution Imaging Spectroradiometer (MODIS) fire detection algorithm (Collection 5), which is subsequently applied to several large wildfire events in North America. The methodology inherits an earlier bi-spectral algorithm for retrieving sub-pixel …
Significant Themes In 19th-Century Literature, Matthew L. Jockers, David Mimno
Significant Themes In 19th-Century Literature, Matthew L. Jockers, David Mimno
Department of English: Faculty Publications
External factors such as author gender, author nationality, and date of publication affect both the choice of literary themes in novels and the expression of those themes, but the extent of this association is difficult to quantify. In this work, we apply statistical methods to identify and extract hundreds of "topics" from a corpus of 3,346 works of 19th-century British, Irish, and American fiction. We use these topics as a measurable, data-driven proxy for literary themes. External factors may predict fluctuations in the use of themes and the individual word choices within themes. We use topics to measure the evidence …
Bayesian Approaches To Assessing Architecture And Stopping Rule, Joseph W. Houpt, Andrew Heathcote, Ami Eidels, J. T. Townsend
Bayesian Approaches To Assessing Architecture And Stopping Rule, Joseph W. Houpt, Andrew Heathcote, Ami Eidels, J. T. Townsend
Psychology Faculty Publications
Much of scientific psychology and cognitive science can be viewed as a search to understand the mechanisms and dynamics of perception, thought and action. Two processing attributes of particular interest to psychologists are the architecture, or temporal relationships between sub-processes of the system, and the stopping rule, which dictates how many of the sub-processes must be completed for the system to finish. The Survivor Interaction Contrast (SIC) is a powerful tool for assessing the architecture and stopping rule of a mental process model. Thus far, statistical analysis of the SIC has been limited to null-hypothesis- significance tests. In this talk …
Rank-Based Estimation And Prediction For Mixed Effects Models In Nested Designs, Yusuf K. Bilgic
Rank-Based Estimation And Prediction For Mixed Effects Models In Nested Designs, Yusuf K. Bilgic
Dissertations
Hierarchical designs frequently occur in many research areas. The experimental design of interest is expressed in terms of fixed effects but, for these designs, nested factors are a natural part of the experiment. These nested effects are generally considered random and must be taken into account in the statistical analysis. Traditional analyses are quite sensitive to outliers and lose considerable power to detect the fixed effects of interest.
This work proposes three rank-based fitting methods for handling random, fixed and scale effects in k-level nested designs for estimation and inference. An algorithm, which iteratively obtains robust prediction for both scale …
The Interacting Multiple Models Algorithm With State-Dependent Value Assignment, Rastin Rastgoufard
The Interacting Multiple Models Algorithm With State-Dependent Value Assignment, Rastin Rastgoufard
LSU New Orleans Theses and Dissertations
The value of a state is a measure of its worth, so that, for example, waypoints have high value and regions inside of obstacles have very small value. We propose two methods of incorporating world information as state-dependent modifications to the interacting multiple models (IMM) algorithm, and then we use a game's player-controlled trajectories as ground truths to compare the normal IMM algorithm to versions with our proposed modifications. The two methods involve modifying the model probabilities in the update step and modifying the transition probability matrix in the mixing step based on the assigned values of different target states. …
Bayesian And Related Methods: Techniques Based On Bayes' Theorem, Mehmet Vurkaç
Bayesian And Related Methods: Techniques Based On Bayes' Theorem, Mehmet Vurkaç
Systems Science Friday Noon Seminar Series
Bayes' theorem is a simple algebraic consequence of conditional probability. Yet, its consequences are critical to philosophy, society, and technology. Starting from its simple derivation, we will show how its interpretation in terms of base rates (priors) and class-conditional likelihoods illuminates everyday problems in medicine and law, and provides signal processing, communications, machine learning, model selection, and other applications of statistics with powerful classification and estimation tools. Next, we will briefly examine some of the ways in which this theorem can be adopted to include multiple attributes, contexts, hypotheses, and levels of risk. Methods derived from or related to Bayes’ …
A Normal Truncated Skewed-Laplace Model In Stochastic Frontier Analysis, Junyi Wang
A Normal Truncated Skewed-Laplace Model In Stochastic Frontier Analysis, Junyi Wang
Masters Theses & Specialist Projects
Stochastic frontier analysis is an exciting method of economic production modeling that is relevant to hospitals, stock markets, manufacturing factories, and services. In this paper, we create a new model using the normal distribution and truncated skew-Laplace distribution, namely the normal-truncated skew-Laplace model. This is a generalized model of the normal-exponential case. Furthermore, we compute the true technical efficiency and estimated technical efficiency of the normal-truncated skewed-Laplace model. Also, we compare the technical efficiencies of normal-truncated skewed-Laplace model and normal-exponential model.
Using The R Library Rpanel For Gui-Based Simulations In Introductory Statistics Courses, Ryan M. Allison
Using The R Library Rpanel For Gui-Based Simulations In Introductory Statistics Courses, Ryan M. Allison
Statistics
As a student, I noticed that the statistical package R (http://www.r-project.org) would have several benefits of its usage in the classroom. One benefit to the package is its free and open-source nature. This would be a great benefit for instructors and students alike since it would be of no cost to use, unlike other statistical packages. Due to this, students could continue using the program after their statistical courses and into their professional careers. It would be good to expose students while they are in school to a tool that professionals use in industry. R also has powerful …
Differential Patterns Of Interaction And Gaussian Graphical Models, Masanao Yajima, Donatello Telesca, Yuan Ji, Peter Muller
Differential Patterns Of Interaction And Gaussian Graphical Models, Masanao Yajima, Donatello Telesca, Yuan Ji, Peter Muller
COBRA Preprint Series
We propose a methodological framework to assess heterogeneous patterns of association amongst components of a random vector expressed as a Gaussian directed acyclic graph. The proposed framework is likely to be useful when primary interest focuses on potential contrasts characterizing the association structure between known subgroups of a given sample. We provide inferential frameworks as well as an efficient computational algorithm to fit such a model and illustrate its validity through a simulation. We apply the model to Reverse Phase Protein Array data on Acute Myeloid Leukemia patients to show the contrast of association structure between refractory patients and relapsed …
Light Vs. Quantum Gravity, Irving Martinez^*
Light Vs. Quantum Gravity, Irving Martinez^*
COURI Symposium Abstracts, Spring 2012
No abstract provided.
Finding Dynamic Treatment Effects Under Anticipation: Spanking Effects On Behavior, Myoung-Jae Lee, Fali Huang
Finding Dynamic Treatment Effects Under Anticipation: Spanking Effects On Behavior, Myoung-Jae Lee, Fali Huang
Research Collection School Of Economics
The dynamic treatment effect literature considers multiple treatments administered over time, with some treatments affected by interim outcomes. But the literature overlooks the possibility of individuals acting in anticipation of future treatments. This lack of anticipation aspect may not matter in the drug–response relationships which motivated the literature. But human beings (or animals with some intelligence) do not just respond to current and past treatments, but also ‘reflect and anticipate’ future treatments. For example, a punishment or reward is likely to prompt forward looking. Even if no personal punishment or reward is involved, people may take action in anticipation of …
C2bat: A Novel Method For Association Between Ge- Netic Markers And Multiple Phenotypes, Melissa Naylor, Christoph Lange
C2bat: A Novel Method For Association Between Ge- Netic Markers And Multiple Phenotypes, Melissa Naylor, Christoph Lange
Harvard University Biostatistics Working Paper Series
The purpose of this technical report is to describe a novel method developed to detect association between a genetic marker and multiple phenotypes. In order to obtain a one-degree of freedom test, a generalized principal component approach is suggested that aggregates the information about the genetic effect in the first prin- cipal component, while the remain principal components contain only environment noise. A limited simulation study is done validating the method. For scenarios in which the genetic effect is constant across all measurements and there is no envi- ronmental correlation between the measurements, preliminary results suggest that this method has …
The Quotient Of The Beta-Weibull Distribution, Nonhle Channon Mdziniso
The Quotient Of The Beta-Weibull Distribution, Nonhle Channon Mdziniso
Theses, Dissertations and Capstones
A new class of distributions recently developed involves the logit of the beta distribution. Among this class of distributions are, the beta-Normal (Eugene et al. [15]); beta-Gumbel (Nadarajah and Kotz [18]); beta-Exponential (Nadarajah and Kotz [19]); beta-Weibull (Famoye et al. [6]); beta-Rayleigh (Akinsete and Lowe [3]); beta-Laplace (Kozubowshi and Nadarajah [20]); and beta-Pareto (Akinsete et al. [4]), among a few others. Many useful statistical properties arising from these distributions and their applications to real life data have been discussed in literature. One approach by which a new statistical distribution is generated is by the transformation of random variables having known …
The Analysis Of Acute Stroke Clinical Trials With Responder Analysis Outcomes, Kyra Michelle Garofolo
The Analysis Of Acute Stroke Clinical Trials With Responder Analysis Outcomes, Kyra Michelle Garofolo
MUSC Theses and Dissertations
Traditionally in acute stroke clinical trials, the primary outcome has been a dichotomized modified Rankin Scale (mRS). The mRS is a 7-point ordinal scale indicating a patient's level of disability following a stroke. Traditional analyses have used a fixed dichotomization scheme, which dichotomizes 'success' as an mRS of 0-1 or 0-2. This method fails to address the concern that stroke severity may impact the likelihood of a successful outcome; subjects with mild strokes may achieve the defined threshold for success more easily than subjects with severe strokes. Consequently, subjects are unable to contribute equally to the estimation of treatment effect. …
Grts And Graphs: Monitoring Natural Resources In Urban Landscapes, Todd R. Lookingbill, John Paul Schmit, Shawn L. Carter
Grts And Graphs: Monitoring Natural Resources In Urban Landscapes, Todd R. Lookingbill, John Paul Schmit, Shawn L. Carter
Geography and the Environment Faculty Publications
Environmental monitoring programs are an important tool for providing land managers with a scientific basis for management decisions. However, many ecological processes operate on spatial scales that transcend management boundaries (Schonewald-Cox 1988). For example, adjacent lands may influence protected-area resources via edge effects, source-sink dynamics, or invasion processes (Jones et al. 2009). Hydrologic alterations outside management units also may have profound effects on the integrity of resources being managed (Pringle 2000). The impacts of climate change are presenting challenges to resource management at local-to-global scales (Karl et al. 2009). This potential disparity between ecological and political boundaries presents an interesting …
The Role Of Cd147 In Breast Cancer Progression, George Daniel Grass
The Role Of Cd147 In Breast Cancer Progression, George Daniel Grass
MUSC Theses and Dissertations
In the U.S., approximately 40,000 women will die from breast cancer this year, while an additional 230,500 women will be newly diagnosed with invasive breast disease. Despite tremendous advancement leading to earlier detection and novel therapeutic approaches, recurrent metastatic breast cancer remains a major cause of mortality. Invasive breast cancer cells employ specialized actin-rich protrusions called invadopodia, which are enriched in proteases, to degrade the extracellular matrix and these structures correlate with metastasis in vivo. The multifunctional immunoglobulin superfamily protein emmprin (CD147) is highly enriched on the surface of malignant breast cancer cells and is associated with matrix metalloproteinase (MMP) …
Alternatives To Mixture Model Analysis Of Correlated Binomial Data, N. Rao Chaganty, Roy Sabo, Yihao Deng
Alternatives To Mixture Model Analysis Of Correlated Binomial Data, N. Rao Chaganty, Roy Sabo, Yihao Deng
Mathematics & Statistics Faculty Publications
While univariate instances of binomial data are readily handled with generalized linear models, cases of multivariate or repeated measure binomial data are complicated by the possibility of correlated responses. Likelihood-based estimation can be applied by using mixture distribution models, though this approach can present computational challenges. The logistic transformation can be used to bypass these concerns and allow for alternative estimating procedures. One popular alternative is the generalized estimating equation (GEE) method, though systematic errors can lead to infeasible correlation estimates or nonconvergence problems. Our approach is the coupling of quasileast squares (QLSs) method with a rarely used matrix factorization, …
Analysis Of Binary Data Via Spatial-Temporal Autologistic Regression Models, Zilong Wang
Analysis Of Binary Data Via Spatial-Temporal Autologistic Regression Models, Zilong Wang
Theses and Dissertations--Statistics
Spatial-temporal autologistic models are useful models for binary data that are measured repeatedly over time on a spatial lattice. They can account for effects of potential covariates and spatial-temporal statistical dependence among the data. However, the traditional parametrization of spatial-temporal autologistic model presents difficulties in interpreting model parameters across varying levels of statistical dependence, where its non-negative autocovariates could bias the realizations toward 1. In order to achieve interpretable parameters, a centered spatial-temporal autologistic regression model has been developed. Two efficient statistical inference approaches, expectation-maximization pseudo-likelihood approach (EMPL) and Monte Carlo expectation-maximization likelihood approach (MCEML), have been proposed. Also, Bayesian …
General Recognition Theory Extended To Include Response Times: Predictions For A Class Of Parallel Systems, James T. Townsend, Joseph W. Houpt, Noah H. Silbert
General Recognition Theory Extended To Include Response Times: Predictions For A Class Of Parallel Systems, James T. Townsend, Joseph W. Houpt, Noah H. Silbert
Psychology Faculty Publications
General Recognition Theory (GRT; Ashby & Townsend, 1986) is a multidimensional theory of classification. Originally developed to study various types of perceptual independence, it has also been widely employed in diverse cognitive venues, such as categorization. The initial theory and applications have been static, that is, lacking a time variable and focusing on patterns of responses, such as confusion matrices. Ashby proposed a parallel, dynamic stochastic version of GRT with application to perceptual independence based on discrete linear systems theory with imposed noise (Ashby, 1989). The current study again focuses on cognitive/perceptual independence within an identification classification paradigm. We extend …
Analysis Of Discrete Choice Probit Models With Structured Correlation Matrices, Bhaskara Ravi
Analysis Of Discrete Choice Probit Models With Structured Correlation Matrices, Bhaskara Ravi
Mathematics & Statistics Theses & Dissertations
Discrete choice models are very popular in Economics and the conditional logit model is the most widely used model to analyze consumer choice behavior, which was introduced in a seminal paper by McFadden (1974). This model is based on the assumption that the unobserved factors, which determine the consumer choices, are independent and follow a Gumbel distribution, widely known as the Independence of irrelevant Alternatives (IIA) assumption. Alternate models that relax IIA assumption are the Generalized Extreme Value (GEV) models, which allow dependency between unobserved factors. However, GEV models do not incorporate all dependency patterns, other choice behaviors such as …