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Relevant bibliographies by topics / Random variables

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Academic literature on the topic 'Random variables'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 June 2025

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Journal articles on the topic "Random variables"

1

Vos, Paul W. "Random Variables Aren’t Random." Mathematics 13, no. 5 (February 26, 2025): 775. https://doi.org/10.3390/math13050775.

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This paper examines the foundational concept of random variables in probability theory and statistical inference, demonstrating that their mathematical definition requires no reference to randomization or hypothetical repeated sampling. We show how measure-theoretic probability provides a framework for modeling populations through distributions, leading to three key contributions. First, we establish that random variables, properly understood as measurable functions, can be fully characterized without appealing to infinite hypothetical samples. Second, we demonstrate how this perspective enables statistical inference through logical rather than probabilistic reasoning, extending the reductio ad absurdum argument from deductive to inductive inference. Third, we show how this framework naturally leads to an information-based assessment of statistical procedures, replacing traditional inference metrics that emphasize bias and variance with information-based approaches that describe the families of distributions used in parametric inference better. This reformulation addresses long-standing debates in statistical inference while providing a more coherent theoretical foundation. Our approach offers an alternative to traditional frequentist inference that maintains mathematical rigor while avoiding the philosophical complications inherent in repeated sampling interpretations.

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Jovanovic Dolecek, Gordana. "Teaching Random Variables." U.Porto Journal of Engineering 7, no. 1 (February 19, 2021): 10–15. http://dx.doi.org/10.24840/2183-6493_007.001_0003.

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This paper presents demo program for teaching random variables dedicated to demonstration and visualization of behaviour of the product of m independent uniform random variables. The demo is used as a complementary tool in the teaching Random signals and processes curriculum at the graduate level. The demo is made in MATLAB and utilizes all benefits provided by MATLAB, such as simplicity, and good graphic environment, interactive use, among others. Additionally, this demo is used with other demo programs, also made in MATLAB, in teaching/learning process of random variables. Students were very satisfied with this demo program expressing that helped them understanding better the behaviour of the product of uniform random variables.

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FLETCHER, M. E. "Introducing Random Variables." Teaching Mathematics and its Applications 5, no. 4 (January 1, 1986): 191–92. http://dx.doi.org/10.1093/teamat/5.4.191.

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Assani, I. "distributed random variables." Duke Mathematical Journal 88, no. 2 (June 1997): 217–46. http://dx.doi.org/10.1215/s0012-7094-97-08808-6.

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Mendonça, Sandra, António Alberto Oliveira, Dinis Pestana, and Maria Luísa Rocha. "Count Random Variables." Encyclopedia 4, no. 3 (September 23, 2024): 1367–80. http://dx.doi.org/10.3390/encyclopedia4030089.

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The observation of randomness patterns serves as guidance for the craft of probabilistic modelling. The most used count models—Binomial, Poisson, Negative Binomial—are the discrete Morris’ natural exponential families whose variance is at most quadratic on the mean, and the solutions of Katz–Panjer recurrence relation, aside from being members of the generalised power series and hypergeometric distribution families, and this accounts for their many advantageous characteristics. Some other basic count models are also described, as well as models with less obvious but useful randomness patterns in connection with maximum entropy characterisations, such as Zipf and Good models. Simple tools, such as truncation, thinning, or parameter randomisation, are straightforward ways of constructing other count models.

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Peköz, Erol, and Sheldon M. Ross. "COMPOUND RANDOM VARIABLES." Probability in the Engineering and Informational Sciences 18, no. 4 (October 2004): 473–84. http://dx.doi.org/10.1017/s0269964804184039.

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We give a probabilistic proof of an identity concerning the expectation of an arbitrary function of a compound random variable and then use this identity to obtain recursive formulas for the probability mass function of compound random variables when the compounding distribution is Poisson, binomial, negative binomial random, hypergeometric, logarithmic, or negative hypergeometric. We then show how to use simulation to efficiently estimate both the probability that a positive compound random variable is greater than a specified constant and the expected amount by which it exceeds that constant.

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Nadarajah, Saralees, Emmanuel Afuecheta, and Stephen Chan. "Ordered random variables." OPSEARCH 56, no. 1 (January 30, 2019): 344–66. http://dx.doi.org/10.1007/s12597-019-00355-6.

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Shapiro, Arnold F. "Fuzzy random variables." Insurance: Mathematics and Economics 44, no. 2 (April 2009): 307–14. http://dx.doi.org/10.1016/j.insmatheco.2008.05.008.

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Gil, M. "Fuzzy random variables." Information Sciences 133, no. 1-2 (March 2001): 1–2. http://dx.doi.org/10.1016/s0020-0255(01)00072-x.

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Hathaway, Richard J. "Clustering Random Variables." IETE Journal of Research 44, no. 4-5 (July 1998): 199–205. http://dx.doi.org/10.1080/03772063.1998.11416046.

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Dissertations / Theses on the topic "Random variables"

1

Yan, Xiaosong. "Quantifications of random variables." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1996. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/NQ36218.pdf.

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Wanntorp, Henrik. "Summability Methods and Random Variables." Thesis, Uppsala University, Department of Mathematics, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-122047.

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Spencer, Steven Robert. "Renewal theory for uniform random variables." CSUSB ScholarWorks, 2002. https://scholarworks.lib.csusb.edu/etd-project/2248.

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This project will focus on finding formulas for E[N(t)] using one of the classical problems in the discipline first, and then extending the scope of the problem to include overall times greater than the time t in the original problem. The expected values in these cases will be found using the uniform and exponential distributions of random variables.

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Zarepour, Mahmoud. "Some topics on infinite variance random variables." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ28099.pdf.

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Jairu, Desiderio N. "Distributions of some random volumes of uniform and beta type-1 random variables." Thesis, City University London, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.283156.

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Venigella, Pavan Kumar. "Robust Mechanism synthesis with random and interval variables." Diss., Rolla, Mo. : University of Missouri-Rolla, 2007. http://scholarsmine.mst.edu/thesis/pdf/Venigella_09007dcc8046c1ff.pdf.

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Thesis (M.S.)--University of Missouri--Rolla, 2007.<br>Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed March 27, 2008) Includes bibliographical references (p. 86-89).

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Kharoufeh, Jeffrey P. "Density estimation for functions of correlated random variables." Ohio : Ohio University, 1997. http://www.ohiolink.edu/etd/view.cgi?ohiou1177097417.

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Njoroge, Moses M. "On jacobians connected with matrix variate random variables." Thesis, McGill University, 1988. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=61966.

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Nešlehová, Johana [Verfasser]. "Dependence of Non-Continuous Random Variables / Johana Nešlehová." Aachen : Shaker, 2004. http://d-nb.info/1181604567/34.

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Papathomas, Michail. "Non-parametric Bayesian procedures for binary random variables." Thesis, University of Sheffield, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.369897.

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Books on the topic "Random variables"

1

1946-, Nevzorov Valery B., ed. Ordered random variables. Huntington, N.Y: Nova Science Publishers, 2001.

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Veazie, Peter J. What Makes Variables Random. Boca Raton : CRC Press, 2017.: Chapman and Hall/CRC, 2017. http://dx.doi.org/10.1201/9781315180700.

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Malik, A. K. Random Variables & Stochastic Processes. Jaipur, Rajasthan, India: Neelkanth Publishers Pvt. Ltd., 2013.

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Devroye, Luc. Non-uniform random variate generation. New York: Springer-Verlag, 1986.

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Grami, Ali. Probability, Random Variables, Statistics, and Random Processes. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2019. http://dx.doi.org/10.1002/9781119300847.

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6

Peebles, Peyton Z. Probability, random variables, and random signal principles. 2nd ed. New York: McGraw-Hill, 1987.

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7

Hsu, Hwei P. Schaum's outlines: Probability, random variables & random processes. 2nd ed. New York: McGraw-Hill, 2011.

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Buldygin, V. V. Metric characterization of random variables and random processes. Providence, R.I: American Mathematical Society, 2000.

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Hsu, Hwei P. (Hwei Piao), 1930- Schaum's outline of theory and problems of probability, random variables, and random processes, ed. Schaum's outline's of probability, random variables & random processes. 2nd ed. New York: McGraw-Hill, 2010.

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Hsu, Hwei P. Schaum's outline's of probability, random variables & random processes. 2nd ed. New York: McGraw-Hill, 2010.

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Book chapters on the topic "Random variables"

1

Hausner, Melvin. "Random Variables." In Elementary Probability Theory, 153–205. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-1753-5_5.

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Jacod, Jean, and Philip Protter. "Random Variables." In Universitext, 47–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-55682-1_8.

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Zabarankin, Michael, and Stan Uryasev. "Random Variables." In Statistical Decision Problems, 3–17. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8471-4_1.

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Haigh, John. "Random Variables." In Springer Undergraduate Mathematics Series, 61–91. London: Springer London, 2002. http://dx.doi.org/10.1007/978-1-4471-0169-7_4.

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O’Hagan, Anthony. "Random variables." In Probability, 93–131. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-1211-3_5.

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Cufaro Petroni, Nicola. "Random Variables." In UNITEXT for Physics, 49–98. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48408-8_3.

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Fristedt, Bert, and Lawrence Gray. "Random Variables." In A Modern Approach to Probability Theory, 11–24. Boston, MA: Birkhäuser Boston, 1997. http://dx.doi.org/10.1007/978-1-4899-2837-5_2.

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Löffler, Andreas, and Lutz Kruschwitz. "Random Variables." In Springer Texts in Business and Economics, 59–68. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20103-6_4.

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Gordon, Hugh. "Random Variables." In Discrete Probability, 75–110. New York, NY: Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4612-1966-8_4.

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Schay, Géza. "Random Variables." In Introduction to Probability with Statistical Applications, 105–72. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30620-9_5.

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Conference papers on the topic "Random variables"

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Goubault-Larrecq, Jean, and Daniele Varacca. "Continuous Random Variables." In 2011 26th Annual IEEE Symposium on Logic in Computer Science (LICS 2011). IEEE, 2011. http://dx.doi.org/10.1109/lics.2011.23.

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Vidakovic, Brani. "Wavelet random variables." In Optical Science, Engineering and Instrumentation '97, edited by Akram Aldroubi, Andrew F. Laine, and Michael A. Unser. SPIE, 1997. http://dx.doi.org/10.1117/12.292796.

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Wang, Chao, Ming-Hu Ha, Yi-Jun Fan, and Ji-Qiang Chen. "Intuitionistic fuzzy random variables." In 2011 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 2011. http://dx.doi.org/10.1109/icmlc.2011.6016733.

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SCHOTT, RENÉ, and G. STACEY STAPLES. "CLIFFORD ALGEBRAS, RANDOM GRAPHS, AND QUANTUM RANDOM VARIABLES." In Quantum Stochastics and Information - Statistics, Filtering and Control. WORLD SCIENTIFIC, 2008. http://dx.doi.org/10.1142/9789812832962_0005.

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Semenova, Daria, and Natalia Lukyanova. "Random set decomposition of discrete-continuous random variables." In 2012 IV International Conference "Problems of Cybernetics and Informatics" (PCI). IEEE, 2012. http://dx.doi.org/10.1109/icpci.2012.6486479.

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Weld, Christopher, and Lawrence Leemis. "Modeling mixed type random variables." In 2017 Winter Simulation Conference (WSC). IEEE, 2017. http://dx.doi.org/10.1109/wsc.2017.8247900.

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Friedrich, Tobias, and Ralf Rothenberger. "Sharpness of the Satisfiability Threshold for Non-Uniform Random k-SAT." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/853.

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We study a more general model to generate random instances of Propositional Satisfiability (SAT) with n Boolean variables, m clauses, and exactly k variables per clause. Additionally, our model is given an arbitrary probability distribution (p_1, ..., p_n) on the variable occurrences. Therefore, we call it non-uniform random k-SAT. The number m of randomly drawn clauses at which random formulas go from asymptotically almost surely (a.a.s.) satisfiable to a.a.s. unsatisfiable is called the satisfiability threshold. Such a threshold is called sharp if it approaches a step function as n increases. We identify conditions on the variable probability distribution (p_1, ..., p_n) under which the satisfiability threshold is sharp if its position is already known asymptotically. This result generalizes Friedgut’s sharpness result from uniform to non-uniform random k -SAT and implies sharpness for thresholds of a wide range of random k -SAT models with heterogeneous probability distributions, for example such models where the variable probabilities follow a power-law.

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Huang, Peng, Hong-Zhong Huang, and Hua-Ming Qian. "Structural Reliability Analysis Based on Random Variables and Interval Variables." In Proceedings of the 29th European Safety and Reliability Conference (ESREL). Singapore: Research Publishing Services, 2019. http://dx.doi.org/10.3850/978-981-11-2724-3_0312-cd.

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Gohari, Amin Aminzadeh, and Venkat Anantharam. "Generating dependent random variables over networks." In 2011 IEEE Information Theory Workshop (ITW). IEEE, 2011. http://dx.doi.org/10.1109/itw.2011.6089587.

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Chen, Hailong, and Yan Zhang. "Laplace Transform for Stable Random Variables." In 2015 3rd International Conference on Computer and Computing Science (COMCOMS). IEEE, 2015. http://dx.doi.org/10.1109/comcoms.2015.10.

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Reports on the topic "Random variables"

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Jakeman, John, Fabian Franzelin, Akil Narayan, Michael Eldred, and Dirk Pflueger. Polynomial chaos expansions for dependent random variables. Office of Scientific and Technical Information (OSTI), May 2019. http://dx.doi.org/10.2172/1762354.

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Bacelli, Francois, and Armand M. Makowski. Multi-Dimensional Stochastic Ordering and Associated Random Variables. Fort Belvoir, VA: Defense Technical Information Center, January 1987. http://dx.doi.org/10.21236/ada453456.

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Serfozo, R. F. Compound Poisson Approximations for Sums of Random Variables,. Fort Belvoir, VA: Defense Technical Information Center, May 1985. http://dx.doi.org/10.21236/ada158555.

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Chaganty, Narasinga R. Strong Moderate Deviation Theorems for m-Dependent Random Variables. Fort Belvoir, VA: Defense Technical Information Center, August 1989. http://dx.doi.org/10.21236/ada212618.

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Chan, Wai, Dong H. Park, and Frank Proschan. Peakedness of Weighted Averages of Jointly Distributed Random Variables. Fort Belvoir, VA: Defense Technical Information Center, August 1987. http://dx.doi.org/10.21236/ada185611.

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Boland, Philip J., Frank Proschan, and Y. L. Tong. Some Majorization Inequalities for Functions of Exchangeable Random Variables. Fort Belvoir, VA: Defense Technical Information Center, October 1987. http://dx.doi.org/10.21236/ada188207.

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Butler, Ken, and Michael Stephens. The Distribution of a Sum of Binomial Random Variables. Fort Belvoir, VA: Defense Technical Information Center, April 1993. http://dx.doi.org/10.21236/ada266969.

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Masten, Matthew. Random coefficients on endogenous variables in simultaneous equations models. Institute for Fiscal Studies, January 2014. http://dx.doi.org/10.1920/wp.cem.2013.0114.

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Masten, Matthew. Random coefficients on endogenous variables in simultaneous equations models. Institute for Fiscal Studies, June 2015. http://dx.doi.org/10.1920/wp.cem.2015.2515.

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Chan, Wai, Dong Ho Park, and Frank Proschan. Peakedness of Weighted Averages of Jointly Distributed Random Variables. Fort Belvoir, VA: Defense Technical Information Center, October 1985. http://dx.doi.org/10.21236/ada162876.

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