Dissertations / Theses: 'Correlation (Statistics)'

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Conrad, III Dallis G. "Speckle Statistics of Articulating Objects." University of Dayton / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1320673424.

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Abdalmajid, Mohammed Babekir Elmalik. "An application of factor analysis on a 24-item scale on the attitudes towards AIDS precautions using Pearson, Spearman and Polychoric correlation matrices." Thesis, University of the Western Cape, 2006. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_8765_1184324798.

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The 24-item scale has been used extensively to assess the attitudes towards AIDS precautions. This study investigated the usefulness and validity of the instrument in a South African setting, fourteen years after the development of the instrument. If a new structure could be found statistically, the HIV/AIDS prevention strategies could be more effective in aiding campaigns to change attitudes and sexual behaviour.

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Wood, Christopher. "Higher order statistics in photon-correlation spectroscopy." Thesis, University of Nottingham, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.267626.

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Penman, David Binnie. "Random graphs with correlation structure." Thesis, University of Sheffield, 1998. http://etheses.whiterose.ac.uk/14768/.

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In this thesis we consider models of random graphs where, unlike in the classical models G (n, p) the probability of an edge arising can be correlated with that of other edges arising. Attention focuses on graphs whose vertices are each assigned a colour (type) at random and where edges between differently coloured vertices subsequently arise with different probabilities (so-called RRC graphs), especially the special case with two colours. Various properties of these graphs are considered, often by comparing and contrasting them with the classical model with the same probability of each particular edge existing. Topics examined include the probabilities of trees and cycles, how the joint probability of two subgraphs compares with the product of their probabilities, the number of edges in the graph (including large deviations results), connectedness, connectivity, the number and order of complete graphs and cliques, and tournaments with correlation structure.

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Smoljanovic, Lada. "The estimation of intraclass correlation coefficients." Thesis, University of Hull, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.301491.

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Fridline, Mark M. "Almost Sure Confidence Intervals for the Correlation Coefficient." Cleveland, Ohio : Case Western Reserve University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=case1258999665.

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Thesis(Ph.D.)--Case Western Reserve University, 2010
Title from PDF (viewed on 2009-12-22) Department of Statistics Includes abstract Includes bibliographical references and appendices Available online via the OhioLINK ETD Center

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Pei, Yanbo. "Statistical inference for correlated binary data from bilateral studies." HKBU Institutional Repository, 2009. http://repository.hkbu.edu.hk/etd_ra/1077.

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Hamdi, Walaa Ahmed. "Local Distance Correlation: An Extension of Local Gaussian Correlation." Bowling Green State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1589239468129597.

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Vargas-Guzman, Jose Antonio 1961. "Scaling variances, correlation and principal components with multivariate geostatistics." Diss., The University of Arizona, 1998. http://hdl.handle.net/10150/282813.

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A new concept of dispersion (cross) covariance has been introduced for the modeling of spatial scale dependent multivariate correlations. Such correlations between attributes depend on the spatial size of the domain and size of samples in the population and have been modeled by first time in this research. Modeled correlations have been used to introduce a new scale dependent principal component analysis (PCA) method. This method is based on computation of eigen values and vectors from dispersion covariance matrices or scale dependent correlations which can be modeled from integrals of matrix variograms. For second order stationary random functions this PCA converges for large domains to the classic PCA. A new technique for computing variograms from spatial variances have also been developed using derivatives. For completeness, a deeper analysis of the linear model of coregionalizations widely used in multivariate geostatistics has been included as well. This last part leads to a new more sophisticated model we termed "linear combinations coregionalization model." This whole research explains the relationship between different average states and the micro- state of vector random functions in the framework of geostatistics. Examples have been added to illustrate the practical application of the theory. This approach will be useful in all earth sciences and particularly in soil and environmental sciences.

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Ma, Ping Hang. "Disagreement : estimation of relative bias or discrepancy rate." Thesis, University of British Columbia, 1987. http://hdl.handle.net/2429/26445.

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Not only basic research in sciences, but also medicine, law, and manufacturing need statistical techniques, including graphics, to assess disagreement. For some items or individuals ⍳ = 1,2,---,ո suppose that pairs (X⍳,Y⍳) denote each item's measurements by two distinct methods or by two observers, or X⍳ and Y⍳ may be initial and repeat measurement scores, with discrepancy D⍳ = X⍳ - Y⍳. Disagreement may be characterized by location and scale parameters of discrepancy distributions. The present work primarily addresses estimation of central tendency - relative bias or median discrepancy (or discrepancy rate in some instances). Most previous literature on "agreement" or "reliability" instead concerns X, Y correlation, which can be regarded as the complement of discrepancy variance. (There is ambiguity or confusion about concepts of "reliability" in the literature of various applications.) Discrepancies D₁, D₂, • • •, Dո in practice often violate assumptions of standard statistical models and methods that have been commonly applied in studies of agreement. In particular, both X⍳ and Y⍳ generally incorporate measurement errors. Further, these two measurement error distributions for the ⍳th item need not be the same; and both distributions could depend on the magnitude µ⍳, of the item being measured. Hence, for example, discrepancy D⍳ could have variance proportional to the size of the item; and in general D₁, D₂, • • •, Dո are not identically distributed. Finally, the selection of items ⍳ = 1,2, • • •, ո often is not random. To estimate median discrepancy, we consider nonparametric confidence intervals corresponding to Student t test, sign test, Wilcoxon signed rank test, or other permutation tests. Several criteria are developed to compare the performance of one procedure relative to another, including expected ratio of confidence interval lengths (related to Pitman asymptotic relative efficiency of tests) and relative variability of interval lengths. Theoretical calculations and Monte Carlo simulation results suggest different procedural preferences for random sampling from different distributions. For discrepancies distributed non-identically, but symmetrically about a common median value, mixture sampling is used as an approximate model. This approach is related to a "random walk" (rather than random sample) model of D₁, D₂, • • •, Dո proposed particularly for discrepancies between counting processes. We also emphasize graphic methods, especially plots of difference of Y - X versus average (X + Y)/2, for exploratory analysis of discrepancy data and to choose appropriate statistical models and numerical methods. Various data sets are analyzed as examples of the methodology.
Science, Faculty of
Statistics, Department of
Graduate

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11

Tang, Yuxiao. "Inference on cross correlation with repeated measures data." Columbus, Ohio : Ohio State University, 2004. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1078857542.

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Thesis (Ph. D.)--Ohio State University, 2004.
Title from first page of PDF file. Document formatted into pages; contains xiii, 116 p.; also includes graphics. Includes abstract and vita. Advisor: H.N. Nagaraja, Dept. of Statistics. Includes bibliographical references (p. 113-116).

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Sun, Jianhua. "Polyphase sequences with good correlation and low PAPR /." View abstract or full-text, 2007. http://library.ust.hk/cgi/db/thesis.pl?ECED%202007%20SUN.

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Wilson, Celia M. "Attenuation of the Squared Canonical Correlation Coefficient Under Varying Estimates of Score Reliability." Thesis, University of North Texas, 2010. https://digital.library.unt.edu/ark:/67531/metadc30528/.

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Research pertaining to the distortion of the squared canonical correlation coefficient has traditionally been limited to the effects of sampling error and associated correction formulas. The purpose of this study was to compare the degree of attenuation of the squared canonical correlation coefficient under varying conditions of score reliability. Monte Carlo simulation methodology was used to fulfill the purpose of this study. Initially, data populations with various manipulated conditions were generated (N = 100,000). Subsequently, 500 random samples were drawn with replacement from each population, and data was subjected to canonical correlation analyses. The canonical correlation results were then analyzed using descriptive statistics and an ANOVA design to determine under which condition(s) the squared canonical correlation coefficient was most attenuated when compared to population Rc2 values. This information was analyzed and used to determine what effect, if any, the different conditions considered in this study had on Rc2. The results from this Monte Carlo investigation clearly illustrated the importance of score reliability when interpreting study results. As evidenced by the outcomes presented, the more measurement error (lower reliability) present in the variables included in an analysis, the more attenuation experienced by the effect size(s) produced in the analysis, in this case Rc2. These results also demonstrated the role between and within set correlation, variable set size, and sample size played in the attenuation levels of the squared canonical correlation coefficient.

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Matshawule, Siyambonga Donald. "Probing the large-scale structure of the universe with correlation functions." Thesis, University of the Western Cape, 2014. http://hdl.handle.net/11394/4280.

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>Magister Scientiae - MSc
In this project we explore a new statistical package called KSTAT that computes the 2PCF and higher order correlation functions, such as the 3PCF, on BOSS, making use of high performance computing facilities to improve optimization. The higher order statistics such as the 3PCF can be used to probe primordial non-Gaussianity. We present the first and most precise measurements of the reduced 3PCF (Q) measured using KSTAT on the DR10 data release at higher redshift, DR10 CMASS p z 0:5q and LOWZ p z 0:3q. Our reduced 3PCF results at low redshift z 0:3 are consistent with those of McBride et al. (2011a) at z 0:104 in the SDSS LRG sample. In this initial analysis, we have found no evidence of evolution of the 3PCF on small and large scales, however we do observe the characteristic U shape of the reduced 3PCF as one increases scale

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15

Hill, Raymond R. "Multivariate Sampling With Explicit Correlation Induction For Simulation and Optimization Studies /." The Ohio State University, 1996. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487931993469621.

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Latour, Dominique. "Equalities and inequalities for canonical correlation coefficients, with emphasis on the two-way layout of experimental design." Thesis, McGill University, 1987. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=63827.

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17

Gu, Hong, and 谷紅. "Influence diagnostics in principal components and canonical analyses." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B31238518.

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Morris, Erica Jane. "The design and evaluation of Link : a CAL system designed to address psychology students' misconceptions about correlation." n.p, 1999. http://library7.open.ac.uk/abstracts/page.php?thesisid=81.

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19

He, Qinying. "Inference on correlation from incomplete bivariate samples." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1180468775.

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20

Chang, Patrick. "High-frequency correlation dynamics: Is the Epps effect a bias?" Master's thesis, Faculty of Science, 2021. http://hdl.handle.net/11427/33682.

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We tackle the question of whether Trade and Quote data from high-frequency finance are representative of discrete connected events, or whether these measurements can still be faithfully represented as random samples of some underlying Brownian diffusion in the context of modelling correlation dynamics. In particular, if the implicit notion of instantaneous correlation dynamics that are independent of the time-scale a reasonable assumption. To this end, we apply kernel averaging non-uniform fast Fourier transforms in the context of the Malliavin-Mancino integrated and instantaneous volatility estimators to speed up the estimators. We demonstrate the implicit time-scale investigated by the estimator by comparing it to the theoretical Epps effect arising from asynchrony. We compare the Malliavin-Mancino and Cuchiero-Teichmann Fourier instantaneous estimators and demonstrate the relationship between the instantaneous Epps effect and the cutting frequencies in the Fourier estimators. We find that using the previous tick interpolation in the Cuchiero-Teichmann estimator results in unstable estimates when dealing with asynchrony, while the ability to bypass the time domain with the Malliavin-Mancino estimator allows it to produce stable estimates and is therefore better suited for ultra high-frequency finance. We derive the Epps effect arising from asynchrony and provide a refined approach to correct the effect. We compare methods to correct for the Epps effect arising from asynchrony when the underlying process is a Brownian diffusion, and when the underlying process is from discrete connected events (proxied using a D-type Hawkes process). We design three experiments using the Epps effect to discriminate the underlying processes. These experiments demonstrate that using a Hawkes representation recovers the empiricism reported in the literature under simulation conditions that cannot be achieved when using a Brownian representation. The experiments are applied to Trade and Quote data from the Johannesburg Stock Exchange and the evidence suggests that the empirical measurements are from a system of discrete connected events where correlations are an emergent property of the time-scale rather than an instantaneous quantity that exists at all time-scales.

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Li, Xiaobo. "Neural network based exchange-correlation functional." Click to view the E-thesis via HKUTO, 2007. http://sunzi.lib.hku.hk/HKUTO/record/B3955899X.

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Li, Xiaobo, and 李曉博. "Neural network based exchange-correlation functional." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B3955899X.

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23

Moore, Julie Carolyn. "Comparisons of correlation methods in risk analysis." Thesis, This resource online, 1994. http://scholar.lib.vt.edu/theses/available/etd-06102009-063246/.

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24

Mu, Jun. "VHF radar aurora, statistics, fading and correlation with optical aurora." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1996. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq24039.pdf.

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25

Marjerison, William M. "Bayesian Logistic Regression with Spatial Correlation: An Application to Tennessee River Pollution." Digital WPI, 2006. https://digitalcommons.wpi.edu/etd-theses/1115.

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"We analyze data (length, weight and location) from a study done by the Army Corps of Engineers along the Tennessee River basin in the summer of 1980. The purpose is to predict the probability that a hypothetical channel catfish at a location studied is toxic and contains 5 ppm or more DDT in its filet. We incorporate spatial information and treate it separetely from other covariates. Ultimately, we want to predict the probability that a catfish from the unobserved location is toxic. In a preliminary analysis, we examine the data for observed locations using frequentist logistic regression, Bayesian logistic regression, and Bayesian logistic regression with random effects. Later we develop a parsimonious extension of Bayesian logistic regression and the corresponding Gibbs sampler for that model to increase computational feasibility and reduce model parameters. Furthermore, we develop a Bayesian model to impute data for locations where catfish were not observed. A comparison is made between results obtained fitting the model to only observed data and data with missing values imputed. Lastly, a complete model is presented which imputes data for missing locations and calculates the probability that a catfish from the unobserved location is toxic at once. We conclude that length and weight of the fish have negligible effect on toxicity. Toxicity of these catfish are mostly explained by location and spatial effects. In particular, the probability that a catfish is toxic decreases as one moves further downstream from the source of pollution."

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Hoyle, B. S. "Position vector sensing from airborne vehicles using a correlation-based method." Thesis, University of Huddersfield, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.372382.

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27

Wiedemann, Eric A. "Reducing variance between two systems by inducing correlation." Thesis, Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/23345.

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Jia, Liyi. "Modeling the Correlation Structure of RNA Sequencing Data Using A Multivariate Poisson-Lognormal Model." Thesis, The George Washington University, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10149691.

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High-throughput sequencing technologies have been widely used in biomedical research, especially in human genomic studies. RNA Sequencing (RNA-seq) applies high-throughput sequencing technologies to quantify gene expression, study alternatively spliced gene and discover novel isoform.

Poisson distribution based methods have been popularly used to model RNA-seq data in practice. Differential expression analysis of RNA-seq data has been well studied. However, the correlation structure of RNA-seq data has not been extensively studied.

The dissertation proposes a multivariate Poisson-lognormal model for the correlation structure of RNA-seq data. This approach enables us to estimate both positive and negative correlations for the count-type RNA-seq data. Three general scenarios have been discussed. In scenario 1, one exon with one isoform, we propose a bivariate Poisson-lognormal model. In scenario 2, multiple exons with one isoform, we propose a multivariate Poisson-lognormal model. Extending to multiple exons level, the number of pairwise correlations increases accordingly. To reduce the parameter space, the block compound symmetry correlation structure has been introduced. And in scenario 3, multiple exons with multiple isoforms, we propose a mixture of multivariate Poisson-lognormal models.

Correlation coefficients are estimated by the method of moments. At multiple exons level, we apply the average weighting strategy to reduce the number of moment equations. Simulation studies have been conducted and demonstrate the advantage of our correlation coefficient moment estimator, comparing to Pearson correlation coefficient estimator and Spearman's rank correlation coefficient estimator.

For application illustrations, we apply our methods to the RNA-seq data from The Cancer Genome Atlas (TCGA, breast cancer study). We estimate the correlation coefficient between gene TP53 and gene CDKN1A with normal subjects. The results show that TP53 and CDKN1A are slightly negative correlated.

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Zeimer, Michael A. "Selection of pure error generators for simulation experiments." Thesis, This resource online, 1992. http://scholar.lib.vt.edu/theses/available/etd-11242009-020207/.

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Zhang, Ju. "Trans-Ancestral Genetic Correlation Estimates from Summary Statistics for Admixed Populations." Case Western Reserve University School of Graduate Studies / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=case1619455882746982.

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31

Huang, Na. "Estimation of covariance, correlation and precision matrices for high-dimensional data." Thesis, London School of Economics and Political Science (University of London), 2016. http://etheses.lse.ac.uk/3371/.

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The thesis concerns estimating large correlation and covariance matrices and their inverses. Two new methods are proposed. First, tilting-based methods are proposed to estimate the precision matrix of a p-dimensional random variable, X, when p is possibly much larger than the sample size n. Each 2 by 2 block indexed by (i, j) of the precision matrix can be estimated by the inversion of the pairwise sample conditional covariance matrix of Xi and Xj controlling for all the other variables. However, in the high dimensional setting, including too many or irrelevant controlling variables may distort the results. To determine the controlling subsets, the tilting technique is applied to measure the contribution of each remaining variable to the covariance matrix of Xi and Xj , and only puts the (hopefully) highly relevant remaining variables into the controlling subsets. Four types of tilting-based methods are introduced and the properties are demonstrated. The simulation results are presented under different scenarios for the underlying precision matrix. The second method NOVEL Integration of the Sample and Thresholded covariance estimators (NOVELIST) performs shrinkage of the sample covariance (correlation) towards its thresholded version. The sample covariance (correlation) component is non-sparse and can be low-rank in high dimensions. The thresholded sample covariance (correlation) component is sparse, and its addition ensures the stable invertibility of NOVELIST. The benefits of the NOVELIST estimator include simplicity, ease of implementation, computational efficiency and the fact that its application avoids eigenanalysis. We obtain an explicit convergence rate in the operator norm over a large class of covariance (correlation) matrices when p and n satisfy log p/n → 0. In empirical comparisons with several popular estimators, the NOVELIST estimator performs well in estimating covariance and precision matrices over a wide range of models. An automatic algorithm for NOVELIST is developed. Comprehensive applications and real data examples of NOVELIST are presented. Moreover, intensive real data applications of NOVELIST are presented.

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32

Nelson, Kerrie P. "Generalized linear mixed models : development and comparison of different estimation methods /." Thesis, Connect to this title online; UW restricted, 2002. http://hdl.handle.net/1773/8960.

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33

余秋萍 and Chau-ping Yu. "Screening method." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1993. http://hub.hku.hk/bib/B31977558.

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Ziebell, Sara E. "A Powerful Correlation Method for Microbial Co-Occurrence Networks." Thesis, The University of Arizona, 2015. http://hdl.handle.net/10150/595812.

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Motivation: Network interpretation using correlations has several known difficulties. Firstly, the data structure has discrete counts with an excess of zeros creating non-normal non-continuous data. Secondly, correlations, often used as similarity measures in network inference, are not causal. Thirdly, there is a masking effect of mutualism on commensalism and competition on amensalism in ecological networks that interfere with interpretation (Faust and Raes, 2012). More explicitly, the symmetric nature of correlations (cor(X,Y)=cor(Y,X)) can mask the affect of the asymmetric ecology relationship (commensalism and amensalism). We aim to solve the third issue which may speed up targeted drug therapies or disease diagnosis based on specific relationships in gut microbiomes. Methods: We apply a non-symmetric correlation method, Gini Correlations which should serve as a better classifier of ecological relationships revealing a fuller picture of microbiomes. First, create simulated correlated and independent Zero-Inflated Negative Binomial data. Second, validate Gini correlations by comparing Gini with Pearson Spearman and Kendall correlations; calculate false positive rate, true positive rate, accuracy, ROC, AUC after applying Benjamini-Hochberg (1995) multiple testing correction. Simulation Result: Gini is consistent and out performs other methods for small sample sizes of 10 and 25 producing consistently low false positive rates across 64+ simulation settings as well as consistently high accuracy rates. When sample size is increased to 50 Gini performs as well as other methods. Real Data Result: For well-defined microbial communities Gini correlations found novel biologically and medically relevant relationships. However, Gini's ability to unmask non-symmetric ecological relationships is yet to be determined.

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Salmasizadeh, Mahmoud. "Statistical and correlation analysis of certain shift register based stream ciphers." Thesis, Queensland University of Technology, 1997.

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Baik, Jai Wook. "X control charts in the presence of correlation." Diss., Virginia Tech, 1991. http://hdl.handle.net/10919/39954.

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In traditional quality control charts, fixed sampling interval (FSI) schemes are used where the time between samples has fixed intervals. More efficient methods called variable sampling interval (VSI) schemes have been developed where one takes the next observation sooner than usual if there is an indication that the process is operating off the target value. Another traditional assumption behind most statistical process control charts is that the sequential observations are independent. However, there are many situations where the sequential observations should not to be treated as independent. Rather, a time series model, in particular the first order autoregressive (AR (1)) model, is appropriate. A Markov chain representation is used to study the properties of the FSI and VSI Shewhart X control charts. First, the results show that if the process variance is properly estimated and if traditional control limits are used in the FSI control charts, then the detection time is shorter when the consecutive observations are negatively correlated than when they are positively correlated. If they are positively correlated, then the false alarm rate decreases as the correlation between consecutive observations increases. On the other hand, the detection time increases as the correlation increases. In VSI control charts with traditional control limits, if the process mean is on or near the target, then the average time to signal (A TS) and average number of samples to signal (ANSS) tend to decrease as the correlation increases until the correlation becomes rather moderate. Then, for more highly correlated data, the A TS and ANSS tend to increase as the correlation increases. Next, the results show that, even under the AR (1) process, the VSI chart is more efficient than the FSI chart in terms of ATS. In contrast, the VSI chart is less efficient than the FSI chart in terms of ANSS. The efficiency (inefficiency) of ATS (ANSS) tends to decrease (increase) as the correlation between the consecutive observations becomes stronger. Steady state ATS (A TS·) and steady state ANSS (ANSSO) under the AR (1) process show the same trend as the 'regular' ATS and 'regular' ANSS except when the deviation is very large. If the deviation is very large, then the VSI control chart does not seem to be more efficient than the FSI control chart in terms of steady state ATS. If we have an AR (2) process, then for any given value of tP2 a PSI control chart has a shorter detection time when tPl is negative than when tPl is positive. In a FSI control chart, the effect of positive 2 in addition to positive tPl is that the false alarm rate decreases even further and the detection time is even longer.
Ph. D.

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Durney, Ann Wells. "Truncation and its effect on standard error of correlation coefficients." Thesis, The University of Arizona, 1990. http://hdl.handle.net/10150/277950.

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A Monte Carlo study was conducted to investigate the effect of truncation of score distributions on systematic bias and random error of correlation coefficient distributions. The findings were twofold: Correlation decreases systematically due to increasing truncation; and the standard error of the correlation coefficient, which is a measure of random error, increases due to increasing truncation.

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Zhang, Yanwei. "A hierarchical Bayesian approach to model spatially correlated binary data with applications to dental research." Diss., Connect to online resource - MSU authorized users, 2008.

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Olofsson, Isak. "@TheRealDonaldTrump’s tweets correlation with stock market volatility." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-275683.

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The purpose of this study is to analyze if there is any tweet specific data posted by Donald Trump that has a correlation with the volatility of the stock market. If any details about the president Trump's tweets show correlation with the volatility, the goal is to find a subset of regressors with as high as possible predictability. The content of tweets is used as the base for regressors. The method which has been used is a multiple linear regression with tweet and volatility data ranging from 2010 until 2020. As a measure of volatility, the Cboe VIX has been used, and the regressors in the model have focused on the content of tweets posted by Trump using TF-IDF to evaluate the content of tweets. The results from the study imply that the chosen regressors display a small significant correlation of with an adjusted R2 = 0.4501 between Trump´s tweets and the market volatility. The findings Include 78 words with correlation to stock market volatility when part of President Trump's tweets. The stock market is a large and complex system of many unknowns, which aggravate the process of simplifying and quantifying data of only one source into a regression model with high predictability.
Syftet med denna studie är att analysera om det finns några specifika egenskaper i de tweets publicerade av Donald Trump som har en korrelation med volatiliteten på aktiemarknaden. Om egenskaper kring president Trumps tweets visar ett samband med volatiliteten är målet att hitta en delmängd av regressorer med för att beskriva sambandet med så hög signifikans som möjligt. Innehållet i tweets har varit i fokus använts som regressorer. Metoden som har använts är en multipel linjär regression med tweet och volatilitetsdata som sträcker sig från 2010 till 2020. Som ett mått på volatilitet har Cboe VIX använts, och regressorerna i modellen har fokuserat på innehållet i tweets där TF-IDF har använts för att transformera ord till numeriska värden. Resultaten från studien visar att de valda regressorerna uppvisar en liten men signifikant korrelation med en justerad R2 = 0,4501 mellan Trumps tweets och marknadens volatilitet. Resultaten inkluderar 78 ord som de när en är en del av president Trumps tweets visar en signifikant korrelation till volatiliteten på börsen. Börsen är ett stort och komplext system av många okända, som försvårar processen att förenkla och kvantifiera data från endast en källa till en regressionsmodell med hög förutsägbarhet.

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Cai, Jia. "Learning gradients and canonical correlation by kernel methods /." access full-text access abstract and table of contents, 2009. http://libweb.cityu.edu.hk/cgi-bin/ezdb/thesis.pl?phd-ma-b23749349f.pdf.

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Thesis (Ph.D.)--City University of Hong Kong, 2009.
"Submitted to Department of Mathematics in partial fulfillment of the requirements for the degree of Doctor of Philosophy." Includes bibliographical references (leaves [52]-58)

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Like, Eric C. "Non-Cooperative Modulation Recognition Via Exploitation of Cyclic Statistics." Wright State University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=wright1197649202.

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42

Smith, Andrew Korb. "New results in dimension reduction and model selection." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/22586.

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Thesis (Ph. D.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2008.
Committee Chair: Huo, Xiaoming; Committee Member: Serban, Nicoleta; Committee Member: Shapiro, Alexander; Committee Member: Yuan, Ming; Committee Member: Zha, Hongyuan.

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Alabiso, Audry. "Linear Mixed Model Selection by Partial Correlation." Bowling Green State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1587142724497829.

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陳志昌 and Chee-cheong Chan. "Compositional data analysis of voting patterns." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1993. http://hub.hku.hk/bib/B31977236.

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Banerjee, Bhramori. "Multiple Testing in the Presence of Correlations." Diss., Temple University Libraries, 2011. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/210207.

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Statistics
Ph.D.
Simultaneous testing of multiple null hypotheses has now become an integral part of statistical analysis of data arising from modern scientific investigations. Often the test statistics in such multiple testing problem are correlated. The research in this dissertation is motivated by the scope of improving or extending existing methods to incorporate correlation in the data. Sarkar (2008) proposes controlling the pairwise false discovery rate (Pairwise-FDR), which inherently takes into account the dependence among the p-values, thereby making it a more robust, less conservative and more powerful under dependence than the usual notion of FDR. In this dissertation, we further investigate the performance of Pairwise-FDR under a dependent mixture model. In particular, we consider a step-up method to control the Pairwise-FDR under this model assuming that the correlation between any two p-values is the same (exchangeable). We also suggest improving this method by incorporating an estimate of the number of pairs of true null hypotheses developed under this model. Efron (2007, Journal of the American Statistical Association 102, 93-103) proposed a novel approach to incorporate dependence among the null p-values into a multiple testing method controlling false discoveries. In this dissertation, we try to investigate the scope of utilizing this approach by proposing alternative versions of adaptive Bonferroni and BH methods which estimates the number of true null hypotheses from the empirical null distribution introduced by Efron. These newer adaptive procedures have been numerically shown to perform better than existing adaptive Bonferroni or BH methods within a wider range of dependence. A gene expression microarray data set has been used to highlight the difference in results obtained upon applying the proposed and other adaptive BH methods. Another approach to address the presence of correlation is motivated by the scope of utilizing the dependence structure of the data towards further improving some multiple testing methods while maintaining control of some error rate. The dependence structure of the data is incorporated using pairwise weights. In this dissertation we propose a weighted version of the pairwise FDR (Sarkar, 2008) using pairwise weights and a method controlling the weighted pairwise- FDR. We give a discussion on the application of such weighted procedure and suggest some weighting schemes that generates pairwise weights.
Temple University--Theses

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Chan, Chee-cheong. "Compositional data analysis of voting patterns." [Hong Kong : University of Hong Kong], 1993. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13787160.

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Yevstihnyeyev, Roman. "Estimation of Asset Volatility and Correlation Over Market Microstructure Noise in High-Frequency Data." Thesis, Harvard University, 2015. http://nrs.harvard.edu/urn-3:HUL.InstRepos:14398547.

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Accurate measurement of asset return volatility and correlation is an important problem in financial econometrics. The presence of market microstructure noise in high-frequency data complicates such estimations. This study extends a prior application of a model-based volatility estimator with autocorrelated market microstructure noise to estimation of correlation. The model is applied to a high-frequency dataset including a stock and an index, and the results are compared to some existing models. This study supports previous findings that including an autocorrelation factor produces an estimator potentially less vulnerable to market microstructure noise, and finds that the same is true about the extended correlation estimator that is introduced here.

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Mukhopadhyay, Amit Kumar. "Statistics for motion of microparticles in a plasma." Diss., University of Iowa, 2014. https://ir.uiowa.edu/etd/1369.

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I report experimental and numerical studies of microparticle motion in a dusty plasma. These microparticles are negatively charged and are levitated in a plasma consisting of electrons, ions and neutral gas atoms. The microparticles repel each other, and are confined by the electric fields in the plasma. The neutral gas damps the microparticle motion, and also exerts random forces on them. I investigate and characterize microparticle motion. In order to do this, I study velocity distributions of microparticles and correlations of their motion. To perform such a study, I develop new experimental and analysis techniques. My thesis consists of four separate projects. In the first project, the battle between deterministic and random motion of microparticles is investigated. Two particle velocity distributions and correlations have previously studied only in theory. I performed an experiment with a very simple one dimensional (1D) system of two microparticles in a plasma. My study of velocity correlations involves just two microparticles which is the simplest system that allows interactions. A study of such a simple system provides insight into the motions of the microparticles. It allowed for the experimental measurement of two-particle distributions and correlations. For such a system, it is shown that the motion of the microparticles is dominated by deterministic or oscillatory effects. In the second project, two experiments with just two microparticles are performed to isolate the effects of ion wakes. The two experiments differ in the alignment of the two microparticles: they are aligned either perpendicular or parallel to the ion flow. To have different alignments, the sheath is shaped differently in the two experiments. I demonstrate that microparticle motion is more correlated when they are aligned along the ion flow, rather than perpendicular to the ion flow. In the third project, I develop a model with some key assumptions to compare with the experiments in the first two projects. My model includes all significant forces: gravity, electrical forces due to curved sheath and interparticle interaction, and gas forces. The model does not agree with both the experiments. In the last project, I study the non-Gaussian statistics by analyzing data for microparticle motion from an experiment performed under microgranity conditions. Microparticle motion is studied in a very thin region of microparticles in a three dimensional dust cloud. The microparticle velocity distributions exhibit non-Gaussian characteristics.

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dePillis-Lindheim, Lydia. "Disease Correlation Model: Application to Cataract Incidence in the Presence of Diabetes." Scholarship @ Claremont, 2013. http://scholarship.claremont.edu/scripps_theses/294.

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Diabetes is a major risk factor for the development of cataract [3,14,20,22]. In this thesis, we create a model that allows us to understand the incidence of one disease in the context of another; in particular, cataract in the presence of diabetes. The World Health Organization's Vision 2020 blindness-prevention initiative administers surgeries to remove cataracts, the leading cause of blindness worldwide [24]. One of the geographic areas most impacted by cataract-related blindness is Sub-Saharan Africa. In order to plan the number of surgeries to administer, the World Health Organization uses data on cataract prevalence. However, an estimation of the incidence of cataract is more useful than prevalence data for the purpose of resource planning. In 2012, Dray and Williams developed a method for estimating incidence based on prevalence data [5]. Incidence estimates can be further refined by considering associated risk factors such as diabetes. We therefore extend the Dray and Williams model to include diabetes prevalence when calculating cataract incidence estimates. We explore two possible approaches to our model construction, one a detailed extension, and the other, a simplification of that extension. We provide a discussion comparing the two approaches.

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Underhill, Les, and Dave Bradfield. "INTROSTAT (Statistics textbook)." Thesis, University of Cape Town, 2013. https://vula.uct.ac.za/access/content/group/23066897-bf3d-4a8d-9637-049c04424e24/IntroStat-%20Dr%20Underhill/.

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IntroStat was designed to meet the needs of students, primarily those in business, commerce and management, for a course in applied statistics. IntroSTAT is designed as a lecture-book. One of the aims is to maximize the time spent in explaining concepts and doing examples. The book is commonly used as part of first year courses into Statistics.

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Dissertations / Theses on the topic 'Correlation (Statistics)'

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