Relevant bibliographies by topics / Sampling (statistics)

Academic literature on the topic 'Sampling (statistics)'

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Published: 4 June 2021
Last updated: 29 July 2024

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Journal articles on the topic "Sampling (statistics)"

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Low, C. K., and U. Balasooriya. "Order statistics based sampling design for reliability sampling." Journal of Statistical Computation and Simulation 77, no. 8 (August 2007): 709–15. http://dx.doi.org/10.1080/10629360600575888.

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Kohler, Ulrich, Frauke Kreuter, and Elizabeth A. Stuart. "Nonprobability Sampling and Causal Analysis." Annual Review of Statistics and Its Application 6, no. 1 (March 7, 2019): 149–72. http://dx.doi.org/10.1146/annurev-statistics-030718-104951.

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The long-standing approach of using probability samples in social science research has come under pressure through eroding survey response rates, advanced methodology, and easier access to large amounts of data. These factors, along with an increased awareness of the pitfalls of the nonequivalent comparison group design for the estimation of causal effects, have moved the attention of applied researchers away from issues of sampling and toward issues of identification. This article discusses the usability of samples with unknown selection probabilities for various research questions. In doing so, we review assumptions necessary for descriptive and causal inference and discuss research strategies developed to overcome sampling limitations.
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Kristensen, L., P. Kirkegaard, and J. Mann. "Sampling Statistics of Atmospheric Observations." Wind Energy 5, no. 4 (2002): 301–13. http://dx.doi.org/10.1002/we.75.

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Preston, Ian. "Sampling Distributions of Relative Poverty Statistics." Applied Statistics 44, no. 1 (1995): 91. http://dx.doi.org/10.2307/2986197.

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Wolter, Kirk M., P. R. Krishnaiah, and C. R. Rao. "Handbook of Statistics, Volume 6: Sampling." Journal of the American Statistical Association 86, no. 413 (March 1991): 250. http://dx.doi.org/10.2307/2289749.

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Cormack, R. M., P. R. Krishnaiah, and C. R. Rao. "Handbook of Statistics, Vol. 6: Sampling." Biometrics 46, no. 3 (September 1990): 879. http://dx.doi.org/10.2307/2532113.

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Kim, Sung-Min, and Hyun Mee Kim. "Sampling error of observation impact statistics." Tellus A: Dynamic Meteorology and Oceanography 66, no. 1 (November 14, 2014): 25435. http://dx.doi.org/10.3402/tellusa.v66.25435.

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Pedler, P. J. "Understanding sampling distributions in inferential statistics." International Journal of Mathematical Education in Science and Technology 22, no. 1 (January 1991): 69–87. http://dx.doi.org/10.1080/0020739910220112.

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Alf, Cherié, and Sharon Lohr. "Sampling Assumptions in Introductory Statistics Classes." American Statistician 61, no. 1 (February 2007): 71–77. http://dx.doi.org/10.1198/000313007x171098.

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Ziegel, Eric R. "Handbook of Statistics, Volume 6: Sampling." Technometrics 32, no. 4 (November 1990): 460. http://dx.doi.org/10.1080/00401706.1990.10484749.

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Dissertations / Theses on the topic "Sampling (statistics)"

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Pollard, John. "Adaptive distance sampling." Thesis, University of St Andrews, 2002. http://hdl.handle.net/10023/15176.

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We investigate mechanisms to improve efficiency for line and point transect surveys of clustered populations by combining the distance methods with adaptive sampling. In adaptive sampling, survey effort is increased when areas of high animal density are located, thereby increasing the number of observations. We begin by building on existing adaptive sampling techniques, to create both point and line transect adaptive estimators, these are then extended to allow the inclusion of covariates in the detection function estimator. However, the methods are limited, as the total effort required cannot be forecast at the start of a survey, and so a new fixed total effort adaptive approach is developed. A key difference in the new method is that it does not require the calculation of the inclusion probabilities typically used by existing adaptive estimators. The fixed effort method is primarily aimed at line transect sampling, but point transect derivations are also provided. We evaluate the new methodology by computer simulation, and report on surveys of harbour porpoise in the Gulf of Maine, in which the approach was compared with conventional line transect sampling. Line transect simulation results for a clustered population showed up to a 6% improvement in the adaptive density variance estimate over the conventional, whilst when there was no clustering the adaptive estimate was 1% less efficient than the conventional. For the harbour porpoise survey, the adaptive density estimate cvs showed improvements of 8% for individual porpoise density and 14% for school density over the conventional estimates. The primary benefit of the fixed effort method is the potential to improve survey coverage, allowing a survey to complete within a fixed time and effort; an important feature if expensive survey resources are involved, such as an aircraft, crew and observers.
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Svensson, Jens. "On Importance Sampling and Dependence Modeling." Doctoral thesis, KTH, Matematik (Inst.), 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-11272.

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This thesis consists of four papers. In the first paper, Monte Carlo simulation for tail probabilities of heavy-tailed random walks is considered. Importance sampling algorithms are constructed by using mixtures of the original distribution with some other state-dependent distributions. Sufficient conditions under which the relative error of such algorithms is bounded are found, and the bound is calculated. A new mixture algorithm based on scaling of the original distribution is presented and compared to existing algorithms. In the second paper, Monte Carlo simulation of quantiles is treated. It is shown that by using importance sampling algorithms developed for tail probability estimation, efficient quantile estimators can be obtained. A functional limit of the quantile process under the importance sampling measure is found, and the variance of the limit process is calculated for regularly varying distributions. The procedure is also applied to the calculation of expected shortfall. The algorithms are illustrated numerically for a heavy-tailed random walk. In the third paper, large deviation probabilities for a sum of dependent random variables are derived. The dependence stems from a few underlying random variables, so-called factors. Each summand is composed of two parts: an idiosyncratic part and a part given by the factors. Conditions under which both factors and idiosyncratic components contribute to the large deviation behavior are found, and the resulting approximation is evaluated in a simple example. In the fourth paper, the asymptotic eigenvalue distribution of the exponentially weighted moving average covariance estimator is studied. Equations for the asymptotic spectral density and the boundaries of its support are found using the Marchenko-Pastur theorem.
QC 20100811
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Sung, Iyue. "Importance sampling kernel density estimation /." The Ohio State University, 2001. http://rave.ohiolink.edu/etdc/view?acc_num=osu1486398528559777.

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Meister, Kadri. "On Methods for Real Time Sampling and Distributions in Sampling." Doctoral thesis, Umeå : Univ, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-415.

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Ignatieva, Ekaterina. "Adaptive Bayesian sampling with application to 'bubbles'." Connect to e-thesis, 2008. http://theses.gla.ac.uk/356/.

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Thesis (MSc(R)) - University of Glasgow, 2008.
MSc(R). thesis submitted to the Department of Mathematics, Faculty of Information and Mathematical Sciences, University of Glasgow, 2008. Includes bibliographical references.
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Frey, Jesse C. "Inference procedures based on order statistics." Connect to this title online, 2005. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1122565389.

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Thesis (Ph. D.)--Ohio State University, 2005.
Title from first page of PDF file. Document formatted into pages; contains xi, 148 p.; also includes graphics. Includes bibliographical references (p. 146-148). Available online via OhioLINK's ETD Center
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Greenfield, C. C. "Replicated sampling in censuses and surveys." Thesis, [Hong Kong] : University of Hong Kong, 1985. http://sunzi.lib.hku.hk/hkuto/record.jsp?B1232131X.

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Xi, Liqun, and 奚李群. "Estimating population size for capture-recapture/removal models with heterogeneity and auxiliary information." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B29957783.

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譚玉貞 and Yuk-ching Tam. "Some practical issues in estimation based on a ranked set sample." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1999. http://hub.hku.hk/bib/B31221683.

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尹再英 and Choi-ying Wan. "Statistical analysis for capture-recapture experiments in discrete time." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B31225287.

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Books on the topic "Sampling (statistics)"

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Thompson, Steven K. Sampling. New York: Wiley, 1992.

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Guy, Dan M. Audit sampling: An introduction to statistical sampling in auditing. 2nd ed. New York: Wiley, 1986.

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Bansal, Archana. Survey Sampling. Oxford, UK: Alpha Science International Ltd., 2017.

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Pitard, Francis F. Theory of Sampling and Sampling Practice. Boca Raton, Florida, USA: Chapman and Hall/CRC, 2019.

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Mecatti, Fulvia, Pier Luigi Conti, and Maria Giovanna Ranalli, eds. Contributions to Sampling Statistics. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05320-2.

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Corwin, Rebecca B. Statistics: Prediction and sampling. Palo Alto, CA: Dale Seymour Publications, 1990.

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Guy, Dan M. Audit sampling: An introduction. 5th ed. New York, NY: J. Wiley, 2002.

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Guy, Dan M. Audit sampling: An introduction. 3rd ed. New York: Wiley, 1994.

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Dodge, Harold French. Sampling inspection tables: Single and double sampling. 2nd ed. New York: Wiley, 1998.

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Sugden, R. A. Sampling techniques. London: University of London, 1994.

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Book chapters on the topic "Sampling (statistics)"

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Foster, Dean P., Robert A. Stine, and Richard P. Waterman. "Sampling." In Basic Business Statistics, 107–26. New York, NY: Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4612-1696-4_6.

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Foster, Dean P., Robert A. Stine, and Richard P. Waterman. "Sampling." In Basic Business Statistics, 109–28. New York, NY: Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4757-2717-3_6.

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Yadav, Shakti Kumar, Sompal Singh, and Ruchika Gupta. "Sampling Methods." In Biomedical Statistics, 71–83. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9294-9_9.

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Rossman, Allan J., and Beth L. Chance. "Random Sampling." In Workshop Statistics, 199–216. New York, NY: Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4757-2926-9_12.

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Chamberlin, Scott A. "Statistical Sampling." In Statistics for Kids, 97–109. New York: Routledge, 2021. http://dx.doi.org/10.4324/9781003238201-8.

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Hanvey, Chester. "Sampling and Statistics." In Wage and Hour Law, 147–70. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74612-8_8.

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Nguyen, Hung T., and Gerald S. Rogers. "Sampling and Statistics." In Springer Texts in Statistics, 2–6. New York, NY: Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4613-8914-9_2.

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Ball, A. D., and G. D. Buckwell. "Small Sampling." In Statistics A Level, 174–85. London: Macmillan Education UK, 1991. http://dx.doi.org/10.1007/978-1-349-13856-2_11.

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Finkelstein, Michael O., and Bruce Levin. "Sampling Issues." In Statistics for Lawyers, 258–83. New York, NY: Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4612-3328-2_9.

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Finkelstein, Michael O., and Bruce Levin. "Sampling Issues." In Statistics for Lawyers, 271–98. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4419-5985-0_9.

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Conference papers on the topic "Sampling (statistics)"

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RILSTONE, PAUL, and AMAN ULLAH. "THE SAMPLING BIAS OF HECKMAN'S SAMPLE BIAS ESTIMATOR." In Proceedings of Statistics 2001 Canada: The 4th Conference in Applied Statistics. PUBLISHED BY IMPERIAL COLLEGE PRESS AND DISTRIBUTED BY WORLD SCIENTIFIC PUBLISHING CO., 2002. http://dx.doi.org/10.1142/9781860949531_0022.

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Sim, Hoon, Karthikeyan Diraviyam, Akansha Saxena, and David Sept. "Sampling and statistics in biomolecular simulations." In THEORY AND APPLICATIONS IN COMPUTATIONAL CHEMISTRY: THE FIRST DECADE OF THE SECOND MILLENNIUM: International Congress TACC-2012. AIP, 2012. http://dx.doi.org/10.1063/1.4730657.

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Cohen, Edith. "Stream Sampling for Frequency Cap Statistics." In KDD '15: The 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2783258.2783279.

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Matheny, Michael, Raghvendra Singh, Liang Zhang, Kaiqiang Wang, and Jeff M. Phillips. "Scalable spatial scan statistics through sampling." In SIGSPATIAL'16: 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2996913.2996939.

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NIKI, Naoto, and Yoko ONO. "Sampling Moments of Resamples." In 2nd Annual International Conference on Computational Mathematics, Computational Geometry & Statistics. Global Science Technology Forum, 2013. http://dx.doi.org/10.5176/2251-1911_cmcgs13.21.

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Chen, Zehua. "Ranked Set Sampling: A Simple Idea of Great Use." In Proceedings of the International Statistics Workshop. WORLD SCIENTIFIC, 2006. http://dx.doi.org/10.1142/9789812772466_0023.

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Burgess, Arthur E. "On Sampling Statistics In Observer Performance Studies." In 1989 Intl Congress on Optical Science and Engineering, edited by Max A. Viergever. SPIE, 1989. http://dx.doi.org/10.1117/12.961735.

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Szu, Harold, Lidan Miao, Pornchai Chanyagon, and Masud Cader. "Next gen wavelets down-sampling preserving statistics." In Defense and Security Symposium. SPIE, 2007. http://dx.doi.org/10.1117/12.725201.

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Wang, Xin, Richard T. B. Ma, Yinlong Xu, and Zhipeng Li. "Sampling online social networks via heterogeneous statistics." In IEEE INFOCOM 2015 - IEEE Conference on Computer Communications. IEEE, 2015. http://dx.doi.org/10.1109/infocom.2015.7218649.

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Kadane, Joseph B. "Probability sampling in legal cases: Kansas cellphone users." In XI BRAZILIAN MEETING ON BAYESIAN STATISTICS: EBEB 2012. AIP, 2012. http://dx.doi.org/10.1063/1.4759584.

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Reports on the topic "Sampling (statistics)"

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Wurtz, R. E. Closeout report for statistics for environmental sampling. Office of Scientific and Technical Information (OSTI), November 2019. http://dx.doi.org/10.2172/1576904.

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Ruslan, Kadir. Improving Indonesia’s Food Statistics through the Area Sampling Frame Method. Jakarta, Indonesia: Center for Indonesian Policy Studies, 2019. http://dx.doi.org/10.35497/287781.

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Ruslan, Kadir. Improving Indonesia’s Food Statistics through the Area Sampling Frame Method. Jakarta, Indonesia: Center for Indonesian Policy Studies, 2019. http://dx.doi.org/10.35497/346123.

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WIELOPOLSKI, L. EMERGING MODALITIES FOR SOIL CARBON ANALYSIS: SAMPLING STATISTICS AND ECONOMICS WORKSHOP. Office of Scientific and Technical Information (OSTI), April 2006. http://dx.doi.org/10.2172/881571.

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Horrace, William, Peter Schmidt, and Ann Dryden Witte. Sampling Errors and Confidence Intervals for Order Statistics: Implementing the Family Support Act. Cambridge, MA: National Bureau of Economic Research, December 1995. http://dx.doi.org/10.3386/w5387.

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Zhang, Guangyu, Yulei He, Van Parsons, Chris Moriarty, Stephen Blumberg, Benjamin Zablotsky, Aaron Maitland, Matthew Bramlett, and Jonaki Bose. Developing sampling weights for statistical analysis of parent-child pair data from the National Health Interview Survey. National Center for Health Statistics (U.S.), April 2024. http://dx.doi.org/10.15620/cdc:1147101.

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Zhang, Guangyu, Yulei He, Van Parsons, Chris Moriarty, Stephen Blumberg, Benjamin Zablotsky, Aaron Maitland, Matthew Bramlett, and Jonaki Bose. Developing sampling weights for statistical analysis of parent-child pair data from the National Health Interview Survey. Hyattsville, MD: National Center for Health Statistics (U.S.), April 2024. http://dx.doi.org/10.15620/cdc/147884.

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Favorite, Jeffrey. (U) A Tool to Set Up an MCNP6 Input to Use Correlated Sampling with Batch Statistics. Office of Scientific and Technical Information (OSTI), January 2024. http://dx.doi.org/10.2172/2280547.

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Kane, J. S., and M. S. Epstein. Implications of sampling statistics in using slurry sample introduction for atomic spectrometric analysis of geochemical reference samples. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1993. http://dx.doi.org/10.4095/193262.

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Favorite, Jeffrey. (U) Correlated Sampling Using Batch Statistics to Reduce the Uncertainty of Combinations of KSEN Outputs with MCNP6. Office of Scientific and Technical Information (OSTI), December 2023. http://dx.doi.org/10.2172/2246827.

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