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Dissertations / Theses on the topic 'Applied Statistics'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Binter, Roman. "Applied probabilistic forecasting." Thesis, London School of Economics and Political Science (University of London), 2012. http://etheses.lse.ac.uk/559/.

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In any actual forecast, the future evolution of the system is uncertain and the forecasting model is mathematically imperfect. Both, ontic uncertainties in the future (due to true stochasticity) and epistemic uncertainty of the model (reﬂecting structural imperfections) complicate the construction and evaluation of probabilistic forecast. In almost all nonlinear forecast models, the evolution of uncertainty in time is not tractable analytically and Monte Carlo approaches (”ensemble forecasting”) are widely used. This thesis advances our understanding of the construction of forecast densities f

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2

Zhang, Bo. "Machine Learning on Statistical Manifold." Scholarship @ Claremont, 2017. http://scholarship.claremont.edu/hmc_theses/110.

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This senior thesis project explores and generalizes some fundamental machine learning algorithms from the Euclidean space to the statistical manifold, an abstract space in which each point is a probability distribution. In this thesis, we adapt the optimal separating hyperplane, the k-means clustering method, and the hierarchical clustering method for classifying and clustering probability distributions. In these modifications, we use the statistical distances as a measure of the dissimilarity between objects. We describe a situation where the clustering of probability distributions is needed

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3

Bynum, Lucius. "Modeling Subset Behavior: Prescriptive Analytics for Professional Basketball Data." Scholarship @ Claremont, 2018. https://scholarship.claremont.edu/hmc_theses/117.

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Sports analytics problems have become increasingly prominent in the past decade. Modern image processing capabilities allow coaching staff to easily capture detailed game-time statistics on their players, opponents, team configurations, and plays. The challenge is to turn that data into meaningful insights for team managers and coaches. This project uses descriptive and predictive techniques on publicly available NBA basketball data to identify powerful combinations of players and predict how they will perform against other teams.

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4

Dodson, Huey D. "Applied statistics experience & certification in quality assurance /." Click here to view, 2010. http://digitalcommons.calpoly.edu/statsp/3/.

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Thesis (B.S.)--California Polytechnic State University, 2010.<br>Project advisor: Heather Smith. Title from PDF title page; viewed on Apr. 20, 2010. Includes bibliographical references. Also available on microfiche.

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5

Lochner, Michelle Aileen Anne. "New applications of statistics in astronomy and cosmology." Doctoral thesis, University of Cape Town, 2014. http://hdl.handle.net/11427/12864.

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Includes bibliographical references.<br>Over the last few decades, astronomy and cosmology have become data-driven fields. The parallel increase in computational power has naturally lead to the adoption of more sophisticated statistical techniques for data analysis in these fields, and in particular, Bayesian methods. As the next generation of instruments comes online, this trend should be continued since previously ignored effects must be considered rigorously in order to avoid biases and incorrect scientific conclusions being drawn from the ever-improving data. In the context of supernova co

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6

Tiani, John P. "Using applied statistics to study a pharmaceutical manufacturing process." Worcester, Mass. : Worcester Polytechnic Institute, 2004. http://www.wpi.edu/Pubs/ETD/Available/etd-0430104-125344/.

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7

Fitzgerald, Damon. "Household Preferences for Financing Hurricane Risk Mitigation: A Survey Based Empirical Analysis." FIU Digital Commons, 2014. http://digitalcommons.fiu.edu/etd/1725.

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After a series of major storms over the last 20 years, the state of financing for U.S. natural disaster insurance has undergone substantial disruptions causing many federal and state backed programs against residential property damage to become severally underfunded. In order to regain actuarial soundness, policy makers have proposed a shift to a system that reflects risk-based pricing for property insurance. We examine survey responses from 1394 single-family homeowners in the state of Florida for support of several natural disaster mitigation policy reforms. Utilizing a partial proportional

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8

Liu, Xiang. "A Multi-Indexed Logistic Model for Time Series." Digital Commons @ East Tennessee State University, 2016. https://dc.etsu.edu/etd/3140.

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In this thesis, we explore a multi-indexed logistic regression (MILR) model, with particular emphasis given to its application to time series. MILR includes simple logistic regression (SLR) as a special case, and the hope is that it will in some instances also produce significantly better results. To motivate the development of MILR, we consider its application to the analysis of both simulated sine wave data and stock data. We looked at well-studied SLR and its application in the analysis of time series data. Using a more sophisticated representation of sequential data, we then detail the imp

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9

Brännström, Anton. "A Comparison of Three Methods of Estimation Applied to Contaminated Circular Data." Thesis, Umeå universitet, Statistik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-149426.

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This study compares the performance of the Maximum Likelihood estimator (MLE), estimators based on spacings called Generalized Maximum Spacing estimators (GSEs), and the One Step Minimum Hellinger Distance estimator (OSMHD), on data originating from a circular distribution. The purpose of the study is to investigate the different estimators’ performance on directional data. More specifically, we compare the estimators’ ability to estimate parameters of the von Mises distribution, which is determined by a location parameter and a scale parameter. For this study, we only look at the scenario in

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10

Brody-Moore, Peter. "Bayesian Hierarchical Meta-Analysis of Asymptomatic Ebola Seroprevalence." Scholarship @ Claremont, 2019. https://scholarship.claremont.edu/cmc_theses/2228.

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The continued study of asymptomatic Ebolavirus infection is necessary to develop a more complete understanding of Ebola transmission dynamics. This paper conducts a meta-analysis of eight studies that measure seroprevalence (the number of subjects that test positive for anti-Ebolavirus antibodies in their blood) in subjects with household exposure or known case-contact with Ebola, but that have shown no symptoms. In our two random effects Bayesian hierarchical models, we find estimated seroprevalences of 8.76% and 9.72%, significantly higher than the 3.3% found by a previous meta-analysis of t

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11

Lesser, Elizabeth Rochelle. "A New Right Tailed Test of the Ratio of Variances." UNF Digital Commons, 2016. http://digitalcommons.unf.edu/etd/719.

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It is important to be able to compare variances efficiently and accurately regardless of the parent populations. This study proposes a new right tailed test for the ratio of two variances using the Edgeworth’s expansion. To study the Type I error rate and Power performance, simulation was performed on the new test with various combinations of symmetric and skewed distributions. It is found to have more controlled Type I error rates than the existing tests. Additionally, it also has sufficient power. Therefore, the newly derived test provides a good robust alternative to the already existing me

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12

Andersson, Carl. "Deep learning applied to system identification : A probabilistic approach." Licentiate thesis, Uppsala universitet, Avdelningen för systemteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-397563.

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Machine learning has been applied to sequential data for a long time in the field of system identification. As deep learning grew under the late 00's machine learning was again applied to sequential data but from a new angle, not utilizing much of the knowledge from system identification. Likewise, the field of system identification has yet to adopt many of the recent advancements in deep learning. This thesis is a response to that. It introduces the field of deep learning in a probabilistic machine learning setting for problems known from system identification. Our goal for sequential modelin

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13

Theisen, Benjamin. "Predicting Turnover Cognition in Applied Behavior Analysis Supervisors." Thesis, The Chicago School of Professional Psychology, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10934198.

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<p> The study looked for predictors of turnover cognition among program supervisors at various applied behavior analysis organizations. A hierarchical regression model (<i>n</i> = 248) tested whether burnout moderated effects of training hours on turnover cognition, and whether burnout moderated effects of training procedures on turnover cognition. The best model (R<sup> 2</sup> = .719, delta <i>F</i> (2, 239) = 3.22, <i>p</i> = .042) did not detect burnout. Results were interpreted using the Conservation of Resources theory. Recommendations for researchers and organizations planning superviso

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Melbourne, Davayne A. "A New method for Testing Normality based upon a Characterization of the Normal Distribution." FIU Digital Commons, 2014. http://digitalcommons.fiu.edu/etd/1248.

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The purposes of the thesis were to review some of the existing methods for testing normality and to investigate the use of generated data combined with observed to test for normality. The approach to testing for normality is in contrast to the existing methods which are derived from observed data only. The test of normality proposed follows a characterization theorem by Bernstein (1941) and uses a test statistic D*, which is the average of the Hoeffding’s D-Statistic between linear combinations of the observed and generated data to test for normality. Overall, the proposed method showed consid

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15

Saket, Munther Musa. "Cost-significance applied to estimating and control of construction projects." Thesis, University of Dundee, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.276578.

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Rosa, Joao Miguel Feu. "Mathematical programming applied to diet problems in a Brazilian region." Thesis, Lancaster University, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.332375.

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17

Chun, So Yeon. "Hybrid is good: stochastic optimization and applied statistics for or." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/44717.

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In the first part of this thesis, we study revenue management in resource exchange alliances. We first show that without an alliance the sellers will tend to price their products too high and sell too little, thereby foregoing potential profit, especially when capacity is large. This provides an economic motivation for interest in alliances, because the hope may be that some of the foregone profit may be captured under an alliance. We then consider a resource exchange alliance, including the effect of the alliance on competition among alliance members. We show that the foregone profit may inde

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18

Risk, James Kenneth. "Three Applications of Gaussian Process Modeling in Evaluation of Longevity Risk Management." Thesis, University of California, Santa Barbara, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10620897.

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<p> Longevity risk, the risk associated with people living too long, is an emerging issue in financial markets. Two major factors related to this are with regards to mortality modeling and pricing of life insurance instruments. We propose use of Gaussian process regression, a technique recently populuarized in machine learning, to aid in both of these problems. In particular, we present three works using Gaussian processes in longevity risk applications. The first is related to pricing, where Gaussian processes can serve as a surrogate for conditional expectation needed for Monte Carlo simulat

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19

Shafie, H. Khalil. "The geometry of Gaussian rotation space random fields /." Thesis, McGill University, 1998. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=35614.

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In recent years, very detailed images of the brain, produced by modern sensor technologies, have given the neuroscientist the opportunity to study the functional activation of the brain under different conditions. The main statistical problem is to locate the isolated regions of the brain where activation has occurred (the signal), and separate them from the rest of the brain where no activation can be detected (the noise). To do this the images are often spatially smoothed before analysis by convolution with a filter f (t) to enhance the signal to noise ratio, where t is a location vec

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20

Zhou, Xiaojie. "Optimal designs for change point problems." Thesis, McGill University, 1997. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=35667.

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This thesis investigates Bayesian optimal design for change-point problems. While there is a large optimal design literature for linear and some non-linear problems, this is the first time optimality has been addressed for change-point problems.<br>In designing a longitudinal study, the decision as to when to collect data can have a large impact on the quality of the final inferences. If a change may occur in the distribution of one or more variables under study, the timing of observations can greatly influence the chances of detecting any effects.<br>Two classes of problems are considered. Fi

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21

Peng, Yuanyuan. "On Singular Values of Random Matrices." Kent State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=kent1438253068.

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22

Yin, Kai. "Bayesian Uncertainty Quantification for Differential Equation Models Related to Financial Volatility and Disease Transmission." Case Western Reserve University School of Graduate Studies / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=case1623863667837324.

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23

Elkadry, Alaa. "Statistical Analyses of "Randomly Sourced Data"." Thesis, Oakland University, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10262484.

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<p> Warner in 1965 introduced randomized response, and since then many extensions and improvements to the Warner model have been done. In this study a randomized response model applicable to continuous data that considers a mixture of two normal distributions is considered and analyzed. This includes a study of the efficiency, an estimation of some unknown parameters and a discussion of contaminated data issues and an application of this method to the problem of estimating Oakland University student income is presented and discussed. Also, this study includes inference for two or more populati

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Bahuguna, Manoj. "Analytics of Asymmetry and Transformation to Multivariate Normality Through Copula Functions with Applications in Biomedical Sciences and Finance." Thesis, Oakland University, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10263461.

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<p> In this work, we study and develop certain aspects of the analytics of asymmetry for univariate and multivariate data. Accordingly, the above work consists of three separate parts.</p><p> In the first part of our work, we introduce a new approach to measure the univariate and multivariate skewness based on quantiles and the properties of odd and even functions. We illustrate through numerous examples and simulations that in the multivariate case the Mardia’s measure of skewness fails to provide consistent and meaningful interpretations. However, our new measure appears to provide a

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25

Rialland, P. C. R. P. "Three essays in applied microeconomics." Thesis, University of Essex, 2018. http://repository.essex.ac.uk/23688/.

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This thesis focuses on three vulnerable groups in Europe that have recently been highlighted both in media and in the economics literature; and that are policy priorities. Chapter 1 is a joint work with Giovanni Mastrobuoni which focuses on prisoners and peer effects in prison. Studies that estimate criminal peer effects need to define the reference group. Researchers usually use the amount of time inmates overlap in prison, sometimes in combination with nationality to define such groups. Yet, there is often little discussion about such assumptions, which could potentially have important effec

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McIntosh, Alasdair. "Interpretable models of genetic drift applied especially to human populations." Thesis, University of Glasgow, 2018. http://theses.gla.ac.uk/30690/.

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This thesis aims to develop and implement population genetic models that are directly interpretable in terms of events such as population fission and admixture. Two competing methods of approximating the Wright--Fisher model of genetic drift are critically examined, one due to Balding and Nichols and another to Nicholson and colleagues. The model of population structure consisting of all present-day subpopulations arising from a common ancestral population at a single fission event (first described by Nicholson et al.) is reimplemented and applied to single-nucleotide polymorphism data from th

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27

Donnelly, James P. "NFL Betting Market: Using Adjusted Statistics to Test Market Efficiency and Build a Betting Model." Scholarship @ Claremont, 2013. http://scholarship.claremont.edu/cmc_theses/721.

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The use of statistical analysis has been prevalent in the sports gambling industry for years. More recently, we have seen the emergence of "adjusted statistics", a more sophisticated way to examine each play and each result (further explanation below). And while adjusted statistics have become commonplace for professional and recreational bettors alike, little research has been done to justify their use. In this paper the effectiveness of this data is tested on the most heavily wagered sport in the world – the National Football League (NFL). The results are studied with two central questions i

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Wardrop, Daniel M. "Optimality criteria applied to certain response surface designs." Diss., Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/49960.

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The estimation of a particular matrix of coefficients of a second-order polynomial model was shown to be important in Response Surface Methodology (RSM). This led naturally to designing RSM experiments for best estimation of these coefficients as a primary goal. A design criterion, D<sub>S</sub>-optimality, was applied to several classes of RSM designs to find optimal choices of design parameters. Further, previous results on D-optimal RSM designs were extended. The designs resulting from the use of the two criteria were compared. Two other design criteria were also studied. These were IV, th

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Ay, Belit, and Nabiel Efrem. "Benford’s law applied to sale prices on the Swedish housing market." Thesis, Stockholms universitet, Statistiska institutionen, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-194865.

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Benford’s law is based on an observation that certain digits occur more often than others in a set of numbers. This have provided researchers to apply the law in different areas including identifying digit patterns and manipulated data. To our knowledge, this have yet not been tested in the Swedish housing market. The purpose of this thesis is to examine whether the sale price for 171 643 tenant-owned apartments in Stockholm, Gothenburg and Malmö follow Benford’s law. Numerous researchers have used this law for testing various types of data but based solely on the first digit distribution of t

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Howard, Marylesa Marie. "Computational methods for support vector machine classification and large-scale Kalman filtering." Thesis, University of Montana, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=3568109.

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<p> The first half of this dissertation focuses on computational methods for solving the constrained quadratic program (QP) within the support vector machine (SVM) classifier. One of the SVM formulations requires the solution of bound and equality constrained QPs. We begin by describing an augmented Lagrangian approach which incorporates the equality constraint into the objective function, resulting in a bound constrained QP. Furthermore, all constraints may be incorporated into the objective function to yield an unconstrained quadratic program, allowing us to apply the conjugate gradient (CG)

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Raissi, Maziar. "Multi-fidelity Stochastic Collocation." Thesis, George Mason University, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=3591697.

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<p> Over the last few years there have been dramatic advances in our understanding of mathematical and computational models of complex systems in the presence of uncertainty. This has led to a growth in the area of uncertainty quantification as well as the need to develop efficient, scalable, stable and convergent computational methods for solving differential equations with random inputs. Stochastic Galerkin methods based on polynomial chaos expansions have shown superiority to other non-sampling and many sampling techniques. However, for complicated governing equations numerical implementati

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Ruffin, Michael. "User retention and classification in a mobile gaming environment." Thesis, California State University, Long Beach, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=1527021.

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<p> Game analytics is a fast growing field where game studios are allocating valuable resources to develop sophisticated statistical models to understand user behavior and monetization habits to optimize game play and performance. Game developers' ability to understand user retention allows for game features that will generate high engagement leading to stronger overall monetization and increased lifetimes of players. </p><p> One important industry adopted metric is the percentage of users who log back into the game one day after installation, otherwise known as a one-day retention. Although

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33

McCants, Michael. "Efficacy of robust regression applied to fractional factorial treatment structures." Thesis, Kansas State University, 2011. http://hdl.handle.net/2097/9260.

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Master of Science<br>Department of Statistics<br>James J. Higgins<br>Completely random and randomized block designs involving n factors at each of two levels are used to screen for the effects of a large number of factors. With such designs it may not be possible either because of costs or because of time to run each treatment combination more than once. In some cases, only a fraction of all the treatments may be run. With a large number of factors and limited observations, even one outlier can adversely affect the results. Robust regression methods are designed to down-weight the adverse affe

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Eiland, E. Earl. "A Coherent Classifier/Prediction/Diagnostic Problem Framework and Relevant Summary Statistics." Thesis, New Mexico Institute of Mining and Technology, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10617960.

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<p> Classification is a ubiquitous decision activity. Regardless of whether it is predicting the future, e.g., a weather forecast, determining an existing state, e.g., a medical diagnosis, or some other activity, classifier outputs drive future actions. Because of their importance, classifier research and development is an active field.</p><p> Regardless of whether one is a classifier developer or an end user, evaluating and comparing classifier output quality is important. Intuitively, classifier evaluation may seem simple, however, it is not. There is a plethora of classifier summary stati

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Chernoff, Parker. "Sabermetrics - Statistical Modeling of Run Creation and Prevention in Baseball." FIU Digital Commons, 2018. https://digitalcommons.fiu.edu/etd/3663.

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The focus of this thesis was to investigate which baseball metrics are most conducive to run creation and prevention. Stepwise regression and Liu estimation were used to formulate two models for the dependent variables and also used for cross validation. Finally, the predicted values were fed into the Pythagorean Expectation formula to predict a team’s most important goal: winning. Each model fit strongly and collinearity amongst offensive predictors was considered using variance inflation factors. Hits, walks, and home runs allowed, infield putouts, errors, defense-independent earned run aver

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36

Book, Emil, and Linus Ekelöf. "A Multiple Linear Regression Model To Assess The Effects of Macroeconomic Factors On Small and Medium-Sized Enterprises." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254298.

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Small and medium-sized enterprises (SMEs) have long been considered the backbone in any country’s economy for their contribution to growth and prosperity. It is therefore of great importance that the government and legislators adopt policies that optimise the success of SMEs. Recent concerns of an impending recession has made this topic even more relevant since small companies will have greater difficulty withstanding such an event. This thesis will focus on the effects of macroeconomic factors on SMEs in Sweden, with the usage of multiple linear regression. Data was collected for a 10 year pe

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Zhi, Tianchen. "Maximum Likelihood Estimation of Parameters in Exponential Power Distribution with Upper Record Values." FIU Digital Commons, 2017. http://digitalcommons.fiu.edu/etd/3211.

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The exponential power (EP) distribution is a very important distribution that was used by survival analysis and related with asymmetrical EP distribution. Many researchers have discussed statistical inference about the parameters in EP distribution using i.i.d random samples. However, sometimes available data might contain only record values, or it is more convenient for researchers to collect record values. We aim to resolve this problem. We estimated two parameters of the EP distribution by MLE using upper record values. According to simulation study, we used the Bias and MSE of the estimato

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Williams, Ulyana P. "On Some Ridge Regression Estimators for Logistic Regression Models." FIU Digital Commons, 2018. https://digitalcommons.fiu.edu/etd/3667.

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The purpose of this research is to investigate the performance of some ridge regression estimators for the logistic regression model in the presence of moderate to high correlation among the explanatory variables. As a performance criterion, we use the mean square error (MSE), the mean absolute percentage error (MAPE), the magnitude of bias, and the percentage of times the ridge regression estimator produces a higher MSE than the maximum likelihood estimator. A Monto Carlo simulation study has been executed to compare the performance of the ridge regression estimators under different experimen

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Jacobson, Daniel A. "Networks and multivariate statistics as applied to biological datasets and wine-related omics." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/85630.

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Thesis (PhD)--Stellenbosch University, 2013.<br>ENGLISH ABSTRACT: Introduction: Wine production is a complex biotechnological process aiming at productively coordinating the interactions and outputs of several biological systems, including grapevine and many microorganisms such as wine yeast and wine bacteria. High-throughput data generating tools in the elds of genomics, transcriptomics, proteomics, metabolomics and microbiomics are being applied both locally and globally in order to better understand complex biological systems. As such, the datasets available for analysis and mining

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Araújo, Daniel Costa. "Channel estimation techniques applied to massive MIMO systems using sparsity and statistics approaches." reponame:Repositório Institucional da UFC, 2016. http://www.repositorio.ufc.br/handle/riufc/23478.

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ARAÚJO, D. C. Channel estimation techniques applied to massive MIMO systems using sparsity and statistics approaches. 2016. 124 f. Tese (Doutorado em Engenharia de Teleinformática)–Centro de Tecnologia, Universidade Federal do Ceará, Fortaleza, 2016.<br>Submitted by Renato Vasconcelos (ppgeti@ufc.br) on 2017-06-21T13:52:26Z No. of bitstreams: 1 2016_tese_dcaraújo.pdf: 1832588 bytes, checksum: a4bb5d44287b92a9321d5fcc3589f22e (MD5)<br>Approved for entry into archive by Marlene Sousa (mmarlene@ufc.br) on 2017-06-21T16:17:55Z (GMT) No. of bitstreams: 1 2016_tese_dcaraújo.pdf: 1832588 bytes, chec

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Gard, Rikard. "Design-based and Model-assisted estimators using Machine learning methods : Exploring the k-Nearest Neighbor metod applied to data from the Recreational Fishing Survey." Thesis, Örebro universitet, Handelshögskolan vid Örebro Universitet, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-72488.

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Chu, Chi-Yang. "Applied Nonparametric Density and Regression Estimation with Discrete Data| Plug-In Bandwidth Selection and Non-Geometric Kernel Functions." Thesis, The University of Alabama, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10262364.

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<p> Bandwidth selection plays an important role in kernel density estimation. Least-squares cross-validation and plug-in methods are commonly used as bandwidth selectors for the continuous data setting. The former is a data-driven approach and the latter requires <i>a priori</i> assumptions about the unknown distribution of the data. A benefit from the plug-in method is its relatively quick computation and hence it is often used for preliminary analysis. However, we find that much less is known about the plug-in method in the discrete data setting and this motivates us to propose a plug-in ban

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Albaqshi, Amani Mohammed H. "Generalized Partial Least Squares Approach for Nominal Multinomial Logit Regression Models with a Functional Covariate." Thesis, University of Northern Colorado, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10599676.

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<p> Functional Data Analysis (FDA) has attracted substantial attention for the last two decades. Within FDA, classifying curves into two or more categories is consistently of interest to scientists, but multi-class prediction within FDA is challenged in that most classification tools have been limited to binary response applications. The functional logistic regression (FLR) model was developed to forecast a binary response variable in the functional case. In this study, a functional nominal multinomial logit regression (F-NM-LR) model was developed that shifts the FLR model into a multiple log

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Paciencia, Todd J. "Improving non-linear approaches to anomaly detection, class separation, and visualization." Thesis, Air Force Institute of Technology, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3667806.

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<p> Linear approaches for multivariate data analysis are popular due to their lower complexity, reduced computational time, and easier interpretation. In many cases, linear approaches produce adequate results; however, non-linear methods may generate more robust transformations, features, and decision boundaries. Of course, these non-linear methods present their own unique challenges that often inhibit their use. </p><p> In this research, improvements to existing non-linear techniques are investigated for the purposes of providing better, timely class separation and improved anomaly detectio

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Fregosi, Anna. "Calibration of Thermal Soil Properties in the Shallow Subsurface." Thesis, North Carolina State University, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10110538.

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<p> We use nonlinear least squares methods and Bayesian inference to calibrate soil properties using models for heat and groundwater transport in the shallow subsurface. We first assume a constant saturation in our domain and use the analytic solution to the heat equation as a model for heat transport. We compare our results to those using the finite element code, Adaptive Hydrology (ADH). We then use ADH to simulate heat and groundwater transport in an unsaturated domain. We use the Model-Independent Parameter Estimation (PEST) software to solve the least squares problem with ADH as our model

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Pipher, Brandon. "Comparison of Regression Methods with Non-Convex Penalties." Kent State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=kent1573056251025985.

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Crk, Vladimir 1958. "Component and system reliability assessment from degradation data." Diss., The University of Arizona, 1998. http://hdl.handle.net/10150/282820.

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Reliability estimation of highly reliable components, subsystems and systems has become very difficult using the traditional accelerated life tests. Therefore, there is a need to develop new models that will determine the reliability of such components, systems or subsystems, one of which is modeling a long term performance degradation. The proposed method is more general than any of the existing ones. It can be applied to any system, subsystem or component whose degradation over time can be identified and measured. It is assumed that the performance degradation is caused by a number, d, of in

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Smith, Laura. "A Numerical Simulation and Statistical Modeling of High Intensity Radiated Fields Experiment Data." W&M ScholarWorks, 2001. https://scholarworks.wm.edu/etd/1539626330.

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Olsen, Jessica Lyn. "An Applied Investigation of Gaussian Markov Random Fields." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/3273.

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Recently, Bayesian methods have become the essence of modern statistics, specifically, the ability to incorporate hierarchical models. In particular, correlated data, such as the data found in spatial and temporal applications, have benefited greatly from the development and application of Bayesian statistics. One particular application of Bayesian modeling is Gaussian Markov Random Fields. These methods have proven to be very useful in providing a framework for correlated data. I will demonstrate the power of GMRFs by applying this method to two sets of data; a set of temporal data involving

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Zhao, Yang, and Min Zhang. "The Ising Model on a Heavy Gravity Portfolio Applied to Default Contagion." Thesis, Högskolan i Halmstad, Tillämpad matematik och fysik (MPE-lab), 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-16459.

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In this paper we introduce a model of default contagion in the financail market. The structure of the companies are represented by a Heavy Gravity Portfolio, where we assume there are N sectors in the market and in each sector i, there is one big trader and ni supply companies.The supply companies in each sector are directly inuenced by the bigtrader and the big traders are also pairwise interacting with each other.This development of the Ising model is called Heavy gravity portfolioand according to this, the relation between expectation and correlationof the default of companies are derived b

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