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Relevant bibliographies by topics / Methods of selecting

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Academic literature on the topic 'Methods of selecting'

Author: Grafiati

Published: 4 June 2021

Last updated: 4 February 2022

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Journal articles on the topic "Methods of selecting"

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Saqib, Zunaira, Maria Khan, Nihaal Raza, Zainab Sohail, and Aliha Zainab. "Selecting the Selection Methods at a Pakistani NGO." Asian Journal of Management Cases 13, no. 1 (February 11, 2016): 23–31. http://dx.doi.org/10.1177/0972820115618780.

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Brinkman, Paul T., and Deborah J. Teeter. "Methods for selecting comparison groups." New Directions for Institutional Research 1987, no. 53 (1987): 5–23. http://dx.doi.org/10.1002/ir.37019875303.

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Fedorov, Valerii V., Agnes M. Herzberg, and Sergei L. Leonov. "Methods of Selecting Informative Variables." Biometrical Journal 48, no. 1 (February 2006): 157–73. http://dx.doi.org/10.1002/bimj.200410146.

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Panacek, Edward A., and Cheryl Bagley Thompson. "Sampling methods: Selecting your subjects." Air Medical Journal 26, no. 2 (March 2007): 75–78. http://dx.doi.org/10.1016/j.amj.2007.01.001.

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Sleptsova, Y. A. "Methods of selecting antirisk controlling actions." St. Petersburg State Polytechnical University Journal. Economics 233, no. 6 (January 2016): 222–32. http://dx.doi.org/10.5862/je.233.23.

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ACIKEL, Cengiz, and Selim KILIC. "SELECTING STATISTICAL METHODS IN MEDICAL RESEARCHES." TAF Preventive Medicine Bulletin 3, no. 7 (2004): 162. http://dx.doi.org/10.5455/pmb.20040307162.

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Maiden, N. A. M., and G. Rugg. "ACRE: selecting methods for requirements acquisition." Software Engineering Journal 11, no. 3 (1996): 183. http://dx.doi.org/10.1049/sej.1996.0024.

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Streicher, Robert P., Christopher M. Reh, Rosa Key-Schwartz, Paul C. Schlecht, Mary Ellen Cassinelli, and Paula Fey O'Connor. "Selecting Isocyanate Sampling and Analytical Methods." Applied Occupational and Environmental Hygiene 17, no. 3 (March 2002): 157–62. http://dx.doi.org/10.1080/104732202753438234.

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Willis, H. L., H. Tram, M. V. Engel, and L. Finley. "Selecting and applying distribution optimization methods." IEEE Computer Applications in Power 9, no. 1 (1996): 12–17. http://dx.doi.org/10.1109/67.475954.

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Keitel, Holger, Andrea Dimmig-Osburg, Lucie Vandewalle, and Luc Schueremans. "Selecting creep models using Bayesian methods." Materials and Structures 45, no. 10 (March 21, 2012): 1513–33. http://dx.doi.org/10.1617/s11527-012-9854-x.

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Dissertations / Theses on the topic "Methods of selecting"

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Hawkins, Robert Edward. "New methods for selecting high affinity antibodies." Thesis, Open University, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.240367.

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Parkes, Sally J. "A comparison of methods for selecting untagged animals for breeding purposes." Thesis, Bangor University, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.273622.

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Auclair, Paul Fernand. "Applications from simulation to the problem of selecting exponential populations." Diss., Georgia Institute of Technology, 1993. http://hdl.handle.net/1853/25579.

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Zvěřinová, Iva. "Metody výběru pracovníků a jejich využití." Master's thesis, Vysoká škola ekonomická v Praze, 2010. http://www.nusl.cz/ntk/nusl-72396.

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The thesis presents a theoretical knowledge of staffing, especially pay attention to methods of selection and use of them. Application of work sampling analysis of the company and assess the methods that are used in selecting employees in different occupations. Finally are these methods evaluated and recommended changes.

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Eriksson, Stefan. "Visual replenishment methods in manufacturing industry and suggestion for a decision tool." Licentiate thesis, KTH, Produktionssystem, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-123095.

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In almost all supply chains, materials need to be stored or buffered, implying that manufacturing companies need effective replenishment methods. However, this is challenging, since companies must balance inventory costs and customer service in complex and different situations. Therefore, it is important to choose replenishment methods carefully. One well-known and widespread method is Material Requirements Planning (MRP). But the method has problems, such as regarding volume flexibility. There are other methods, but the literature lacks case studies and detailed descriptions and analysis of them, especially for visually oriented methods. Therefore, it is important to explore different methods for materials supply. The purpose of this study is to analyze the application of visually oriented replenishment methods in manufacturing industry and further to design a tentative decision tool for selecting methods. The research aims to provide some answers to three key questions. The first research question concerns general factors that are important for evaluating how effective replenishment methods are. From the literature review, different factors emerged such as product characteristics (fit in the Kraljic matrix, volume issues, size, etc.); information, trust, and geographical proximity between supplier and customer; and different logistics goals (delivery service elements, tied-up capital, use of resources, inventory accuracy). It is also import to include the basic principles methods are related to. The factors were summarized in an analysis model, which is structured with three main areas (planning environment/conditions, basic principles, and effects). The model is used to analyze four case studies. The second research question focuses on the characteristics for visually orientedreplenishment methods. Examples of characteristics are: easy to understand and operate, offers uncomplicated flows, substantially applicable for noncritical and leverage parts with high yearly requirement and fairly even consumption, provides potential for reduced errors in stores/flows, potential for providing high delivery service and low levels of tied-up capital and resource utilization. The third research question focuses on what a tentative decision tool for selecting replenishment methods might look like, based on the factors that emerged from the other research questions and studies by others. In order to achieve an efficient materials supply, companies need to consider these factors when selecting replenishment methods. The decision tool consists of different steps, considering aspects of the planning environment/conditions in relation to the product and the supplier. The importance of the companies’ goals/motives for materials supply must also be assessed. The output from the decision tool is appropriate replenishment methods.

QC 20130603

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Kisthardt, Adam M. "Selecting hostage negotiators for the Pennsylvania State Police Special Emergency Response Team an examination of methods of personnel selection /." Click here to access this electronic resource. Access available to Kutztown University faculty, staff, and students only. Instructions for remote access, 2000. http://www.kutztown.edu/library/services/remote_access.asp.

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Thesis (M.P.A.)--Kutztown University of Pennsylvania, 2000.
Source: Masters Abstracts International, Volume: 45-06, page: 2946. Typescript. Abstract precedes thesis as, preliminary leaves [2-3]. Includes bibliographical references (leaves 89-90).

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Royster, Reba Michelle. "Strategies for Selecting and Individualizing Training for Employee Positioning." ScholarWorks, 2018. https://scholarworks.waldenu.edu/dissertations/5652.

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Lack of effective selection and training of employees for positioning within a business can have extensive financial repercussions. Fostering mentoring relationships between leaders and employees increases competitive advantage and institutional financial growth. However, there is limited research that supports the role of mentoring leadership styles for improving organizational productivity. The purpose of this single case study was to explore strategies used by business managers to select and individually train employees for opportunities within the organization to achieve job-person fit. The sample included 5 business managers employed within a medium-sized organization in a consultation firm in the mid-Atlantic region of the United States. Strategic human resource management theory formed the conceptual framework for this study. Data collection used semistructured interviews and employee performance evaluations. Yin's 5 steps for qualitative data analysis provided the process for organizing the data and conducting the data analysis. Four themes emerged from the data analysis including job-person fit, organizational culture, employee relationships, and performance management. Potential contributions to positive social change include increasing employee retention rates, which could benefit local business economies due to the retained employees'sustained local buying power and contributions to their communities' charities.

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Robertson, Gail Alexandra. "Computerised methods for selecting a small number of single nucleotide polymorphisms that enable bacterial strain discrimination." Queensland University of Technology, 2006. http://eprints.qut.edu.au/16284/.

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The possibility of identifying single nucleotide polymorphisms (SNPs) that would be useful for rapid bacterial typing was investigated. Neisseria meningitidis was the organism chosen for modelling the approach since informative SNPs could be found amongst the sequence data available for multi-locus sequence typing (MLST) at http://www.mlst.net. The hypothesis tested was that a small number of SNPs located within the seven gene fragments sequenced for MLST provide information equivalent to MLST. Preliminary investigations revealed that a small number of SNPs could be utilised to highly discriminate sequence types (STs) of clinical interest. Laboratory procedures demonstrated that SNP fingerprinting of N. meningitidis isolates is achievable. Further tests showed that laboratory identification of a defining SNP in the genome of isolates was to be a practical method of obtaining relevant typing information. Identification of the most discriminating SNPs amongst the ever-increasing amount of MLST sequence data summoned the need for computer-based assistance. Two methods of SNP selection devised by the author of this thesis were translated into computer-based algorithms by contributing team members. Software for two computer programs was produced. The algorithms facilitate the optimal selection of SNPs useful for (1) distinguishing specific STs and (2) differentiating non-specific STs. Current input information can be obtained from the MLST database and consequently the programs can be applied to any bacterial species for which MLST data have been entered. The two algorithms for the selection of SNPs were designed to serve contrasting purposes. The first of these was to determine the ST identity of isolates from an outbreak of disease. In this case, isolates would be tested for their membership to any of the STs known to be associated with disease. It was shown that one SNP per ST could distinguish each of four hyperinvasive STs of N. meningitidis from between 92.5% and 97.5% of all other STs. With two SNPs per ST, between 96.7% and 99.0% discrimination is achieved. The SNPs were selected from MLST loci with the assistance of the first algorithm which scores SNPs according to the number of base mismatches in a sequence alignment between an allele of an ST of interest and alleles belonging to all other STs at a specified locus. The second purpose was to determine whether or not isolates from different sources belong to the same ST, regardless of their actual ST identity. It was shown that with seven SNPs, four sample STs of N. meningitidis could, on average, be discriminated from 97.1% of all other STs. The SNPs were selected with the aid of the second algorithm which scores SNPs at MLST loci for the relative frequency of each nucleotide base in a sequence alignment as a measure of the extent of their polymorphism. A third algorithm for selecting SNPs has been discussed. By altering the method of scoring SNPs, it is possible to overcome the limitations inherent in the two algorithms that were utilised for finding SNPs. In addition, the third approach caters for finding SNPs that distinguish members of a complex from non-members.

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Finch, Aureliano Paolo. "An investigation of methods for identifying and selecting bolt-on dimensions : the EQ-5D-5L case study." Thesis, University of Sheffield, 2017. http://etheses.whiterose.ac.uk/19113/.

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In health economics benefits are often measured in terms of quality adjusted life years (QALYs), an index that combines the length of life and the health related quality of life (HRQoL) of patients. HRQoL is usually estimated using generic preference based measures (GPBMs). To ensure comparable decisions it would be recommended to use only one GPBM in all assessments, but this is not always appropriate due to validity and responsiveness problems of these measures. When this happens, bolt-ons represent a potential solution. Bolt-on research is at an early stage, and the process of how to identify and select bolt-ons is still unclear. To address this gap, this thesis examines methods for identifying and selecting bolt-on dimensions, using the EQ-5D as a case study. This thesis summarizes the results of four studies. The first study examined the performance of the 5 most commonly used GPBMs across all disease areas and conditions, using an overview of systematic reviews. The second study investigated the possibility of using factor analysis techniques to identify bolt-on dimensions. The third study explored whether it is possible to select between bolt-ons using their ability to predict differences in HRQoL. The fourth study examined whether it is possible to select between bolt-ons using preferences elicited from pairwise choices over health states. A number of important findings were made. First, GPBMs appear generally valid and responsive across many disease areas, but the quality, nature and breath of evidence makes difficult to draw definitive conclusions. Second, factor analysis techniques can be used to identify bolt-on dimensions. Exploratory and confirmatory factor analysis need to be used in conjunction. Third, bolt-ons differ in their ability to predict differences in HRQoL and for this reason they might be selected based on this information. Fourth, bolt-ons differ in terms of their impact on preferences and for this reason they might be selected based on this information. Overall, a key contribution of this thesis is to systematically examine methods for identifying and selecting bolt-ons for generic preference based measures.

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Chen, I.-Chen. "Improved Methods and Selecting Classification Types for Time-Dependent Covariates in the Marginal Analysis of Longitudinal Data." UKnowledge, 2018. https://uknowledge.uky.edu/epb_etds/19.

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Generalized estimating equations (GEE) are popularly utilized for the marginal analysis of longitudinal data. In order to obtain consistent regression parameter estimates, these estimating equations must be unbiased. However, when certain types of time-dependent covariates are presented, these equations can be biased unless an independence working correlation structure is employed. Moreover, in this case regression parameter estimation can be very inefficient because not all valid moment conditions are incorporated within the corresponding estimating equations. Therefore, approaches using the generalized method of moments or quadratic inference functions have been proposed for utilizing all valid moment conditions. However, we have found that such methods will not always provide valid inference and can also be improved upon in terms of finite-sample regression parameter estimation. Therefore, we propose a modified GEE approach and a selection method that will both ensure the validity of inference and improve regression parameter estimation. In addition, these modified approaches assume the data analyst knows the type of time-dependent covariate, although this likely is not the case in practice. Whereas hypothesis testing has been used to determine covariate type, we propose a novel strategy to select a working covariate type in order to avoid potentially high type II error rates with these hypothesis testing procedures. Parameter estimates resulting from our proposed method are consistent and have overall improved mean squared error relative to hypothesis testing approaches. Finally, for some real-world examples the use of mean regression models may be sensitive to skewness and outliers in the data. Therefore, we extend our approaches from their use with marginal quantile regression to modeling the conditional quantiles of the response variable. Existing and proposed methods are compared in simulation studies and application examples.

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Books on the topic "Methods of selecting"

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Vogt, W. Selecting Research Methods. 1 Oliver's Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications Ltd, 2008. http://dx.doi.org/10.4135/9781446263396.

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Johnson, Jeffrey C. Selecting ethnographic informants. Newbury Park, Calif: Sage Publications, 1990.

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National Research Council (U.S.). Transportation Research Board and Airport Cooperative Research Program, eds. A guidebook for selecting airport capital project delivery methods. Washington, D.C: Transportation Research Board, 2009.

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Touran, Ali, Douglas D. Gransberg, Keith R. Molenaar, Kamran Ghavamifar, and Payam Bakhshi. A Guidebook for Selecting Airport Capital Project Delivery Methods. Washington, D.C.: National Academies Press, 2009. http://dx.doi.org/10.17226/14312.

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Building quality management systems: Selecting the right methods and tools. Boca Raton: CRC Press, 2013.

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Dick, JS, ed. Basic Rubber Testing: Selecting Methods for a Rubber Test Program. 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959: ASTM International, 2003. http://dx.doi.org/10.1520/mnl39-eb.

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International Association of Concrete Repair Specialists. Technical Guidelines Committee. Guide for selecting application methods for the repair of concrete surfaces. Washington, D.C: The Association, 1992.

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National Research Council (U.S.). Transportation Research Board, Airport Cooperative Research Program, United States. Federal Aviation Administration, Gresham Smith and Partners, and Terra Hydr Inc, eds. Guidebook for selecting methods to monitor airport and aircraft deicing materials. Washington, D.C: Transportation Research Board, 2012.

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Mericas, Jill Greene and Dean. Guidebook for Selecting Methods to Monitor Airport and Aircraft Deicing Materials. Washington, D.C.: Transportation Research Board, 2017. http://dx.doi.org/10.17226/22749.

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Don, Nance, and Myers Pennie, eds. Adaptive counseling and therapy: A systematic approach to selecting effective treatments. San Francisco: Jossey-Bass, 1987.

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Book chapters on the topic "Methods of selecting"

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Watson, David, Janice West, and Jo Campling. "Selecting Methods." In Social Work Process and Practice: Approaches, Knowledge and Skills, 110–26. London: Macmillan Education UK, 2006. http://dx.doi.org/10.1007/978-0-230-62816-8_7.

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Armstrong, J. Scott. "Selecting Forecasting Methods." In International Series in Operations Research & Management Science, 365–86. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-0-306-47630-3_16.

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Piganeau, Nicolas. "Selecting Allosteric Ribozymes." In Methods in Molecular Biology, 317–28. Totowa, NJ: Humana Press, 2012. http://dx.doi.org/10.1007/978-1-61779-545-9_19.

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Halevi, Gideon, and Roland D. Weill. "Selecting detailed methods of production." In Principles of Process Planning, 120–33. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-1250-5_6.

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Cleveland, Matthew A., and Nader Deeb. "Selecting Markers and Evaluating Coverage." In Methods in Molecular Biology, 55–71. Totowa, NJ: Humana Press, 2012. http://dx.doi.org/10.1007/978-1-61779-785-9_5.

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Esposito, Floriana, Donato Malerba, and Giovanni Semeraro. "Discovering Probabilistic Causal Relationships: A Comparison Between Two Methods." In Selecting Models from Data, 233–42. New York, NY: Springer New York, 1994. http://dx.doi.org/10.1007/978-1-4612-2660-4_24.

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York, Jeremy C., and David Madigan. "Markov Chain Monte Carlo Methods for Hierarchical Bayesian Expert Systems." In Selecting Models from Data, 445–52. New York, NY: Springer New York, 1994. http://dx.doi.org/10.1007/978-1-4612-2660-4_45.

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Runnalls, Andrew. "A Survey of Sampling Methods for Inference on Directed Graphs." In Selecting Models from Data, 153–62. New York, NY: Springer New York, 1994. http://dx.doi.org/10.1007/978-1-4612-2660-4_16.

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Holley, Benjamin L., and Bruce E. Eaton. "Methods for Selecting Catalytic Nucleic Acids." In Evolutionary Methods in Biotechnology, 87–111. Weinheim, FRG: Wiley-VCH Verlag GmbH & Co. KGaA, 2005. http://dx.doi.org/10.1002/3527603697.ch8.

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Byrne, Barbara M. "Selecting Sem Computer Programs." In Handbook of Quantitative Methods for Educational Research, 367–94. Rotterdam: SensePublishers, 2013. http://dx.doi.org/10.1007/978-94-6209-404-8_17.

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Conference papers on the topic "Methods of selecting"

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Petrova, M. V., and E. S. Volkova. "Fuzzy programming methods to selecting portfolios." In 2015 XVIII International Conference on Soft Computing and Measurements (SCM). IEEE, 2015. http://dx.doi.org/10.1109/scm.2015.7190478.

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Houldridge, D. "Introduction to the use of real options and a comparison with existing methods." In IEE Seminar on Justifying and Selecting Innovation Projects. IEE, 2005. http://dx.doi.org/10.1049/ic:20050353.

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Mitchell, Brian A., Daniel A. McAdams, Robert B. Stone, and Irem Y. Tumer. "Computational Methods to Predict and Avoid Design Failure." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-79907.

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Component selection can be a difficult task for designers, and the components they choose can have a large impact on the robustness of the design. Using previous methods to predict and identify potential failure modes, known as the function-failure design method (FFDM), the impact on failure of selecting a particular component over another can be explored based on failure results from previous design endeavors using the same component. This assists designers in selecting the component that is best suited for the application. Since the predicted distribution of failure modes changes depending on the selected component, failure reduction is possible through component selection. Through this method of component selection, risk can be decreases and potential failures can be eliminated. Experiments based on undergraduate student competition design projects are presented to illustrate this method’s ability to predict failure modes. Initial results indicate that the predictions are accurate and meaningful to designers. The experiment also serves as initial validation previous work in the area of failure prediction.

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Li, Wenheng. "Some Specific Methods About Selecting Dams' Address." In 2017 3rd International Conference on Economics, Social Science, Arts, Education and Management Engineering (ESSAEME 2017). Paris, France: Atlantis Press, 2017. http://dx.doi.org/10.2991/essaeme-17.2017.226.

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Le, Thanh-Binh, and Sang-Woon Kim. "On Selecting Useful Unlabeled Data Using Multi-view Learning Techniques." In International Conference on Pattern Recognition Applications and Methods. SCITEPRESS - Science and and Technology Publications, 2015. http://dx.doi.org/10.5220/0005171301570164.

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Lipaev, Aleksander. "CRITERIA FOR SELECTING METHODS OF DEVELOPING HEAVY HYDROCARBONS." In 13th SGEM GeoConference on SCIENCE AND TECHNOLOGIES IN GEOLOGY, EXPLORATION AND MINING. Stef92 Technology, 2013. http://dx.doi.org/10.5593/sgem2013/ba1.v1/s03.020.

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Tromp, Nynke, Reint Jan Renes, and Jaap Daalhuizen. "Heuristics for selecting and using behavioural design methods." In Design Research Society Conference 2018. Design Research Society, 2018. http://dx.doi.org/10.21606/drs.2018.607.

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Mahrin, Mohd Naz'ri, Paul Strooper, and David Carrington. "Selecting Usability Evaluation Methods for Software Process Descriptions." In 2009 16th Asia-Pacific Software Engineering Conference (APSEC). IEEE, 2009. http://dx.doi.org/10.1109/apsec.2009.33.

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Shtern, Mark, and Vassilios Tzerpos. "Methods for selecting and improving software clustering algorithms." In 2009 IEEE 17th International Conference on Program Comprehension (ICPC). IEEE, 2009. http://dx.doi.org/10.1109/icpc.2009.5090051.

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Wei Ding and Rongzeng Cao. "Methods for selecting the optimal portfolio of projects." In 2008 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI). IEEE, 2008. http://dx.doi.org/10.1109/soli.2008.4682979.

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Reports on the topic "Methods of selecting"

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Hartley, III, D., C. Snyder, and M. Boling. Decision analysis methods for selecting RFP (Request for Proposal) responses. Office of Scientific and Technical Information (OSTI), September 1989. http://dx.doi.org/10.2172/5174065.

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Crockett, A. B., H. D. Craig, T. F. Jenkins, and W. E. Sisk. Field sampling and selecting on-site analytical methods for explosives in soil. Office of Scientific and Technical Information (OSTI), December 1996. http://dx.doi.org/10.2172/527939.

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Fahr, Sven, Daniel Tschopp, Jan Erik Nielsen, Korbinian Kramer, and Philip Ohnewein. Review of In Situ Test Methods for Solar Collectors and Solar Collector Arrays. IEA SHC Task 55, December 2020. http://dx.doi.org/10.18777/ieashc-task55-2020-0014.

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This fact sheet presents three in situ test methods for solar collectors and solar collector arrays, namely In situ Collector Certification (ICC), Performance Check for Collector Arrays (PC) and Dynamic Collector Array Test (D-CAT). A comparison is made regarding their scopes and use cases, methodologies and outcomes, which could serve as a decision-making aid for stakeholders in selecting the procedure that best suits their needs. The analysis shows that the methods do not contradict, but rather complement each other.

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Karam, Sofia, Morteza Nagahi, Vidanelage Dayarathna, Junfeng Ma, Raed Jaradat, and Michael Hamilton. Integrating systems thinking skills with multi-criteria decision-making technology to recruit employee candidates. Engineer Research and Development Center (U.S.), June 2021. http://dx.doi.org/10.21079/11681/41026.

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The emergence of modern complex systems is often exacerbated by a proliferation of information and complication of technologies. Because current complex systems challenges can limit an organization's ability to efficiently handle socio-technical systems, it is essential to provide methods and techniques that count on individuals' systems skills. When selecting future employees, companies must constantly refresh their recruitment methods in order to find capable candidates with the required level of systemic skills who are better fit for their organization's requirements and objectives. The purpose of this study is to use systems thinking skills as a supplemental selection tool when recruiting prospective employees. To the best of our knowledge, there is no prior research that studied the use of systems thinking skills for recruiting purposes. The proposed framework offers an established tool to HRM professionals for assessing and screening of prospective employees of an organization based on their level of systems thinking skills while controlling uncertainties of complex decision-making environment with the fuzzy linguistic approach. This framework works as an expert system to find the most appropriate candidate for the organization to enhance the human capital for the organization.

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Fink, Eugene. Statistical Selection Among Problem-Solving Methods. Fort Belvoir, VA: Defense Technical Information Center, January 1997. http://dx.doi.org/10.21236/ada327284.

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Vaidya, Bikas. Selective spectroscopic methods for water analysis. Office of Scientific and Technical Information (OSTI), June 1997. http://dx.doi.org/10.2172/537286.

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Bai, Z. D., P. R. Krishnaiah, and L. C. Zhao. Signal Processing Using Model Selection Methods,. Fort Belvoir, VA: Defense Technical Information Center, January 1986. http://dx.doi.org/10.21236/ada167318.

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Carretta, THomas R. US Air Force Pilot Selection and Training Methods. Fort Belvoir, VA: Defense Technical Information Center, January 2000. http://dx.doi.org/10.21236/ada430320.

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Wei-Yin, Loh. Bootstrap Calibration, Model Selection and Tree-Structured Methods. Fort Belvoir, VA: Defense Technical Information Center, April 1998. http://dx.doi.org/10.21236/ada344443.

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Becker, Jennifer J., and Michel R. Gagne. Selective Methods for C-X Activation in Carbohydrates. Fort Belvoir, VA: Defense Technical Information Center, January 2013. http://dx.doi.org/10.21236/ada579558.

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