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Relevant bibliographies by topics / Double sampling for regression

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Academic literature on the topic 'Double sampling for regression'

Author: Grafiati

Published: 4 June 2021

Last updated: 5 February 2022

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Journal articles on the topic "Double sampling for regression"

1

Jiang, Xuejun, Jiancheng Jiang, and Yanling Liu. "Nonparametric regression under double-sampling designs." Journal of Systems Science and Complexity 24, no. 1 (2011): 167–75. http://dx.doi.org/10.1007/s11424-011-8129-x.

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Samawi, Hani M., and Eman M. Tawalbeh. "Regression Estimator Using Double Ranked Set Sampling." Sultan Qaboos University Journal for Science [SQUJS] 7, no. 2 (2002): 311. http://dx.doi.org/10.24200/squjs.vol7iss2pp311-322.

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The performance of a regression estimator based on the double ranked set sample (DRSS) scheme, introduced by Al-Saleh and Al-Kadiri (2000), is investigated when the mean of the auxiliary variable X is unknown. Our primary analysis and simulation indicates that using the DRSS regression estimator for estimating the population mean substantially increases relative efficiency compared to using regression estimator based on simple random sampling (SRS) or ranked set sampling (RSS) (Yu and Lam, 1997) regression estimator. Moreover, the regression estimator using DRSS is also more efficient than the

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Chen, Yi-Hau, and Hung Chen. "A unified approach to regression analysis under double-sampling designs." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 62, no. 3 (2000): 449–60. http://dx.doi.org/10.1111/1467-9868.00243.

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Causeur, David. "Exact Distribution of the Regression Esti Mator in Double Sampling." Statistics 32, no. 4 (1999): 297–315. http://dx.doi.org/10.1080/02331889908802671.

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Mukerjee, Rahul, and Arijit Chaudhuri. "Asymptotic optimality of double sampling plans employing generalized regression estimators." Journal of Statistical Planning and Inference 26, no. 2 (1990): 173–83. http://dx.doi.org/10.1016/0378-3758(90)90125-e.

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Baker, Stuart G., Yohanan Wax, and Blossom H. Patterson. "Regression Analysis of Grouped Survival Data: Informative Censoring and Double Sampling." Biometrics 49, no. 2 (1993): 379. http://dx.doi.org/10.2307/2532551.

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Catchpole, W. R., and E. A. Catchpole. "ESTIMATING BIOMASS IN A VEGETATION MOSAIC USING DOUBLE SAMPLING WITH REGRESSION." Australian Journal of Statistics 33, no. 3 (1991): 279–89. http://dx.doi.org/10.1111/j.1467-842x.1991.tb00434.x.

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Dorfman, Alan H. "A Note on Variance Estimation for the Regression Estimator in Double Sampling." Journal of the American Statistical Association 89, no. 425 (1994): 137–40. http://dx.doi.org/10.1080/01621459.1994.10476454.

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Collins, Brian T. "Guidelines for Using Double Sampling in Avian Population Monitoring." Auk 124, no. 4 (2007): 1373–87. http://dx.doi.org/10.1093/auk/124.4.1373.

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Abstract Double sampling involves combining information from inexpensive rapid counts with intensive complete counts to provide an efficient population estimate. This technique is a valuable approach for calibrating population indices based on incomplete counts and improving the precision of monitoring studies. Data collected through a double-sampling protocol can be analyzed with either a ratio or a regression estimator. The ratio estimator is recommended when the relationship of the actual count to the rapid count is a straight line through origin, which may not be valid when surveying popul

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Samawi, Hani M., Ahmed Y. A. Al-Samarraie, and Obaid M. Al-Saidy. "On Regression Estimators Using Extreme Ranked Set Samples." Sultan Qaboos University Journal for Science [SQUJS] 9 (June 1, 2004): 67. http://dx.doi.org/10.24200/squjs.vol9iss0pp67-86.

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Regression is used to estimate the population mean of the response variable, , in the two cases where the population mean of the concomitant (auxiliary) variable, , is known and where it is unknown. In the latter case, a double sampling method is used to estimate the population mean of the concomitant variable. We invesitagate the performance of the two methods using extreme ranked set sampling (ERSS), as discussed by Samawi et al. (1996). Theoretical and Monte Carlo evaluation results as well as an illustration using actual data are presented. The results show that if the underlying joint dis

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Dissertations / Theses on the topic "Double sampling for regression"

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Tan, Edith Estillore. "Design and regression estimation in double sampling." Diss., Virginia Polytechnic Institute and State University, 1987. http://hdl.handle.net/10919/74777.

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Two methods developed to improve regression estimation in double sampling under the superpopulation model approach are examined. One method proposes the use of an alternative double sample regression estimator. The other method recommends the use of nonrandom, purposive subsampling plans. Both methods aim to reduce the mean squared errors of regression estimators in double sampling. A major criticism against the superpopulation model approach is its strong dependence on the correctness of the assumed model. Thus, two purposive subsampling plans were considered. The first plan designed subsam

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Koziuk, Andzhey. "Re-sampling in instrumental variables regression." Doctoral thesis, Humboldt-Universität zu Berlin, 2020. http://dx.doi.org/10.18452/20869.

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Diese Arbeit behandelt die Instrumentalvariablenregression im Kontext der Stichprobenwiederholung. Es wird ein Rahmen geschaffen, der das Ziel der Inferenz identifiziert. Diese Abhandlung versucht die Instrumentalvariablenregression von einer neuen Perspektive aus zu motivieren. Dabei wird angenommen, dass das Ziel der Schätzung von zwei Faktoren gebildet wird, einer Umgebung und einer zu einem internen Model spezifischen Struktur. Neben diesem Rahmen entwickelt die Arbeit eine Methode der Stichprobenwiederholung, die geeignet für das Testen einer linearen Hypothese bezüglich der Schätzung

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ARAUJO, AURELIA APARECIDA DE. "DOUBLE-SAMPLING CONTROL CHARTS FOR ATTRIBUTES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2005. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=6938@1.

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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>Nesta tese é proposta a incorporação da estratégia de amostragem dupla, já utilizada em inspeção de lotes, ao gráfico de controle de np (número de defeituosos), com o objetivo de aumentar a sua eficiência, ou seja, reduzir o número médio de amostras até a detecção de um descontrole (NMA1), sem aumentar o tamanho médio de amostra (TMA) nem reduzir o número médio de amostras até um alarme falso (NMA0). Alternativamente, este esquema pode ser usado para reduzir o custo de amostragem do gráfico de np, uma vez que para obter o

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Corrow, Allissa. "DOUBLE SAMPLING FOR COARSE WOODY DEBRIS ESTIMATIONS FOLLOWING LINE INTERSECT SAMPLING." The University of Montana, 2010. http://etd.lib.umt.edu/theses/available/etd-06122010-133739/.

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Coarse woody debris (CWD), an essential component of healthy forests, has typically been defined as dead and down, large woody material. Quantification of this resource provides a useful metric for assessing wildlife habitat, fuel loading, and more recently, carbon sequestration. Although many CWD sampling methods exist, accurate estimation is difficult and expensive. Double sampling incorporates auxiliary data that is positively correlated with the attribute of interest as a means of reducing sampling costs and/or increasing estimation precision. The present study investigated double sampling

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Sinko, Arthur Ghysels Eric. "Some applications of mixed data sampling regression models." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2008. http://dc.lib.unc.edu/u?/etd,2643.

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Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 2008.<br>Title from electronic title page (viewed Oct. 5, 2009). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Economics." Discipline: Economics; Department/School: Economics.

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Fiery, Michael Allen. "A form of two-phase sampling utilizing regression analysis." Morgantown, W. Va. : [West Virginia University Libraries], 2005. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=4312.

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Thesis (M.S.)--West Virginia University, 2005.<br>Title from document title page. Document formatted into pages; contains iv, 81 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 32).

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Ertefaie, Ashkan. "Casual inference via propensity score regression and length-biased sampling." Thesis, McGill University, 2011. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=104784.

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Confounder adjustment is the key in the estimation of exposure effect in observational studies. Two well known causal adjustment techniques are the propensity score and the inverse probability of treatment weighting. We have compared the asymptotic properties of these two estimators and showed that the former method results in a more efficient estimator. Since ignoring important confounders result in a biased estimator, it seems beneficial to adjust for all the covariates. This, however, may result in an inflation of the variance of the estimated parameters and induce bias as well. We presen

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Bůžková, Petra. "Marginal regression analysis of longitudinal data with irregular, biased sampling /." Thesis, Connect to this title online; UW restricted, 2004. http://hdl.handle.net/1773/9547.

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Paneru, Khyam Narayan. "Regression Analysis for Zero Inflated Population Under Complex Sampling Designs." Bowling Green State University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1375197852.

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Wang, Yi-Fu 1958. "Evaluation of correlated double sampling used with solid state imagers." Thesis, The University of Arizona, 1989. http://hdl.handle.net/10150/277187.

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Correlated double sampling (CDS) is a widely used signal processing technique for removal of the Nyquist (reset) noise which is associated with charge sensing circuits employed in a solid state imager. In this thesis work, the power spectral density at the output of a correlated double sampling circuit with first-order low-pass filtered white noise at the input is calculated. A circuit constructed with discrete elements is made to simulate the output stage of a charge-coupled device (CCD). A low-pass filtered wide-band noise from a noise generator is added to the reset reference level when the

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Books on the topic "Double sampling for regression"

1

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

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Bansal, Archana. Survey Sampling. Alpha Science International Ltd., 2017.

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Mukhopadhyay, Parimal. Inferential Problems in Survey Sampling. New Age International Publishers, 2015.

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Stewart, Rounds, Clean Water Services (Washington County, Or.), and Geological Survey (U.S.), eds. Use of continuous monitors and autosamplers to predict unmeasured water-quality constituents in tributaries of the Tualatin River, Oregon. U.S. Dept. of the Interior, U.S. Geological Survey, 2010.

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Analyzing environmental data. Wiley, 2004.

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Ouyang, Zhao. Finite population corrections of the Horvitz-Thompson estimator and their application in estimating the variance of regression estimators. U.S. Dept. of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station, 1997.

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Sharma, H. L. Experimental Designs And Survey Sampling: Methods And Applications. Agrotech Publishing Academy, 2010.

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8

Weighted empiricals and linear models. Institute of Mathematical Statistics, 1992.

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L, Koul H., ed. Weighted empirical processes in dynamic nonlinear models. 2nd ed. Springer, 2002.

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Bulinski, Alexander, ed. Encyclopaedia of Applied Statistics: Using SPSS, Statistica and Matlab: Using SPSS, Statistica and Matlab (3 Volumes). Koros Press Limited, 2015.

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Book chapters on the topic "Double sampling for regression"

1

Di Lorenzo, Renato. "Double Sampling." In Perspectives in Business Culture. Springer Milan, 2012. http://dx.doi.org/10.1007/978-88-470-2534-9_16.

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Cumming, Jeffrey M., Bradley J. Sinclair, Charles A. Triplehorn, et al. "Double Sampling." In Encyclopedia of Entomology. Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6359-6_980.

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Latpate, Raosaheb, Jayant Kshirsagar, Vinod Kumar Gupta, and Girish Chandra. "Double Sampling." In Advanced Sampling Methods. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0622-9_6.

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de Vries, Pieter G. "Regression Estimator." In Sampling Theory for Forest Inventory. Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-71581-5_5.

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de Vries, Pieter G. "Two-Phase Sampling or Double Sampling." In Sampling Theory for Forest Inventory. Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-71581-5_6.

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Särndal, Carl-Erik, Bengt Swensson, and Jan Wretman. "The Regression Estimator." In Model Assisted Survey Sampling. Springer New York, 1992. http://dx.doi.org/10.1007/978-1-4612-4378-6_6.

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Latpate, Raosaheb, Jayant Kshirsagar, Vinod Kumar Gupta, and Girish Chandra. "Adaptive Cluster Double Sampling." In Advanced Sampling Methods. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0622-9_12.

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Latpate, Raosaheb, Jayant Kshirsagar, Vinod Kumar Gupta, and Girish Chandra. "Negative Adaptive Cluster Double Sampling." In Advanced Sampling Methods. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0622-9_17.

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Rao, Malempati M. "Sampling and Regression for Processes." In Springer Monographs in Mathematics. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12172-7_6.

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Särndal, Carl-Erik, Bengt Swensson, and Jan Wretman. "Regression Estimators for Element Sampling Designs." In Model Assisted Survey Sampling. Springer New York, 1992. http://dx.doi.org/10.1007/978-1-4612-4378-6_7.

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Conference papers on the topic "Double sampling for regression"

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Chen, Chong, Zhenfei Zhan, Huili Yu, and Hui Zhao. "A Relevance Vector Regression Based Uncertainty Quantification Method for Robustness Design." In ASME 2017 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/imece2017-71842.

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Metamodel based robustness design is commonly used to mitigate the consequences of variability without removing its underlying sources. However, uncertainties introduced by metamodels should be properly addressed before conducting design optimization. In addition, the measurable data uncertainties from physical tests and computer simulations are also unneglectable. Relevance Vector Regression (RVR) is a probability model based on the Bayesian learning framework. It shows potential in estimating the prediction uncertainty. This paper proposes an alternative RVR based robustness design procedure

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Yu, Hwanjo, and Sungchul Kim. "Passive Sampling for Regression." In 2010 IEEE 10th International Conference on Data Mining (ICDM). IEEE, 2010. http://dx.doi.org/10.1109/icdm.2010.9.

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Nicolaidis, Michael. "Double-sampling architectures." In 2014 IEEE International Reliability Physics Symposium (IRPS). IEEE, 2014. http://dx.doi.org/10.1109/irps.2014.6860626.

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Nicolaidis, Michael, and Michael Dimopoulos. "Advanced double-sampling architectures." In 2016 IEEE 22nd International Symposium on On-Line Testing and Robust System Design (IOLTS). IEEE, 2016. http://dx.doi.org/10.1109/iolts.2016.7604685.

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Hassanpour, Negar, and Russell Greiner. "CounterFactual Regression with Importance Sampling Weights." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/815.

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Perhaps the most pressing concern of a patient diagnosed with cancer is her life expectancy under various treatment options. For a binary-treatment case, this translates into estimating the difference between the outcomes (e.g., survival time) of the two available treatment options – i.e., her Individual Treatment Effect (ITE). This is especially challenging to estimate from observational data, as that data has selection bias: the treatment assigned to a patient depends on that patient's attributes. In this work, we borrow ideas from domain adaptation to address the distributional shift betwee

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Afshari, Robab, Bahram Sadeghpour Gildeh, and Adel Ahmadi Nadi. "Fuzzy Double Variable Sampling Plan." In 2019 15th Iran International Industrial Engineering Conference (IIIEC). IEEE, 2019. http://dx.doi.org/10.1109/iiiec.2019.8720632.

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Drineas, Petros, Michael W. Mahoney, and S. Muthukrishnan. "Sampling algorithms for l2 regression and applications." In the seventeenth annual ACM-SIAM symposium. ACM Press, 2006. http://dx.doi.org/10.1145/1109557.1109682.

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Wai, Hoi-To, and Anna Scaglione. "Decentralized regression with asynchronous sub-Nyquist sampling." In 2014 48th Asilomar Conference on Signals, Systems and Computers. IEEE, 2014. http://dx.doi.org/10.1109/acssc.2014.7094559.

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Tanaka, Akira. "Kernel regression with autocorrelation prior." In 2017 International Conference on Sampling Theory and Applications (SampTA). IEEE, 2017. http://dx.doi.org/10.1109/sampta.2017.8024370.

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Pimentel-Alarcon, Daniel, Laura Balzano, Roummel Marcia, Robert Nowak, and Rebecca Willett. "Mixture regression as subspace clustering." In 2017 International Conference on Sampling Theory and Applications (SampTA). IEEE, 2017. http://dx.doi.org/10.1109/sampta.2017.8024386.

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Reports on the topic "Double sampling for regression"

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Ahmad, M., C. Marcotte, and R. S. Singh. Double Sampling in Estimation of a Ratio. Defense Technical Information Center, 1985. http://dx.doi.org/10.21236/ada160346.

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RASMUSSEN, J. H. Double Shell Tank (DST) Process Waste Sampling Subsystem Specification. Office of Scientific and Technical Information (OSTI), 2000. http://dx.doi.org/10.2172/803637.

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RASMUSSEN, J. H. Double Shell Tank (DST) Process Waste Sampling Subsystem Definition Report. Office of Scientific and Technical Information (OSTI), 2000. http://dx.doi.org/10.2172/803003.

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SASAKI, L. M. Double Shell Tank (DST) Ventilation System Vapor Sampling and Analysis Plan. Office of Scientific and Technical Information (OSTI), 2000. http://dx.doi.org/10.2172/803949.

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Gonzalez, Jhanis, Chunyi Liu, Jong Yoo, Xianglei Mao, and RickRick Russo. Solids sampling using double-pulse laser ablation inductivelycoupled plasma mass spectrometry. Office of Scientific and Technical Information (OSTI), 2003. http://dx.doi.org/10.2172/861019.

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Chojnacky, David C. Double sampling for stratification: a forest inventory application in the Interior West. U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 1998. http://dx.doi.org/10.2737/rmrs-rp-7.

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Idakwo, Gabriel, Sundar Thangapandian, Joseph Luttrell, Zhaoxian Zhou, Chaoyang Zhang, and Ping Gong. Deep learning-based structure-activity relationship modeling for multi-category toxicity classification : a case study of 10K Tox21 chemicals with high-throughput cell-based androgen receptor bioassay data. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41302.

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Deep learning (DL) has attracted the attention of computational toxicologists as it offers a potentially greater power for in silico predictive toxicology than existing shallow learning algorithms. However, contradicting reports have been documented. To further explore the advantages of DL over shallow learning, we conducted this case study using two cell-based androgen receptor (AR) activity datasets with 10K chemicals generated from the Tox21 program. A nested double-loop cross-validation approach was adopted along with a stratified sampling strategy for partitioning chemicals of multiple AR

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Leis, Sherry. Vegetation community monitoring at Lincoln Boyhood National Memorial: 2011–2019. National Park Service, 2021. http://dx.doi.org/10.36967/nrr-2284711.

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Lincoln Boyhood National Memorial celebrates the lives of the Lincoln family including the final resting place of Abraham’s mother, Nancy Hanks Lincoln. Lincoln’s childhood in Indiana was a formative time in the life our 16th president. When the Lincoln family arrived in Indiana, the property was covered in the oak-hickory forest type. They cleared land to create their homestead and farm. Later, designers of the memorial felt that it was important to restore woodlands to the site. The woodlands would help visitors visualize the challenges the Lincoln family faced in establishing and maintainin

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