Relevant bibliographies by topics / Statistical Theory

Academic literature on the topic 'Statistical Theory'

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Published: 4 June 2021
Last updated: 29 January 2023

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Journal articles on the topic "Statistical Theory"

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Scheaffer, Richard L., and Bernard W. Lindgren. "Statistical Theory." Journal of the American Statistical Association 89, no. 426 (June 1994): 711. http://dx.doi.org/10.2307/2290878.

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Lindgren, B. W. "Statistical Theory." Biometrics 51, no. 1 (March 1995): 387. http://dx.doi.org/10.2307/2533367.

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Lubinsky, David J. "Integrating statistical theory with statistical databases." Annals of Mathematics and Artificial Intelligence 2, no. 1-4 (March 1990): 245–59. http://dx.doi.org/10.1007/bf01531010.

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Anroch, Jaromir, Johan Pfanzagl, and R. Hamboker. "Parametric Statistical Theory." Journal of the American Statistical Association 91, no. 433 (March 1996): 438. http://dx.doi.org/10.2307/2291434.

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Sackrowitz, Harold. "Statistical Decision Theory." Journal of the American Statistical Association 98, no. 462 (June 2003): 492. http://dx.doi.org/10.1198/jasa.2003.s274.

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Parisi, Giorgio, and Ramamurti Shankar. "Statistical Field Theory." Physics Today 41, no. 12 (December 1988): 110. http://dx.doi.org/10.1063/1.2811677.

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Wu, Yuhai. "Statistical Learning Theory." Technometrics 41, no. 4 (November 1999): 377–78. http://dx.doi.org/10.1080/00401706.1999.10485951.

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Parisi, Giorgio, and Jonathan Machta. "Statistical Field Theory." American Journal of Physics 57, no. 3 (March 1989): 286–87. http://dx.doi.org/10.1119/1.16061.

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Leemis, Lawrence. "Statistical Reliability Theory." Journal of Quality Technology 22, no. 1 (January 1990): 84–85. http://dx.doi.org/10.1080/00224065.1990.11979217.

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Bishop, R. F. "Statistical field theory." Contemporary Physics 30, no. 2 (March 1989): 137–40. http://dx.doi.org/10.1080/00107518908225513.

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Dissertations / Theses on the topic "Statistical Theory"

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Liang, Annie. "Economic Theory and Statistical Learning." Thesis, Harvard University, 2016. http://nrs.harvard.edu/urn-3:HUL.InstRepos:33493561.

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This dissertation presents three independent essays in microeconomic theory. Chapter 1 suggests an alternative to the common prior assumption, in which agents form beliefs by learning from data, possibly interpreting the data in different ways. In the limit as agents observe increasing quantities of data, the model returns strict solutions of a limiting complete information game, but predictions may diverge substantially for small quantities of data. Chapter 2 (with Jon Kleinberg and Sendhil Mullainathan) proposes use of machine learning algorithms to construct benchmarks for “achievable" predictive accuracy. The paper illustrates this approach for the problem of predicting human-generated random sequences. We find that leading models explain approximately 10-15% of predictable variation in the problem. Chapter 3 considers the problem of how to interpret inconsistent choice data, when the observed departures from the standard model (perfect maximization of a single preference) may emerge either from context-dependencies in preference or from stochastic choice error. I show that if preferences are “simple" in the sense that they consist only of a small number of context-dependencies, then the analyst can use a proposed optimization problem to recover the true number of underlying context-dependent preferences.
Economics
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Lu, Adonis. "Statistical Theory Through Differential Geometry." Scholarship @ Claremont, 2019. https://scholarship.claremont.edu/cmc_theses/2181.

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This thesis will take a look at the roots of modern-day information geometry and some applications into statistical modeling. In order to truly grasp this field, we will first provide a basic and relevant introduction to differential geometry. This includes the basic concepts of manifolds as well as key properties and theorems. We will then explore exponential families with applications of probability distributions. Finally, we select a few time series models and derive the underlying geometries of their manifolds.
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Leroux, Brian Gilbert. "Likelihood ratios in asymptotic statistical theory." Thesis, University of British Columbia, 1985. http://hdl.handle.net/2429/24843.

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This thesis deals with two topics in asymptotic statistics. A concept of asymptotic optimality for sequential tests of statistical hypotheses is introduced. Sequential Probability Ratio Tests are shown to have asymptotic optimality properties corresponding to their usual optimality properties. Secondly, the asymptotic power of Pearson's chi-square test for goodness of fit is derived in a new way. The main tool for evaluating asymptotic performance of tests is the likelihood ratio of two hypotheses. In situations examined here the likelihood ratio based on a sample of size ⁿ has a limiting distribution as ⁿ → ∞ and the limit is also a likelihood ratio. To calculate limiting values of various performance criteria of statistical tests the calculations can be made using the limiting likelihood ratio.
Science, Faculty of
Statistics, Department of
Graduate
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Rasmussen, H. O. "The statistical theory of stationery turbulence." Thesis, University of Cambridge, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.363346.

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Thomas, Kuryan. "A statistical theory of the epilepsies." Diss., Virginia Polytechnic Institute and State University, 1988. http://hdl.handle.net/10919/87673.

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A new physical and mathematical model for the epilepsies is proposed, based on the theory of bond percolation on finite lattices. Within this model, the onset of seizures in the brain is identified with the appearance of spanning clusters of neurons engaged in the spurious and uncontrollable electrical activity characteristic of seizures. It is proposed that the fraction of excitatory to inhibitory synapses can be identified with a bond probability, and that the bond probability is a randomly varying quantity displaying Gaussian statistics. The consequences of the proposed model to the treatment of the epilepsies is explored. The nature of the data on the epilepsies which can be acquired in a clinical setting is described. It is shown that such data can be analyzed to provide preliminary support for the bond percolation hypothesis, and to quantify the efficacy of anti-epileptic drugs in a treatment program. The results of a battery of statistical tests on seizure distributions are discussed. The physical theory of the electroencephalogram (EEG) is described, and extant models of the electrical activity measured by the EEG are discussed, with an emphasis on their physical behavior. A proposal is made to explain the difference between the power spectra of electrical activity measured with cranial probes and with the EEG. Statistical tests on the characteristic EEG manifestations of epileptic activity are conducted, and their results described. Computer simulations of a correlated bond percolating system are constructed. It is shown that the statistical properties of the results of such a simulation are strongly suggestive of the statistical properties of clinical data. The study finds no contradictions between the predictions of the bond percolation model and the observed properties of the available data. Suggestions are made for further research and for techniques based on the proposed model which may be used for tuning the effects of anti-epileptic drugs.
Ph. D.
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Lee, Yun-Soo. "On some aspects of distribution theory and statistical inference involving order statistics." Virtual Press, 1991. http://liblink.bsu.edu/uhtbin/catkey/834141.

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Statistical methods based on nonparametric and distribution-free procedures require the use of order statistics. Order statistics are also used in many parametric estimation and testing problems. With the introduction of modern high speed computers, order statistics have gained more importance in recent years in statistical inference - the main reason being that ranking a large number of observations manually was difficult and time consuming in the past, which is no longer the case at present because of the availability of high speed computers. Also, applications of order statistics require in many cases the use of numerical tables and computer is needed to construct these tables.In this thesis, some basic concepts and results involving order statistics are provided. Typically, application of the Theory of Permanents in the distribution of order statistics are discussed. Further, the correlation coefficient between the smallest observation (Y1) and the largest observation (Y,,) of a random sample of size n from two gamma populations, where (n-1) observations of the sample are from one population and the remaining observation is from the other population, is presented.
Department of Mathematical Sciences
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Grigo, Alexander. "Billiards and statistical mechanics." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/29610.

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Thesis (Ph.D)--Mathematics, Georgia Institute of Technology, 2009.
Committee Chair: Bunimovich, Leonid; Committee Member: Bonetto, Federico; Committee Member: Chow, Shui-Nee; Committee Member: Cvitanovic, Predrag; Committee Member: Weiss, Howard. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Jeng, Tian-Tzer. "Some contributions to asymptotic theory on hypothesis testing when the model is misspecified /." The Ohio State University, 1987. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487332636473942.

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Weston, Robert Andrew. "Lattice field theory and statistical-mechanical models." Thesis, University of Cambridge, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.315971.

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Jiang, Xiao. "Contributions to statistical distribution theory with applications." Thesis, University of Manchester, 2018. https://www.research.manchester.ac.uk/portal/en/theses/contributions-to-statistical-distribution-theory-with-applications(fa612f53-1950-48c2-9cdf-135b2d145587).html.

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The whole thesis contains 10 chapters. Chapter 1 is the introductory chapter of my thesis and the main contributions are presented in Chapter 2 through to Chapter 9. Chapter 10 is the conclusion chapter. These chapters are motivated by applications to new and existing problems in finance, healthcare, sports, and telecommunications. In recent years, there has been a surge in applications of generalized hyperbolic distributions in finance. Chapter 2 provides a review of generalized hyperbolic and related distributions, including related programming packages. A real data application is presented which compares some of the distributions reviewed. Chapter 3 and Chapter 4 derive conditions for stochastic, hazard rate, likelihood ratio, reversed hazard rate, increasing convex and mean residual life orderings of Pareto distributed variables and Weibull distributed variables, respectively. A real data application of the conditions is presented in each chapter. Motivated by Lee and Cha [The American Statistician 69 (2015) 221-230], Chapter 5 introduces seven new families of discrete bivariate distributions. We reanalyze the football data in Lee and Cha (2015) and show that some of the newly proposed distributions provide better fits than the two families proposed by Lee and Cha (2015). Chapter 6 derives the distribution of amplitude, its moments and the distribution of phase for thirty-four flexible bivariate distributions. The results in part extend those given in Coluccia [IEEE Communications Letters, 17, 2013, 2364-2367]. Motivated by Schoenecker and Luginbuhl [IEEE Signal Processing Letters, 23, 2016, 644-647], Chapter 7 studies the characteristic function of products of two independent random variables. One follows the standard normal distribution and the other follows one of forty other continuous distributions. In this chapter, we give explicit expressions for the characteristic function of products, and some of the results are verified by simulations. Cossette, Marceau, and Perreault [Insurance: Mathematics and Economics, 64, 2015, 214-224] derived formulas for aggregation and capital allocation based on risks following two bivariate exponential distributions. Chapter 8 derives formulas for aggregation and capital allocation for thirty-three commonly known families of bivariate distributions. This collection of formulas could be a useful reference for financial risk management. Chapter 9 derives expressions for the kth moment of the dependent random sum using copulas. It also extends Mao and Zhao[IMA Journal of Management Mathematics, 25, 2014, 421-433]’s results to the case where the components of the sum are not identically distributed. The practical usefulness of the results in terms of computational time and computational accuracy is demonstrated by simulation.
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Books on the topic "Statistical Theory"

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Lindgren, B. W. Statistical theory. 4th ed. New York, NY: Chapman & Hall, 1993.

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Jean-Michel, Drouffe, ed. Statistical field theory. Cambridge: CUP, 1992.

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Jean-Michel, Drouffe, ed. Statistical field theory. Cambridge [England]: Cambridge University Press, 1989.

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Itzykson, Claude. Statistical field theory. Cambridge: Cambridge University Press, 1989.

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Simon, French. Statistical decision theory. London: Arnold, 2000.

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Parisi, Giorgio. Statistical field theory. Reading, Mass: Perseus Books, 1998.

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Pfanzagl, J. Parametric statistical theory. Berlin: W. de Gruyter, 1994.

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Vapnik, Vladimir Naumovich. Statistical learning theory. New York: Wiley, 1998.

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Longford, Nicholas T. Statistical Decision Theory. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40433-7.

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Statistical field theory. Redwood City, Calif: Addison-Wesley Pub. Co., 1988.

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Book chapters on the topic "Statistical Theory"

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Farebrother, Richard William. "Statistical Theory." In L1-Norm and L∞-Norm Estimation, 31–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36300-9_5.

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Burnham, Kenneth P., and David R. Anderson. "Statistical Theory." In Model Selection and Inference, 230–314. New York, NY: Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4757-2917-7_6.

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Buckland, S. T., D. R. Anderson, K. P. Burnham, and J. L. Laake. "Statistical theory." In Distance Sampling, 52–103. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-1572-8_3.

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Buckland, S. T., D. R. Anderson, K. P. Burnham, and J. L. Laake. "Statistical theory." In Distance Sampling, 52–103. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-1574-2_3.

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Schumacker, Randall, and Sara Tomek. "Statistical Theory." In Understanding Statistics Using R, 43–53. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-6227-9_3.

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Luscombe, James H. "Ensemble theory." In Statistical Mechanics, 83–124. First edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2021. http://dx.doi.org/10.1201/9781003139669-4.

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Luscombe, James H. "Probability theory." In Statistical Mechanics, 57–82. First edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2021. http://dx.doi.org/10.1201/9781003139669-3.

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Berger, James O. "Statistical Decision Theory." In Game Theory, 217–24. London: Palgrave Macmillan UK, 1989. http://dx.doi.org/10.1007/978-1-349-20181-5_26.

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Bongaarts, Peter. "Quantum Statistical Physics." In Quantum Theory, 157–69. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09561-5_11.

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Nagasawa, Masao. "Micro Statistical Theory." In Stochastic Processes in Quantum Physics, 437–60. Basel: Birkhäuser Basel, 2000. http://dx.doi.org/10.1007/978-3-0348-8383-2_13.

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Conference papers on the topic "Statistical Theory"

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Wu, F. Y. "Knot theory and statistical mechanics." In Computer-aided statistical physics. AIP, 1992. http://dx.doi.org/10.1063/1.41949.

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Gibbs, Alison L., and Alex Stringer. "The Fundamental Role of Computation in Teaching Statistical Theory." In IASE 2021 Satellite Conference: Statistics Education in the Era of Data Science. International Association for Statistical Education, 2022. http://dx.doi.org/10.52041/iase.rmcxl.

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What skills, knowledge and habits of mind does a statistician require in order to contribute effectively as an inhabitant of the data science ecosystem? We describe a new course in statistical theory that was developed as part of our consideration of this question. The course is a core requirement in a new curriculum for undergraduate students enrolled in statistics programs of study. Problem solving and critical thinking are developed through both mathematical and computational thinking and all ideas are motivated through questions to be answered from large, open and messy data. Central to the development of the course is the tenet that the use of computation is as fundamental to statistical thinking as the use of mathematics. We describe the course, including its connection to the learning outcomes of our new statistics program of study, and the multiple ways we use and integrate computation.
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Khrennikov, Andrei, Guillaume Adenier, Andrei Yu Khrennikov, Pekka Lahti, Vladimir I. Man'ko, and Theo M. Nieuwenhuizen. "Prequantum Classical Statistical Field Theory—PCSFT." In Quantum Theory. AIP, 2007. http://dx.doi.org/10.1063/1.2827293.

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Helland, Inge S. "Quantum theory as a statistical theory under symmetry." In FOUNDATIONS OF PROBABILITY AND PHYSICS - 3. AIP, 2005. http://dx.doi.org/10.1063/1.1874567.

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Bazhanov, V. V., and C. J. Burden. "Statistical Mechanics and Field Theory." In Seventh Physics Summer School. WORLD SCIENTIFIC, 1995. http://dx.doi.org/10.1142/9789814532280.

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DeLoach, Richard, and Norbert M. Ulbrich. "A Statistical Theory of Bidirectionality." In AIAA Ground Testing Conference. Reston, Virginia: American Institute of Aeronautics and Astronautics, 2013. http://dx.doi.org/10.2514/6.2013-2995.

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Hsu, Hung-Wei, and I.-Hsiang Wang. "On Binary Statistical Classification from Mismatched Empirically Observed Statistics." In 2020 IEEE International Symposium on Information Theory (ISIT). IEEE, 2020. http://dx.doi.org/10.1109/isit44484.2020.9174520.

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Debris-Alazard, Thomas, and Jean-Pierre Tillich. "Statistical decoding." In 2017 IEEE International Symposium on Information Theory (ISIT). IEEE, 2017. http://dx.doi.org/10.1109/isit.2017.8006839.

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Cortese, John A. "Designing classifier architectures using information theory." In 2016 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2016. http://dx.doi.org/10.1109/ssp.2016.7551812.

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Tvorogov, Stanislav D., and Olga B. Rodimova. "Statistical approximation in line wing theory." In Omsk - DL tentative, edited by Leonid N. Sinitsa. SPIE, 1992. http://dx.doi.org/10.1117/12.131159.

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Reports on the topic "Statistical Theory"

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Basu, Asit P. Statistical Theory and Reliability. Fort Belvoir, VA: Defense Technical Information Center, September 1994. http://dx.doi.org/10.21236/ada288519.

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Basu, Asit P. Statistical Theory and Reliability. Fort Belvoir, VA: Defense Technical Information Center, September 1994. http://dx.doi.org/10.21236/ada295494.

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Basu, Asit P. Statistical Theory of Reliability. Fort Belvoir, VA: Defense Technical Information Center, May 1989. http://dx.doi.org/10.21236/ada215320.

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Moody, John. Statistical Learning Theory and Algorithms. Fort Belvoir, VA: Defense Technical Information Center, February 1993. http://dx.doi.org/10.21236/ada270209.

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Batchelder, William H. Statistical Inference for Cultural Consensus Theory. Fort Belvoir, VA: Defense Technical Information Center, February 2014. http://dx.doi.org/10.21236/ada605989.

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Tetenov, Aleksey. An economic theory of statistical testing. The IFS, September 2016. http://dx.doi.org/10.1920/wp.cem.2016.5016.

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Anderson, Richard G., Barry Jones, and Travis Nesmith. Monetary Aggregation Theory and Statistical Index Numbers. Federal Reserve Bank of St. Louis, 1996. http://dx.doi.org/10.20955/wp.1996.007.

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Kashiwa, B. Statistical theory of turbulent incompressible multimaterial flow. Office of Scientific and Technical Information (OSTI), October 1987. http://dx.doi.org/10.2172/6009875.

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Batchelder, William H. Statistical Development and Application of Cultural Consensus Theory. Fort Belvoir, VA: Defense Technical Information Center, March 2012. http://dx.doi.org/10.21236/ada578264.

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Walston, S. The Idiot's Guide to the Statistical Theory of Fission Chains. Office of Scientific and Technical Information (OSTI), March 2009. http://dx.doi.org/10.2172/966899.

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