Relevant bibliographies by topics / Correlation coefficient

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Correlation coefficient'

Author: Grafiati
Published: 4 June 2021
Last updated: 8 September 2023

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Journal articles on the topic "Correlation coefficient"

1

Zheng, Qi, and James H. Matis. "Correlation Coefficient Revisited." American Statistician 48, no. 3 (August 1994): 240. http://dx.doi.org/10.2307/2684726.

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Sedgwick, P. "Intraclass correlation coefficient." BMJ 346, mar22 1 (March 22, 2013): f1816. http://dx.doi.org/10.1136/bmj.f1816.

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Sedgwick, P. "Pearson's correlation coefficient." BMJ 345, jul04 1 (July 4, 2012): e4483-e4483. http://dx.doi.org/10.1136/bmj.e4483.

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Zheng, Qi, and James H. Matis. "Correlation Coefficient Revisited." American Statistician 48, no. 3 (August 1994): 240–41. http://dx.doi.org/10.1080/00031305.1994.10476066.

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M. Tratz, Christine, Patton L. Fast, and Donald G. Truhlar. "Improved coefficients for the scaling all correlation and multi-coefficient correlation methods." PhysChemComm 2, no. 14 (1999): 70. http://dx.doi.org/10.1039/a908207g.

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Shieh, Gwowen. "Improved procedures and computer programs for equivalence assessment of correlation coefficients." PLOS ONE 16, no. 5 (May 28, 2021): e0252323. http://dx.doi.org/10.1371/journal.pone.0252323.

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The correlation coefficient is the most commonly used measure for summarizing the magnitude and direction of linear relationship between two response variables. Considerable literature has been devoted to the inference procedures for significance tests and confidence intervals of correlations. However, the essential problem of evaluating correlation equivalence has not been adequately examined. For the purpose of expanding the usefulness of correlational techniques, this article focuses on the Pearson product-moment correlation coefficient and the Fisher’s z transformation for developing equivalence procedures of correlation coefficients. Equivalence tests are proposed to assess whether a correlation coefficient is within a designated reference range for declaring equivalence decisions. The important aspects of Type I error rate, power calculation, and sample size determination are also considered. Special emphasis is given to clarify the nature and deficiency of the two one-sided tests for detecting a lack of association. The findings demonstrate the inappropriateness of existing methods for equivalence appraisal and validate the suggested techniques as reliable and primary tools in correlation analysis.
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Bradley, Christopher. "The Absolute Correlation Coefficient." Mathematical Gazette 69, no. 447 (March 1985): 12. http://dx.doi.org/10.2307/3616441.

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Novak, S. Y. "On Gebelein's correlation coefficient." Statistics & Probability Letters 69, no. 3 (September 2004): 299–303. http://dx.doi.org/10.1016/j.spl.2004.06.026.

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MIMOTO, Tomoaki, Hiroyuki YOKOYAMA, Toru NAKAMURA, Takamasa ISOHARA, Masayuki HASHIMOTO, Ryosuke KOJIMA, Aki HASEGAWA, and Yasushi OKUNO. "Privacy-Preserving Correlation Coefficient." IEICE Transactions on Information and Systems E106.D, no. 5 (May 1, 2023): 868–76. http://dx.doi.org/10.1587/transinf.2022dap0014.

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LYU, JIANHUA, CHENG GUAN, XIANWEI LI, and MING CHEN. "EFFECTS OF STAND DENSITY ON TURPENTINE TERPENE COMPONENTS AND RESIN DUCT MORPHOLOGICAL STRUCTURE OF PINUS MASSONIANA." WOOD RESEARCH 66(4) 2021 66, no. 4 (September 9, 2021): 643–56. http://dx.doi.org/10.37763/wr.1336-4561/66.4.643656.

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The influence of stand density on the resin duct morphological structure and terpene components of Pinus massonianawere studied. The resin duct morphological characteristics and the relative content of the terpene components were investigated by microscopyand gas chromatography-mass spectroscopy, respectively. The experimental results revealed that there was a specific correlation between thestand density andresin duct area, resin duct diameter, and the relative contents of main terpene components in the turpentine extracts. Additionally, the relative contents of β-pinene and (+)-camphene were positively correlated with stand density, with correlation coefficients of 0.8208and 0.5539, respectively.In contrast, the relative contents of(+)-longifolene and (+)-longicyclene were negatively correlated with stand density, with correlation coefficients of -0.5750and -0.7726, respectively, andα-pinene, β-caryophyllene, and (+)-α-longipinene had no correlation with stand density. The relative content of (+)-α-pinene was negatively correlated with the relative contents of both (+)-longifolene and (+)-longicyclene,with correlation coefficients of-0.8770 and -0.8914, respectively. There were positive correlations between the relative contents of (+)-longifolene and (+)-longicyclenewith correlation coefficient of0.9718, (+)-longifolene and (+)-α-longipinenewith correlation coefficient of0.8399,β-caryophyllene and (+)-α-longipinenewith correlation coefficient of0.9360, and (+)-longicyclene and (+)-α-longipinenewith correlation coefficient of0.8626.
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Dissertations / Theses on the topic "Correlation coefficient"

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Jung, Aekyung. "Interval Estimation for the Correlation Coefficient." Digital Archive @ GSU, 2011. http://digitalarchive.gsu.edu/math_theses/109.

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The correlation coefficient (CC) is a standard measure of the linear association between two random variables. The CC plays a significant role in many quantitative researches. In a bivariate normal distribution, there are many types of interval estimation for CC, such as z-transformation and maximum likelihood estimation based methods. However, when the underlying bivariate distribution is unknown, the construction of confidence intervals for the CC is still not well-developed. In this thesis, we discuss various interval estimation methods for the CC. We propose a generalized confidence interval and three empirical likelihood-based non-parametric intervals for the CC. We also conduct extensive simulation studies to compare the new intervals with existing intervals in terms of coverage probability and interval length. Finally, two real examples are used to demonstrate the application of the proposed methods.
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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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Yu, Jianhui. "On Intraclass Correlation Coefficients." Digital Archive @ GSU, 2009. http://digitalarchive.gsu.edu/math_theses/75.

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This paper uses Maximum likelihood estimation method to estimate the common correlation coefficients for multivariate datasets. We discuss a graphical tool, Q-Q plot, to test equality of the common intraclass correlation coefficients. Kolmogorov-Smirnov test and Cramér-von Mises test are used to check if the intraclass correlation coefficients are the same among populations. Bootstrap and empirical likelihood methods are applied to construct the confidence interval of the common intraclass correlation coefficients.
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Liu, Huayu. "Modified Profile Likelihood Approach for Certain Intraclass Correlation Coefficient." Digital Archive @ GSU, 2011. http://digitalarchive.gsu.edu/math_theses/96.

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In this paper we consider the problem of constructing confidence intervals and lower bounds forthe intraclass correlation coefficient in an interrater reliability study where the raters are randomly selected from a population of raters.The likelihood function of the interrater reliability is derived and simplified, and the profile likelihood based approach is readily available for computing the confidence intervals of the interrater reliability. Unfortunately, the confidence intervals computed by using the profile likelihood function are in general too narrow to have the desired coverage probabilities. From the point view of practice, a conservative approach, if is at least as precise as any existing method, is preferred sinceit gives the correct results with a probability higher than claimed. Under this rationale, we propose the so-called modified likelihood approach in this paper. Simulation study shows that, the proposed method in general has better performance than currently used methods.
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Cepel, Raina. "The spatial cross-correlation coefficient as an ultrasonic detection statistic." Diss., Columbia, Mo. : University of Missouri-Columbia, 2007. http://hdl.handle.net/10355/5054.

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Thesis (M.S.)--University of Missouri-Columbia, 2007.
The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on April 7, 2008) Includes bibliographical references.
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CHEN, ZHAOREN. "ANALYSIS OF EQUITY MARKETS: A SPEARMAN RANK CORRELATION COEFFICIENT APPROACH." Thesis, The University of Arizona, 2016. http://hdl.handle.net/10150/612636.

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In this honors thesis, I attempted to develop an investment strategy to analyze the U.S. stock market by studying the correlations between nine sectors defined by the Select Sector Standard & Poor’s Depository Receipts (SPDR). These funds are a group of exchange-traded funds (ETFs) which are traded worldwide and can adequately represent the performance of the sectors. Through my method, I hope to identify the sector trends in the future by evaluating the sector ETF’s most recent short-term period data. This analysis will provide an alternate investment method for investors to avoid short-term investment risk as well as explanations of why I think the approach may not be valid.
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Giraudeau, Bruno. "Sensibilite du coefficient de correlation intraclasse a une observation extreme." Paris 7, 1997. http://www.theses.fr/1997PA077112.

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Le coefficient de correlation intraclasse, defini comme la proportion de la variabilite totale due a la variabilite inter-sujets, est classiquement utilise pour estimer la reproductibilite d'un instrument de mesure. L'objet de ce travail est d'etudier l'influence d'observations extremes sur ce coefficient. Une observation (i. E. Un vecteur de p mesures) est extreme soit parce que la moyenne des p mesures s'ecarte de facon anormale de la moyenne globale, soit parce que la variance des p mesures est anormalement elevee. Deux approches permettant le traitement de ces observations ont ete envisagees. D'une part, une fonction d'influence d'une observation a ete analytiquement etablie. Elle dissocie l'influence positive associee a la moyenne des p mesures de l'influence negative associee a la variance de ces mesures. Deux tests en sont derives, ce qui permet d'exclure une observation extreme de l'echantillon. D'autre part, une etude de simulation a ete conduite pour comparer la robustesse de quatre estimateurs : l'estimateur du maximum de vraisemblance, deux estimateurs bootstrap et un estimateur defini a partir de quartiles. Le reechantillonnage ne permet pas de gagner en robustesse, par contre, l'estimateur defini a partir des quartiles est robuste aux observations extremes, mais necessite une distribution normale des donnees. L'utilisation du coefficient de correlation intraclasse est ensuite illustree par deux etudes en rhumatologie. Ainsi, on a estime la reproductibilite de quatre instruments utilises pour l'evaluation radiologique de la gonarthrose, puis on a etudie la reproductibilite et la sensibilite au changement de plusieurs methodes d'evaluation de la progression de la gonarthrose. Cette derniere etude clinique a, en outre, conduit a une investigation analytique des relations existant entre la reproductibilite et la sensibilite au changement, ce qui nous a permis de montrer que la qualite metrologique primordiale reste la reproductibilite.
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Leach, Lesley Ann Freeny. "Bias and Precision of the Squared Canonical Correlation Coefficient under Nonnormal Data Conditions." Thesis, University of North Texas, 2006. https://digital.library.unt.edu/ark:/67531/metadc5361/.

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This dissertation: (a) investigated the degree to which the squared canonical correlation coefficient is biased in multivariate nonnormal distributions and (b) identified formulae that adjust the squared canonical correlation coefficient (Rc2) such that it most closely approximates the true population effect under normal and nonnormal data conditions. Five conditions were manipulated in a fully-crossed design to determine the degree of bias associated with Rc2: distribution shape, variable sets, sample size to variable ratios, and within- and between-set correlations. Very few of the condition combinations produced acceptable amounts of bias in Rc2, but those that did were all found with first function results. The sample size to variable ratio (n:v)was determined to have the greatest impact on the bias associated with the Rc2 for the first, second, and third functions. The variable set condition also affected the accuracy of Rc2, but for the second and third functions only. The kurtosis levels of the marginal distributions (b2), and the between- and within-set correlations demonstrated little or no impact on the bias associated with Rc2. Therefore, it is recommended that researchers use n:v ratios of at least 10:1 in canonical analyses, although greater n:v ratios have the potential to produce even less bias. Furthermore,because it was determined that b2 did not impact the accuracy of Rc2, one can be somewhat confident that, with marginal distributions possessing homogenous kurtosis levels ranging anywhere from -1 to 8, Rc2 will likely be as accurate as that resulting from a normal distribution. Because the majority of Rc2 estimates were extremely biased, it is recommended that all Rc2 effects, regardless of which function from which they result, be adjusted using an appropriate adjustment formula. If no rationale exists for the use of another formula, the Rozeboom-2 would likely be a safe choice given that it produced the greatest number of unbiased Rc2 estimates for the greatest number of condition combinations in this study.
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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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Liu, Li-yu Daisy. "Coefficient of intrinsic dependence: a new measure of association." Texas A&M University, 2005. http://hdl.handle.net/1969.1/2397.

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To detect dependence among variables is an essential task in many scientific investigations. In this study we propose a new measure of association, the coefficient of intrinsic dependence (CID), which takes value in [0,1] and faithfully reflects the full range of dependence for two random variables. The CID is free of distributional and functional assumptions. It can be easily implemented and extended to multivariate situations. Traditionally, the correlation coefficient is the preferred measure of association. However, it's effectiveness is considerably compromised when the random variables are not normally distributed. Besides, the interpretation of the correlation coefficient is difficult when the data are categorical. By contrast, the CID is free of these problems. In our simulation studies, we find that the ability of the CID in differentiating different levels of dependence remains robust across different data types (categorical or continuous) and model features (linear or curvilinear). Also, the CID is particularly effective when the dependence is strong, making it a powerful tool for variable selection. As an illustration, the CID is applied to variable selection in two aspects: classification and prediction. The analysis of actual data from a study of breast cancer gene expression is included. For the classification problem, we identify a pair of genes that best classify a patient's prognosis signature, and for the prediction problem, we identify a pair of genes that best relates to the expression of a specific gene.
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Books on the topic "Correlation coefficient"

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Keen, K. J. Asymptotic variance of the interclass correlation coefficient. [Toronto, Ont.]: University of Toronto, Department of Statistics, 1989.

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Srivastava, M. S. Point and interval estimation of the interclass correlation coefficient. Toronto: University of Toronto, Dept. of Statistics, 1987.

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Jackson, Douglas E. Tool for studying the effects of range restriction in correlation coefficient estimation. Brooks Air Force Base, Tex: Air Force Systems Command, Air Force Human Resources Laboratory, 1990.

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Sloan, Luke, and Rob Angell. Spearman’s Rank-Order Correlation Coefficient and the General Social Survey (2012): Income and Political Influence. 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2015. http://dx.doi.org/10.4135/9781473937987.

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Al-Ahmadi, Adel Bin Musaed Sulaiman. Electrohydrodynamic (EHD) enhancement of condensation heat transfer - development of correlation for heat transfer coefficient for tubular systems. Birmingham: University of Birmingham, 2003.

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Sloan, Luke, and Rob Angell. Spearman’s Rank-Order Correlation Coefficient and the General Social Survey (2012): Highest Level of Education and Income. 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2015. http://dx.doi.org/10.4135/9781473937857.

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Sloan, Luke, and Rob Angell. Pearson's Correlation Coefficient and the UK Living Cost and Food Survey (2010): The Relationship Between Income and Expenditure. 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2015. http://dx.doi.org/10.4135/9781473937994.

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Thomas, Hoben. Distributions of Correlation Coefficients. New York, NY: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4684-6366-8.

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Distributions of correlation coefficients. New York: Springer-Verlag, 1989.

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Bonilha, M. W. Measurements of correlation coefficients of vibration on a car body shell. Southampton, England: University of Southampton, Institute of Sound and Vibration Research, 1993.

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Book chapters on the topic "Correlation coefficient"

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Hilbert, Sven. "Correlation Coefficient." In Encyclopedia of Personality and Individual Differences, 915–19. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-24612-3_1292.

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Rossman, Allan J., and Beth L. Chance. "Correlation Coefficient." In Workshop Statistics, 127–44. New York, NY: Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4757-2926-9_8.

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Nahler, Gerhard. "correlation coefficient." In Dictionary of Pharmaceutical Medicine, 40–41. Vienna: Springer Vienna, 2009. http://dx.doi.org/10.1007/978-3-211-89836-9_304.

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Johnston, Ron. "Correlation Coefficient." In Encyclopedia of Quality of Life and Well-Being Research, 1304–5. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-0753-5_590.

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Hu, Fuyan. "Correlation Coefficient." In Encyclopedia of Systems Biology, 505–6. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_438.

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Mukhopadhyay, Nitis. "Correlation Coefficient." In International Encyclopedia of Statistical Science, 315–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_194.

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Hilbert, Sven. "Correlation Coefficient." In Encyclopedia of Personality and Individual Differences, 1–4. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-28099-8_1292-1.

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Gooch, Jan W. "Correlation Coefficient." In Encyclopedic Dictionary of Polymers, 977. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-6247-8_15202.

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Pan, Guocheng. "Correlation Coefficient." In Encyclopedia of Mathematical Geosciences, 201–8. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-85040-1_69.

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Narayana, D., Sharad Ranjan, and Nupur Tyagi. "Correlation Coefficient." In Basic Computational Techniques for Data Analysis, 130–53. 2nd ed. London: Routledge India, 2023. http://dx.doi.org/10.4324/9781003398127-7.

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Conference papers on the topic "Correlation coefficient"

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Ahad, Nor Aishah, Suhaida Abdullah, Nur Amira Zakaria, Sharipah Soaad Syed Yahaya, and Norhayati Yusof. "Median based robust correlation coefficient." In PROCEEDINGS OF THE 13TH IMT-GT INTERNATIONAL CONFERENCE ON MATHEMATICS, STATISTICS AND THEIR APPLICATIONS (ICMSA2017). Author(s), 2017. http://dx.doi.org/10.1063/1.5012221.

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Mishachev, Nikolai, Anatoly Shmyrin, and Andrey Kanyugin. "Multiple Correlation Coefficient Versus Tolerances." In 2023 3rd International Conference on Technology Enhanced Learning in Higher Education (TELE). IEEE, 2023. http://dx.doi.org/10.1109/tele58910.2023.10184346.

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Chen, Chong, and Puzhen Gao. "Heat Transfer Correlation for Boiling Flows in Vertical Rectangular Narrow Channel." In 2013 21st International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/icone21-16616.

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In view of the practical significance of a correlation of heat transfer coefficient in the aspect of such applications as engineering and predictive, some efforts towards correlating flow boiling heat transfer correlation for vertical rectangular narrow channels have been made in this paper. Based on analyses of existing general correlations for flow boiling heat transfer, it is found that general correlations are not suitable to predict heat transfer coefficients in narrow channels. By considering the suppression factor S and two-phase pool boiling heat transfer coefficient hnb, introducing boiling number Bo and two-phase friction multiplier ϕtt2, the Chen correlation has been modified to be used for narrow channels. The flow boiling heat transfer was the function of boiling number Bo and two-phase friction multiplier ϕtt2, the coefficients have a regular change with the increase of boiling number Bo or two-phase friction multiplier ϕtt2. A comparison of the newly developed correlation with the existing data for narrow channels shows a satisfactory agreement. The heat transfer coefficient of the narrow channel was well predicted by the new correlation and the deviation within ±20%.
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Wang, Sen, and Li Zhang. "A Supervised Correlation Coefficient Method: Detection of Different Correlation." In 2020 12th International Conference on Advanced Computational Intelligence (ICACI). IEEE, 2020. http://dx.doi.org/10.1109/icaci49185.2020.9177709.

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Ujera, R. Sudha, V. Ragavi, and Chandrasegar Thirumalai. "Analyzing correlation coefficient using software metrics." In 2017 International Conference on Trends in Electronics and Informatics (ICOEI). IEEE, 2017. http://dx.doi.org/10.1109/icoei.2017.8300894.

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Li, Qi, Roberto Aguilera, and Heber Cinco Ley. "A Correlation for Estimating Biot Coefficient." In SPE Western Regional Meeting. Society of Petroleum Engineers, 2019. http://dx.doi.org/10.2118/195359-ms.

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Du, Xiaodong. "Correlation coefficient of hesitant fuzzy sets." In 2017 32nd Youth Academic Annual Conference of Chinese Association of Automation (YAC). IEEE, 2017. http://dx.doi.org/10.1109/yac.2017.7967582.

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Zakaria, Nur Amira, Suhaida Abdullah, and Nor Aishah Ahad. "Robust correlation coefficient based on Qn estimator." In PROCEEDINGS OF THE 13TH IMT-GT INTERNATIONAL CONFERENCE ON MATHEMATICS, STATISTICS AND THEIR APPLICATIONS (ICMSA2017). Author(s), 2017. http://dx.doi.org/10.1063/1.5012266.

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Gao, Ning, and Douglas Oard. "A Head-Weighted Gap-Sensitive Correlation Coefficient." In SIGIR '15: The 38th International ACM SIGIR conference on research and development in Information Retrieval. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2766462.2767793.

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Seongho Kim, Ming Ouyang, and Xiang Zhang. "Compute spearman correlation coefficient with Matlab/CUDA." In 2012 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT). IEEE, 2012. http://dx.doi.org/10.1109/isspit.2012.6621260.

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Reports on the topic "Correlation coefficient"

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Loucks, Richard B. Use of a Correlation Coefficient for Conditional Averaging. Fort Belvoir, VA: Defense Technical Information Center, April 1997. http://dx.doi.org/10.21236/ada324614.

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Casias, Zachary. High Throughput Coefficient Thermal Expansion Testing Utilizing Digital Image Correlation. Office of Scientific and Technical Information (OSTI), November 2022. http://dx.doi.org/10.2172/1898723.

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Soloviev, V., and V. Solovieva. Quantum econophysics of cryptocurrencies crises. [б. в.], 2018. http://dx.doi.org/10.31812/0564/2464.

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From positions, attained by modern theoretical physics in understanding of the universe bases, the methodological and philosophical analysis of fundamental physical concepts and their formal and informal connections with the real economic measuring is carried out. Procedures for heterogeneous economic time determination, normalized economic coordinates and economic mass are offered, based on the analysis of time series, the concept of economic Plank's constant has been proposed. The theory has been approved on the real economic dynamic's time series, related to the cryptocurrencies market, the achieved results are open for discussion. Then, combined the empirical cross-correlation matrix with the random matrix theory, we mainly examine the statistical properties of cross-correlation coefficient, the evolution of average correlation coefficient, the distribution of eigenvalues and corresponding eigenvectors of the global cryptocurrency market using the daily returns of 15 cryptocurrencies price time series across the world from 2016 to 2018. The result indicated that the largest eigenvalue reflects a collective effect of the whole market, practically coincides with the dynamics of the mean value of the correlation coefficient and very sensitive to the crisis phenomena. It is shown that both the introduced economic mass and the largest eigenvalue of the matrix of correlations can serve as quantum indicator-predictors of crises in the market of cryptocurrencies.
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Jackson, Douglas E., and Malcolm J. Ree. Tool for Studying the Effects of Range Restriction in Correlation Coefficient Estimation. Fort Belvoir, VA: Defense Technical Information Center, July 1990. http://dx.doi.org/10.21236/ada224035.

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Hessler, J. P., and P. J. Ogren. Correlation analysis of optical absorption cross section and rate coefficient measurements in reacting systems. Office of Scientific and Technical Information (OSTI), August 1992. http://dx.doi.org/10.2172/10159230.

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Kedzierski, Mark A., and Donggyu Kang. Horizontal convective boiling of R1234yf, R134a, and R450A within a micro-fin tube :. Gaithersburg, MD: National Institute of Standards and Technology (U.S.), August 2017. http://dx.doi.org/10.6028/nist.tn.1966.

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This report presents local convective boiling heat transfer and Fanning friction factor measurements in a micro-fin tube for R134a and two possible low global warming potential (GWP) refrigerant replacements for R134a: R1234yf and R450A. Test section heating was achieved with water in either counterflow or in parallel flow with the test refrigerant to provide for a range of heat fluxes for each thermodynamic quality. An existing correlation from the literature for single and multi-component mixtures was shown to not satisfactorily predict the convective boiling measurements for flow qualities greater than 40 %. Accordingly, a new correlation was developed specifically for the test fluids of this study so that a fair comparison of the heat transfer performance of the low GWP refrigerants to that of R134a could be made. The new correlation was used to compare the heat transfer coefficient of the three test fluids at the same heat flux, saturated refrigerant temperature, and refrigerant mass flux. The resulting example comparison, for the same operating conditions, showed that the heat transfer coefficient of the multi-component R450A and the single-component R1234yf were, on average, 15 % less and 5 % less, respectively, than that of the single-component R134a. Friction factor measurements were also compared to predictions from an existing correlation. A new correlation for the friction factor was developed to provide a more accurate prediction. The measurements and the new models are important for the evaluation of potential low-GWP refrigerants replacements for R134a.
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CHEN, Danfeng, Jianquan CHEN, Xutong ZHENG, Zhuzhu QIN, Simin HUANG, and Chenju ZHAN. Stigma in colorectal cancer patients with colostomy, China: A systematic review and meta-analysis of current status and associated psychological factors. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, February 2023. http://dx.doi.org/10.37766/inplasy2023.2.0073.

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Review question / Objective: To analyze the current stigma and related factors of colorectal cancer stoma patients in China using Meta-analysis. To analyze the current stigma and related factors of colorectal cancer stoma patients in China using Meta-analysis.: (1) The study design was: an observational study (cohort study, case-control study, cross-sectional study) (2) The study population was post-stoma patients with colorectal cancer in China (3) The study index needed to contain at least one scale related to the stigma that was tested for reliability (4) The outcome index needed to contain the level of stigma (x± s) or at least one psychological variable related to stigma after colorectal cancer stoma and report the correlation coefficient.
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Duvvuri, Sarvani, and Srinivas S. Pulugurtha. Researching Relationships between Truck Travel Time Performance Measures and On-Network and Off-Network Characteristics. Mineta Transportation Institute, July 2021. http://dx.doi.org/10.31979/mti.2021.1946.

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Trucks serve significant amount of freight tonnage and are more susceptible to complex interactions with other vehicles in a traffic stream. While traffic congestion continues to be a significant ‘highway’ problem, delays in truck travel result in loss of revenue to the trucking companies. There is a significant research on the traffic congestion mitigation, but a very few studies focused on data exclusive to trucks. This research is aimed at a regional-level analysis of truck travel time data to identify roads for improving mobility and reducing congestion for truck traffic. The objectives of the research are to compute and evaluate the truck travel time performance measures (by time of the day and day of the week) and use selected truck travel time performance measures to examine their correlation with on-network and off-network characteristics. Truck travel time data for the year 2019 were obtained and processed at the link level for Mecklenburg County, Wake County, and Buncombe County, NC. Various truck travel time performance measures were computed by time of the day and day of the week. Pearson correlation coefficient analysis was performed to select the average travel time (ATT), planning time index (PTI), travel time index (TTI), and buffer time index (BTI) for further analysis. On-network characteristics such as the speed limit, reference speed, annual average daily traffic (AADT), and the number of through lanes were extracted for each link. Similarly, off-network characteristics such as land use and demographic data in the near vicinity of each selected link were captured using 0.25 miles and 0.50 miles as buffer widths. The relationships between the selected truck travel time performance measures and on-network and off-network characteristics were then analyzed using Pearson correlation coefficient analysis. The results indicate that urban areas, high-volume roads, and principal arterial roads are positively correlated with the truck travel time performance measures. Further, the presence of agricultural, light commercial, heavy commercial, light industrial, single-family residential, multi-family residential, office, transportation, and medical land uses increase the truck travel time performance measures (decrease the operational performance). The methodological approach and findings can be used in identifying potential areas to serve as truck priority zones and for planning decentralized delivery locations.
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Tschirhart, V. Keating correlation coefficient results over the Tehery Lake area, Nunavut, NTS 56-B and parts of 55-N, O, P, 56-A, C, F, G and H. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2017. http://dx.doi.org/10.4095/299252.

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Soloviev, Vladimir N., Symon P. Yevtushenko, and Viktor V. Batareyev. Comparative analysis of the cryptocurrency and the stock markets using the Random Matrix Theory. [б. в.], February 2020. http://dx.doi.org/10.31812/123456789/3681.

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This article demonstrates the comparative possibility of constructing indicators of critical and crash phenomena in the volatile market of cryptocurrency and developed stock market. Then, combining the empirical cross-correlation matrix with the Random Matrix Theory, we mainly examine the statistical properties of cross-correlation coefficients, the evolution of the distribution of eigenvalues and corresponding eigenvectors in both markets using the daily returns of price time series. The result has indicated that the largest eigenvalue reflects a collective effect of the whole market, and is very sensitive to the crash phenomena. It has been shown that introduced the largest eigenvalue of the matrix of correlations can act like indicators-predictors of falls in both markets.
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