Relevant bibliographies by topics / Applied Statistics

Academic literature on the topic 'Applied Statistics'

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Published: 4 June 2021
Last updated: 9 March 2023

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Journal articles on the topic "Applied Statistics"

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Orlov, A. I. "STATISTICAL SIMULATIONS METHOD IN APPLIED STATISTICS." Industrial laboratory. Diagnostics of materials 85, no. 5 (June 5, 2019): 67–79. http://dx.doi.org/10.26896/1028-6861-2019-85-5-67-79.

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The new paradigm of mathematical research methods is based on the effective application of information and communication technologies both in calculating the characteristics of the methods of data analysis and in simulation modeling. Pseudo-random number generators underlie many modern data analysis technologies. To solve specific applied problems, researchers permanently develop the new methods for processing statistical data, i.e., measurement results (observations, tests, analyzes, experiments) and expert estimations. The properties of each newly proposed method must be studied. The intellectual tools are limit theorems and method of statistical simulations (Monte-Carlo method). In 2016, our journal opened a discussion on the current state and prospects for the development of statistical modeling, i.e., the theory and practice of applicating the method of the statistical simulations (Monte-Carlo method), and various variants of the simulation. The previous discussion about the properties of such generators was conducted in our journal in 1985 - 1993. This article is devoted to application of the statistical simulations method to the study of the properties of statistical criteria for testing the homogeneity of two independent samples. We consider: the Kramer - Welch criterion, which coincides with Student's criterion when sample sizes are equal; the criteria of Lord, Wilcoxon (Mann - Whitney), Wolfowitz, Van der Waerden, Smirnov, со 2 (Lehmann - Rosenblatt). It is necessary to set the distribution functions of the elements of two samples. We use the normal and Weibull - Gnedenko distributions. It is shown advisable to use the Lehmann - Rosenblatt со 2 test when testing the hypothesis of coincidence of the distribution functions of two samples. If there is a reason to assume that the distributions differ mainly in the shift, then the Wilcoxon and Van der Waerden criteria can be used. However, even in this case, the со 2 test may be more powerful. In the general case, apart from the Lehmann - Rosenblatt criterion, the use of the Smirnov criterion is permissible, taking into account the difference between the real level of significance and the nominal one. The frequency of the discrepancies of statistical findings based on different criteria is studied.
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Martynov, G. V. "Probabilistic-statistical programs from ?applied statistics?" Journal of Soviet Mathematics 50, no. 3 (June 1990): 1643–84. http://dx.doi.org/10.1007/bf01096290.

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Berenson, M. L., D. M. Levine, and D. Rindskopf. "Applied Statistics." Biometrics 44, no. 4 (December 1988): 1209. http://dx.doi.org/10.2307/2531751.

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Fildes, Robert. "Applied Statistics." International Journal of Forecasting 10, no. 4 (December 1994): 650. http://dx.doi.org/10.1016/0169-2070(94)90040-x.

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Wozniak, Patricia J., and Wayne W. Daniel. "Applied Nonparametric Statistics." Technometrics 33, no. 3 (August 1991): 364. http://dx.doi.org/10.2307/1268795.

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Kemp, A. W., P. Griffiths, and I. D. Hill. "Applied Statistics Algorithms." Biometrics 41, no. 4 (December 1985): 1100. http://dx.doi.org/10.2307/2530987.

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Richter, Donald, and Fadil H. Zuwaylif. "Applied Business Statistics." Journal of Business & Economic Statistics 5, no. 1 (January 1987): 162. http://dx.doi.org/10.2307/1391231.

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Streitberg, B., and W. W. Daniel. "Applied Nonparametric Statistics." Biometrics 47, no. 4 (December 1991): 1634. http://dx.doi.org/10.2307/2532422.

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Meeker, William Q. "Applied Statistics Algorithms." Technometrics 28, no. 3 (August 1986): 278–79. http://dx.doi.org/10.1080/00401706.1986.10488139.

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Janky, Denis G. "Applied Engineering Statistics." Technometrics 36, no. 2 (May 1994): 221–22. http://dx.doi.org/10.1080/00401706.1994.10485776.

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Dissertations / Theses on the topic "Applied Statistics"

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Binter, Roman. "Applied probabilistic forecasting." Thesis, London School of Economics and Political Science (University of London), 2012. http://etheses.lse.ac.uk/559/.

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In any actual forecast, the future evolution of the system is uncertain and the forecasting model is mathematically imperfect. Both, ontic uncertainties in the future (due to true stochasticity) and epistemic uncertainty of the model (reflecting structural imperfections) complicate the construction and evaluation of probabilistic forecast. In almost all nonlinear forecast models, the evolution of uncertainty in time is not tractable analytically and Monte Carlo approaches (”ensemble forecasting”) are widely used. This thesis advances our understanding of the construction of forecast densities from ensembles, the evolution of the resulting probability forecasts and methods of establishing skill (benchmarks). A novel method of partially correcting the model error is introduced and shown to outperform a competitive approach. The properties of Kernel dressing, a method of transforming ensembles into probability density functions, are investigated and the convergence of the approach is illustrated. A connection between forecasting and Information theory is examined by demonstrating that Kernel dressing via minimization of Ignorance implicitly leads to minimization of Kulback-Leibler divergence. The Ignorance score is critically examined in the context of other Information theory measures. The method of Dynamic Climatology is introduced as a new approach to establishing skill (benchmarking). Dynamic Climatology is a new, relatively simple, nearest neighbor based model shown to be of value in benchmarking of global circulation models of the ENSEMBLES project. ENSEMBLES is a project funded by the European Union bringing together all major European weather forecasting institutions in order to develop and test state-of-the-art seasonal weather forecasting models. Via benchmarking the seasonal forecasts of the ENSEMBLES models we demonstrate that Dynamic Climatology can help us better understand the value and forecasting performance of large scale circulation models. Lastly, a new approach to correcting (improving) imperfect model is presented, an idea inspired by [63]. The main idea is based on a two-stage procedure where a second stage ‘corrective’ model iteratively corrects systematic parts of forecasting errors produced by a first stage ‘core’ model. The corrector is of an iterative nature so that at a given time t the core model forecast is corrected and then used as an input into the next iteration of the core model to generate a time t + 1 forecast. Using two nonlinear systems we demonstrate that the iterative corrector is superior to alternative approaches based on direct (non-iterative) forecasts. While the choice of the corrector model class is flexible, we use radial basis functions. Radial basis functions are frequently used in statistical learning and/or surface approximations and involve a number of computational aspects which we discuss in some detail.
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Zhang, Bo. "Machine Learning on Statistical Manifold." Scholarship @ Claremont, 2017. http://scholarship.claremont.edu/hmc_theses/110.

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This senior thesis project explores and generalizes some fundamental machine learning algorithms from the Euclidean space to the statistical manifold, an abstract space in which each point is a probability distribution. In this thesis, we adapt the optimal separating hyperplane, the k-means clustering method, and the hierarchical clustering method for classifying and clustering probability distributions. In these modifications, we use the statistical distances as a measure of the dissimilarity between objects. We describe a situation where the clustering of probability distributions is needed and useful. We present many interesting and promising empirical clustering results, which demonstrate the statistical-distance-based clustering algorithms often outperform the same algorithms with the Euclidean distance in many complex scenarios. In particular, we apply our statistical-distance-based hierarchical and k-means clustering algorithms to the univariate normal distributions with k = 2 and k = 3 clusters, the bivariate normal distributions with diagonal covariance matrix and k = 3 clusters, and the discrete Poisson distributions with k = 3 clusters. Finally, we prove the k-means clustering algorithm applied on the discrete distributions with the Hellinger distance converges not only to the partial optimal solution but also to the local minimum.
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Bynum, Lucius. "Modeling Subset Behavior: Prescriptive Analytics for Professional Basketball Data." Scholarship @ Claremont, 2018. https://scholarship.claremont.edu/hmc_theses/117.

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Sports analytics problems have become increasingly prominent in the past decade. Modern image processing capabilities allow coaching staff to easily capture detailed game-time statistics on their players, opponents, team configurations, and plays. The challenge is to turn that data into meaningful insights for team managers and coaches. This project uses descriptive and predictive techniques on publicly available NBA basketball data to identify powerful combinations of players and predict how they will perform against other teams.
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Dodson, Huey D. "Applied statistics experience & certification in quality assurance /." Click here to view, 2010. http://digitalcommons.calpoly.edu/statsp/3/.

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Thesis (B.S.)--California Polytechnic State University, 2010.
Project advisor: Heather Smith. Title from PDF title page; viewed on Apr. 20, 2010. Includes bibliographical references. Also available on microfiche.
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Lochner, Michelle Aileen Anne. "New applications of statistics in astronomy and cosmology." Doctoral thesis, University of Cape Town, 2014. http://hdl.handle.net/11427/12864.

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Over the last few decades, astronomy and cosmology have become data-driven fields. The parallel increase in computational power has naturally lead to the adoption of more sophisticated statistical techniques for data analysis in these fields, and in particular, Bayesian methods. As the next generation of instruments comes online, this trend should be continued since previously ignored effects must be considered rigorously in order to avoid biases and incorrect scientific conclusions being drawn from the ever-improving data. In the context of supernova cosmology, an example of this is the challenge from contamination as supernova datasets will become too large to spectroscopically confirm the types of all objects. The technique known as BEAMS (Bayesian Estimation Applied to Multiple Species) handles this contamination with a fully Bayesian mixture model approach, which allows unbiased estimates of the cosmological parameters. Here, we extend the original BEAMS formalism to deal with correlated systematics in supernovae data, which we test extensively on thousands of simulated datasets using numerical marginalization and Markov Chain Monte Carlo (MCMC) sampling over the unknown type of the supernova, showing that it recovers unbiased cosmological parameters with good coverage. We then apply Bayesian statistics to the field of radio interferometry. This is particularly relevant in light of the SKA telescope, where the data will be of such high quantity and quality that current techniques will not be adequate to fully exploit it. We show that the current approach to deconvolution of radio interferometric data is susceptible to biases induced by ignored and unknown instrumental effects such as pointing errors, which in general are correlated with the science parameters. We develop an alternative approach - Bayesian Inference for Radio Observations (BIRO) - which is able to determine the joint posterior for all scientific and instrumental parameters. We test BIRO on several simulated datasets and show that it is superior to the standard CLEAN and source extraction algorithms. BIRO fits all parameters simultaneously while providing unbiased estimates - and errors - for the noise, beam width, pointing errors and the fluxes and shapes of the sources.
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Tiani, John P. "Using applied statistics to study a pharmaceutical manufacturing process." Worcester, Mass. : Worcester Polytechnic Institute, 2004. http://www.wpi.edu/Pubs/ETD/Available/etd-0430104-125344/.

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Fitzgerald, Damon. "Household Preferences for Financing Hurricane Risk Mitigation: A Survey Based Empirical Analysis." FIU Digital Commons, 2014. http://digitalcommons.fiu.edu/etd/1725.

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After a series of major storms over the last 20 years, the state of financing for U.S. natural disaster insurance has undergone substantial disruptions causing many federal and state backed programs against residential property damage to become severally underfunded. In order to regain actuarial soundness, policy makers have proposed a shift to a system that reflects risk-based pricing for property insurance. We examine survey responses from 1394 single-family homeowners in the state of Florida for support of several natural disaster mitigation policy reforms. Utilizing a partial proportional odds model we test for effects of location, risk perception, socio-economic and housing characteristics on support for policy reforms. Our findings suggest residents across the state, not just risk-prone homeowners, support the current subsidized model. We also examine several other policy questions from the survey to verify our initial results. Finally, the implications of our findings are discussed to provide inputs to policymakers.
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Liu, Xiang. "A Multi-Indexed Logistic Model for Time Series." Digital Commons @ East Tennessee State University, 2016. https://dc.etsu.edu/etd/3140.

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In this thesis, we explore a multi-indexed logistic regression (MILR) model, with particular emphasis given to its application to time series. MILR includes simple logistic regression (SLR) as a special case, and the hope is that it will in some instances also produce significantly better results. To motivate the development of MILR, we consider its application to the analysis of both simulated sine wave data and stock data. We looked at well-studied SLR and its application in the analysis of time series data. Using a more sophisticated representation of sequential data, we then detail the implementation of MILR. We compare their performance using forecast accuracy and an area under the curve score via simulated sine waves with various intensities of Gaussian noise and Standard & Poors 500 historical data. Overall, that MILR outperforms SLR is validated on both realistic and simulated data. Finally, some possible future directions of research are discussed.
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Brännström, Anton. "A Comparison of Three Methods of Estimation Applied to Contaminated Circular Data." Thesis, Umeå universitet, Statistik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-149426.

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This study compares the performance of the Maximum Likelihood estimator (MLE), estimators based on spacings called Generalized Maximum Spacing estimators (GSEs), and the One Step Minimum Hellinger Distance estimator (OSMHD), on data originating from a circular distribution.  The purpose of the study is to investigate the different estimators’ performance on directional data. More specifically, we compare the estimators’ ability to estimate parameters of the von Mises distribution, which is determined by a location parameter and a scale parameter. For this study, we only look at the scenario in which one of the parameters is unknown. The main part of the study is concerned with estimating the parameters under the condition, in which the data contain outliers, but a small part is also dedicated to estimation at the true model.  When estimating the location parameter under contaminated conditions, the results indicate that some versions of the GSEs tend to outperform the other estimators. It should be noted that these seemingly more robust estimators appear comparatively less optimal at the true model, but this is a tradeoff that must be made on a case by case basis. Under the same contaminated conditions, all included estimators appear to have seemingly greater difficulties estimating the scale parameter. However, for this case, some of the GSEs are able to handle the contamination a bit better than the rest. In addition, there might exist other versions of GSEs, not included in this study, which perform better.
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Brody-Moore, Peter. "Bayesian Hierarchical Meta-Analysis of Asymptomatic Ebola Seroprevalence." Scholarship @ Claremont, 2019. https://scholarship.claremont.edu/cmc_theses/2228.

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The continued study of asymptomatic Ebolavirus infection is necessary to develop a more complete understanding of Ebola transmission dynamics. This paper conducts a meta-analysis of eight studies that measure seroprevalence (the number of subjects that test positive for anti-Ebolavirus antibodies in their blood) in subjects with household exposure or known case-contact with Ebola, but that have shown no symptoms. In our two random effects Bayesian hierarchical models, we find estimated seroprevalences of 8.76% and 9.72%, significantly higher than the 3.3% found by a previous meta-analysis of these eight studies. We also produce a variation of this meta-analysis where we exclude two of the eight studies. In this model, we find an estimated seroprevalence of 4.4%, much lower than our first two Bayesian hierarchical models. We believe a random effects model more accurately reflects the heterogeneity between studies and thus asymptomatic Ebola is more seroprevalent than previously believed among subjects with household exposure or known case-contact. However, a strong conclusion cannot be reached on the seriousness of asymptomatic Ebola without an international testing standard and more data collection using this adopted standard.
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Books on the topic "Applied Statistics"

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Snell, E. J. Applied Statistics. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-011-6946-2.

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Rasch, Dieter, Rob Verdooren, and Jürgen Pilz. Applied Statistics. Chichester, UK: John Wiley & Sons, Ltd, 2019. http://dx.doi.org/10.1002/9781119551584.

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Neter, John. Applied statistics. 3rd ed. Boston: Allyn and Bacon, 1988.

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Neter, John. Applied statistics. 4th ed. Englewood Cliffs, N.J: Prentice Hall, 1993.

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William, Wasserman, and Whitmore G. A, eds. Applied statistics. 3rd ed. Boston: Allyn and Bacon, 1987.

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Neter, John. Applied statistics. 4th ed. Boston: Allyn and Bacon, 1993.

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Weimer, Richard C. Applied elementary statistics. Monterey, Calif: Brooks/Cole Pub. Co., 1987.

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Cowles, Mary Kathryn. Applied Bayesian Statistics. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-5696-4.

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Ley, Christophe, and Thomas Verdebout, eds. Applied Directional Statistics. Boca Raton : CRC Press, 2018.: Chapman and Hall/CRC, 2018. http://dx.doi.org/10.1201/9781315228570.

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Applied business statistics. Kenwyn: Juta, 1993.

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Book chapters on the topic "Applied Statistics"

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Harpale, Varsha K., and Vinayak K. Bairagi. "Applied Statistics." In Research Methodology, 161–206. Boca Raton : CRC Press, Taylor & Francis Group, 2019.: Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9781351013277-5.

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Starzak, Michael E. "Applied Boltzmann Statistics." In Energy and Entropy, 165–79. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-77823-5_11.

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Rhinehart, R. Russell, and Robert M. Bethea. "Descriptive Statistics." In Applied Engineering Statistics, 73–88. 2nd ed. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003222330-5.

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Girardin, Valérie, and Nikolaos Limnios. "Introduction to Statistics." In Applied Probability, 201–44. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97963-8_5.

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Snell, E. J. "Introduction." In Applied Statistics, 3–4. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-011-6946-2_1.

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Snell, E. J. "Cost of construction of nuclear power plants." In Applied Statistics, 38–49. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-011-6946-2_10.

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Snell, E. J. "Effect of process and purity index on fault occurrence." In Applied Statistics, 50–55. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-011-6946-2_11.

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Snell, E. J. "Growth of bones from chick embryos." In Applied Statistics, 56–60. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-011-6946-2_12.

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Snell, E. J. "Factorial experiment on cycles to failure of worsted yarn." In Applied Statistics, 61–66. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-011-6946-2_13.

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Snell, E. J. "Factorial experiment on diets for chickens." In Applied Statistics, 67–71. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-011-6946-2_14.

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Conference papers on the topic "Applied Statistics"

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Tez, Mujgan, and Kadri Ulas Akay. "Preface to Applied Statistics." In THIRD INTERNATIONAL CONFERENCE OF MATHEMATICAL SCIENCES (ICMS 2019). AIP Publishing, 2019. http://dx.doi.org/10.1063/1.5136218.

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"Preface: 2nd International Conference on Applied Statistics." In STATISTICS AND ITS APPLICATIONS: Proceedings of the 2nd International Conference on Applied Statistics (ICAS II), 2016. Author(s), 2017. http://dx.doi.org/10.1063/1.4979415.

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"Committees: 2nd International Conference on Applied Statistics." In STATISTICS AND ITS APPLICATIONS: Proceedings of the 2nd International Conference on Applied Statistics (ICAS II), 2016. Author(s), 2017. http://dx.doi.org/10.1063/1.4979416.

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Vijayaraj, V., A. M. Cheriyadat, Phil Sallee, Brian Colder, R. R. Vatsavai, E. A. Bright, and B. L. Bhaduri. "Overhead image statistics." In 2008 37th IEEE Applied Imagery Pattern Recognition Workshop. IEEE, 2008. http://dx.doi.org/10.1109/aipr.2008.4906471.

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Harrabi, R., M. Sayadi, and F. Fnaiech. "Higher order statistics applied to image segmentation." In IECON 2009 - 35th Annual Conference of IEEE Industrial Electronics (IECON). IEEE, 2009. http://dx.doi.org/10.1109/iecon.2009.5415191.

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"FRONT MATTER." 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_fmatter.

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BICKIS, MIKELIS G. "THE ASYMPTOTIC DISTRIBUTION OF SPACINGS OF ORDER STATISTICS." 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_0004.

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BERLINET, A., and E. BRUNEL. "KULLBACK-LEIBLER OPTIMIZATION OF DENSITY ESTIMATES." 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_0003.

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BELZIL, CHRISTIAN, and XUELIN ZHANG. "UNEMPLOYMENT, SEARCH AND THE GENDER WAGE GAP: A STRUCTURAL MODEL." 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_0002.

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ARNAB, RAGHUNATH, and SARJINDER SINGH. "ON THE ESTIMATION OF SIZE AND MEAN VALUE OF A STIGMATIZED CHARACTERISTIC OF A HIDDEN GANG IN A FINITE POPULATION." 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_0001.

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Reports on the topic "Applied Statistics"

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Steele, J. M. Probability and Statistics Applied to the Theory of Algorithms. Fort Belvoir, VA: Defense Technical Information Center, April 1995. http://dx.doi.org/10.21236/ada295805.

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Stein, David, Alan Stocker, and Scott Deaven. The Fusion of Quadratic Detection Statistics Applied to Hyperspectral Imagery. Fort Belvoir, VA: Defense Technical Information Center, January 2001. http://dx.doi.org/10.21236/ada394681.

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Pebay, Philippe Pierre, and Janine Camille Bennett. Formulas for Fast Computation of Divergence Statistics Applied to Quantitative Performance Analysis. Office of Scientific and Technical Information (OSTI), October 2015. http://dx.doi.org/10.2172/1504858.

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Bodt, Barry A. Proceedings of the Fifth Annual U.S. Army Conference on Applied Statistics, 19-21 October 1999. Fort Belvoir, VA: Defense Technical Information Center, July 2001. http://dx.doi.org/10.21236/ada394816.

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Bodt, Barry A. Proceedings of the Fourth Annual U.S. Army Conference on Applied Statistics, 21-23 October 1998. Fort Belvoir, VA: Defense Technical Information Center, November 1999. http://dx.doi.org/10.21236/ada371791.

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Hofer, Martin, Tomas Sako, Arturo Martinez Jr., Mildred Addawe, Joseph Bulan, Ron Lester Durante, and Marymell Martillan. Applying Artificial Intelligence on Satellite Imagery to Compile Granular Poverty Statistics. Asian Development Bank, December 2020. http://dx.doi.org/10.22617/wps200432-2.

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This study outlines a computational framework to enhance the spatial granularity of government-published poverty estimates, citing data from the Philippines and Thailand. Computer vision techniques were applied on publicly available medium resolution satellite imagery, household surveys, and census data from the two countries. The results suggest that even using publicly accessible satellite imagery, predictions generally aligned with the distributional structure of government-published poverty estimates after calibration. The study further examines the robustness of the resulting estimates to user-specified algorithmic parameters and model specifications.
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Nuttall, Albert H. Joint Probability Density Function of Selected Order Statistics and the Sum of the Remainder as Applied to Arbitrary Independent Random Variables. Fort Belvoir, VA: Defense Technical Information Center, November 2003. http://dx.doi.org/10.21236/ada419339.

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Mirel, Lisa, Cindy Zhang, Christine Cox, Ye Yeats, Félix Suad El Burai, and Golden Cordell. Comparative analysis of the National Health and Nutrition Examination Survey public-use and restricted-use linked mortality files. Centers for Disease Control and Prevention (U.S.), May 2021. http://dx.doi.org/10.15620/cdc:104744.

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"Objectives—Linking national survey data with administrative data sources enables researchers to conduct analyses that would not be possible with each data source alone. Recently, the Data Linkage Program at the National Center for Health Statistics (NCHS) released updated Linked Mortality Files, including the National Health and Nutrition Examination Survey data linked to the National Death Index mortality files. Two versions of the files were released: restricted-use files available through NCHS and Federal Statistical Research Data Centers and public-use files. To reduce the reidentification risk, statistical disclosure limitation methods were applied to the public-use files before they were released. This included limiting the amount of mortality information available and perturbing cause of death and follow-up time for select records. Methods—To assess the comparability of the restricted-use and public-use files, relative hazard ratios for all-cause and cause-specific mortality using Cox proportional hazards models were estimated and compared. Results—The comparative analysis found that the two data files yield similar descriptive and model results. Suggested citation: Mirel LB, Zhang C, Cox CS, Ye Y, El Burai Félix S, Golden C. Comparative analysis of the National Health and Nutrition Examination Survey public-use and restricted-use linked mortality files. National Health Statistics Reports; no 155. Hyattsville, MD: National Center for Health Statistics. 2021. DOI: https://doi.org/10.15620/cdc:104744. CS323656 nhsr155-508.pdf"
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9

Lo, Gane Samb. How to use the functional empirical process for deriving asymptotic laws for functions of the sample. Arxiv, July 2016. http://dx.doi.org/10.16929/hs/imhotep.2016.x.001.

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The functional empirical process is a very powerful tool for deriving asymptotic laws for almost any kind of statistics whenever we know how to express them into functions of the sample. Since this method seems to be applied more and more in the very recent future, this paper is intended to provide a complete but short description and justification of the method and to illustrate it with a non-trivial example using bivariate data. It may also serve for citation without repeating the arguments
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10

Garton, Timothy. Data enrichment and enhanced accessibility of waterborne commerce numerical data : spatially depicting the National Waterway Network. Engineer Research and Development Center (U.S.), December 2020. http://dx.doi.org/10.21079/11681/39223.

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This report provides methodologies and processes of data enrichment and enhanced accessibility of Waterborne Commerce and Statistics Center (WCSC) maintained databases. These databases house tabular and statistical data that reports on The U.S. Army Corps of Engineers (USACE) Civil Works Division National Waterway Network (NWN), which geospatially represents approximately 1,000 harbors and 25,000 miles of channels and waterways. WCSC is a division of The Institute for Water Resources (IWR). They have been tasked with the international collection, maintenance, and archival of all records involving commercial movements and commerce that occur on federal waterways. The current records structure is a large, tabular dataset and limited to the systems and processes put in place prior to the computing standards and capabilities available today. Methods have been tested and utilized to bring the tabular datasets into an optimized, modern geospatial network and expanded upon to create a higher resolution than previously maintained by the WCSC. This report will expand upon the applied methodologies to optimize data queries and the overall enhancement of the data system to allow for linkages to various other sources of information for commerce data enhancement for decision support assistance.
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