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Статті в журналах з теми "Multiple robustness"
Coko, Klodian, and Jutta Schickore. "Robustness, solidity, and multiple determinations." Metascience 22, no. 3 (February 6, 2013): 681–83. http://dx.doi.org/10.1007/s11016-013-9750-1.
Повний текст джерелаMolina, J., A. Rotnitzky, M. Sued, and J. M. Robins. "Multiple robustness in factorized likelihood models." Biometrika 104, no. 3 (June 15, 2017): 561–81. http://dx.doi.org/10.1093/biomet/asx027.
Повний текст джерелаWang, Lei. "Multiple robustness estimation in causal inference." Communications in Statistics - Theory and Methods 48, no. 23 (December 4, 2018): 5701–18. http://dx.doi.org/10.1080/03610926.2018.1520881.
Повний текст джерелаRatliff, Jacob, Alessio Franci, Eve Marder, and Timothy O’Leary. "Neuronal oscillator robustness to multiple global perturbations." Biophysical Journal 120, no. 8 (April 2021): 1454–68. http://dx.doi.org/10.1016/j.bpj.2021.01.038.
Повний текст джерелаHolland, Burt, and Siu Hung Cheung. "Familywise robustness criteria for multiple-comparison procedures." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 64, no. 1 (January 2002): 63–77. http://dx.doi.org/10.1111/1467-9868.00325.
Повний текст джерелаCazzavillan, Guido, and Patrick A. Pintus. "Robustness of multiple equilibria in OLG economies." Review of Economic Dynamics 7, no. 2 (April 2004): 456–75. http://dx.doi.org/10.1016/j.red.2003.10.001.
Повний текст джерелаClarke, Sandy, and Peter Hall. "Robustness of multiple testing procedures against dependence." Annals of Statistics 37, no. 1 (February 2009): 332–58. http://dx.doi.org/10.1214/07-aos557.
Повний текст джерелаDong, Gaogao, Yan Chen, Fan Wang, Ruijin Du, Lixin Tian, and H. Eugene Stanley. "Robustness on interdependent networks with a multiple-to-multiple dependent relationship." Chaos: An Interdisciplinary Journal of Nonlinear Science 29, no. 7 (July 2019): 073107. http://dx.doi.org/10.1063/1.5093074.
Повний текст джерелаKwon, Yung-Keun, Junil Kim, and Kwang-Hyun Cho. "Dynamical Robustness against Multiple Mutations in Signaling Networks." IEEE/ACM Transactions on Computational Biology and Bioinformatics 13, no. 5 (September 1, 2016): 996–1002. http://dx.doi.org/10.1109/tcbb.2015.2495251.
Повний текст джерелаRangavajhala, Sirisha, and Sankaran Mahadevan. "Design optimization for robustness in multiple performance functions." Structural and Multidisciplinary Optimization 47, no. 4 (December 13, 2012): 523–38. http://dx.doi.org/10.1007/s00158-012-0860-y.
Повний текст джерелаДисертації з теми "Multiple robustness"
Miller, Charles W. "Familywise Robustness Criteria Revisited for Newer Multiple Testing Procedures." Diss., Temple University Libraries, 2009. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/40501.
Повний текст джерелаPh.D.
As the availability of large datasets becomes more prevalent, so does the need to discover significant findings among a large collection of hypotheses. Multiple testing procedures (MTP) are used to control the familywise error rate (FWER) or the chance to commit at least one type I error when performing multiple hypotheses testing. When controlling the FWER, the power of a MTP to detect significant differences decreases as the number of hypotheses increases. It would be ideal to discover the same false null hypotheses despite the family of hypotheses chosen to be tested. Holland and Cheung (2002) developed measures called familywise robustness criteria (FWR) to study the effect of family size on the acceptance and rejection of a hypothesis. Their analysis focused on procedures that controlled FWER and false discovery rate (FDR). Newer MTPs have since been developed which control the generalized FWER (gFWER (k) or k-FWER) and false discovery proportion (FDP) or tail probabilities for the proportion of false positives (TPPFP). This dissertation reviews these newer procedures and then discusses the effect of family size using the FWRs of Holland and Cheung. In the case where the test statistics are independent and the null hypotheses are all true, the Type R enlargement familywise robustness measure can be expressed as a ratio of the expected number of Type I errors. In simulations, positive dependence among the test statistics was introduced, the expected number of Type I errors and the Type R enlargement FWR increased for step-up procedures with higher levels of correlation, but not for step-down or single-step procedures.
Temple University--Theses
Gu, Wei. "Robustness against interference in Internet of Things." Thesis, Lille 1, 2012. http://www.theses.fr/2012LIL10195/document.
Повний текст джерелаInternet of Things brought great interests in recent years for its attractive applications and intelligent structure. However, the implementation of sensor networks still presents important challenges such as the generation of Multiple-Access-Interference (MAI) with impulsive nature and the relatively high energy consumption. Both the MAI and the thermal noise should be considered due to their strong impairments each may cause on the communication quality. We employ the stable and Gaussian distributions to model the MAI and the thermal noise respectively. Firstly we study the performance of turbo codes in the direct link and we propose the p-norm as a decoding metric. This metric allows a considerable error correction performance improvement which is close to the optimal decoder. Then we investigate cooperative communications. The probability densities in the decision statistic of the optimal receiver are estimated using importance sampling approach when both the stable and Gaussian noises are present. Such a method is computationally expensive. Hence we develop an approximation approach based on the Normal Inverse Gaussian (NIG) distribution. This solution is efficient for calculation and is proximate to the optimal receiver. In addition we show that the p-norm receiver has robust performance no matter what kind of noise is dominant. At last we combine the channel coding and cooperative communication works to establish a distributed channel coding strategy. Through some simulation assessments, the energy saving strategy can be realized by choosing an appropriate distributed channel coding scheme based on the direct link quality and target bit error rate
Sandsveden, Li. "Evaluation of the Robustness of the Brain Parenchymal Fraction for Brain Atrophy Measurements." Thesis, Linköpings universitet, Medicinsk informatik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-105801.
Повний текст джерелаManzano, Castro Marc. "New robustness evaluation mechanism for complex networks." Doctoral thesis, Universitat de Girona, 2014. http://hdl.handle.net/10803/295713.
Повний текст джерелаLa ciència de les xarxes (o network science) ha avançat significativament en l'última dècada, proporcionant coneixement sobre l'estructura subjacent i la dinàmica de les xarxes complexes (o complex networks). Infraestructures crítiques com xarxes de telecomunicacions, juguen un paper fonamental per garantir el bon funcionament de la vida moderna. Aquestes xarxes han de lidiar constantment amb fallades dels seus components. En escenaris de fallades múltiples, on els esquemes de protecció i restauració tradicionals no són adequats degut a la gran quantitat de recursos que serien necessaris, el concepte de robustesa (o robustness) s'utilitza per tal de quantificar com de bona és una xarxa quan es produeix una fallada a gran escala. L'objectiu d'aquesta tesi és, en primer lloc, investigar les amenaces actuals de les xarxes d'avui en dia que poden portar a escenaris de fallades múltiples i, en segon lloc, proposar nous indicadors capaços de quantificar la robustesa d'aquestes xarxes.
Zhang, Yao. "Load Frequency Control of Multiple-Area Power Systems." Cleveland State University / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=csu1250196894.
Повний текст джерелаJoo, Seang-Hwane. "Robustness of the Within- and Between-Series Estimators to Non-Normal Multiple-Baseline Studies: A Monte Carlo Study." Scholar Commons, 2017. http://scholarcommons.usf.edu/etd/6715.
Повний текст джерелаLiang, Xiyin. "Security and robustness of a modified parameter modulation communication scheme." Thesis, Pretoria : [s.n.], 2009. http://upetd.up.ac.za/thesis/available/etd-04072009-204834/.
Повний текст джерелаXu, Guoqing. "Assessment of risk of disproportionate collapse of steel building structures exposed to multiple hazards." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/41079.
Повний текст джерелаHajian-Tilaki, Karimollah. "Methodologic contributions to ROC analysis : a study of the robustness of the binormal model for quantitative data and methods for studies involving multiple signals." Thesis, McGill University, 1995. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=29034.
Повний текст джерелаMetz et al (1990) adapted the binormal model, used previously for rating data only, for ROC analysis of quantitative diagnostic tests. Their investigation of its performance was limited to data generated from the bi-normal model itself. Part (i) of this thesis describes a broader numerical investigation to assess how it performs in various configurations of non-binormal pairs of distributions, where one or both pair members were mixtures of Gaussian (MG) distributions. We also investigated the effects of sample size and the number of data categories used. Three criteria, bias in estimates of the area under the curve (AUC), bias in estimated true positive fraction (TPF's) at specific false positive fraction (FPF) points, and discrepancies between the estimated and true TPF over the wider portion of the ROC curve, were used to assess the impact of departures from binormality. The bias in the estimates of AUC was small for all configurations studied, no matter what amount of discretization and what sample sizes were used. By the other criteria, the binormal model was robust to departures involving $ {$G, MG--skewed or bimodal$ }$ pairs. The fits were less appropriate at FPF = 0.05 and 0.10 when both pair-members were skewed to the right, but even then the bias in estimates of TPF was less than 0.06. The "semi-parametric" and nonparametric approaches yielded very similar estimates of AUC and of the corresponding sampling variability.
Part (ii) develops nonparametric ROC analysis for the situation when pathology and test interpretation data for each patient are K-dimensional. The approach computes K "pseudo-accuracies" for each patient; from these, K U-statistics are derived. One can form a summary index from these K components, as well as the standard error (SE) of this index based on the observed correlations among the pseudo-accuracies. The applicability of a simplified formula for the SE was assessed. The method was also extended to comparisons of two diagnostic systems. The procedures are illustrated using data sets from two clinical studies. The approach can handle the complex structure of multi-signal ROC data; it takes the various inter-correlations into account, and makes efficient use of the data.
Nair, Suraj [Verfasser], Alois [Akademischer Betreuer] Knoll, and Dieter [Akademischer Betreuer] Fox. "Visual Tracking of Multiple Humans with Machine Learning based Robustness Enhancement applied to Real-World Robotic Systems / Suraj Nair. Gutachter: Alois Knoll ; Dieter Fox. Betreuer: Alois Knoll." München : Universitätsbibliothek der TU München, 2012. http://d-nb.info/1031076166/34.
Повний текст джерелаКниги з теми "Multiple robustness"
Robustness of Multiple Objective Decision Analysis Preference Functions. Storming Media, 2002.
Знайти повний текст джерелаVan, Rosendale John, and Langley Research Center, eds. The improved robustness of multigrid elliptic solvers based on multiple semicoarsened grids. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1991.
Знайти повний текст джерелаStanford, Ben. Critical Control Point Assessment to Quantify Robustness and Reliability of Multiple Treatment Barriers of a DPR Scheme. IWA Publishing, 2017.
Знайти повний текст джерелаKim, Hyunchul. Robustness and power of procedures for pairwise multiple comparisons of repeated measures means in the split plot design. 1995.
Знайти повний текст джерелаDuclos, Jean-Yves, and Luca Tiberti. Multidimensional Poverty Indices. Edited by Matthew D. Adler and Marc Fleurbaey. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199325818.013.19.
Повний текст джерелаBianconi, Ginestra. Classical Percolation, Generalized Percolation and Cascades. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.003.0012.
Повний текст джерелаHensel, Paul R. Review of Available Data Sets. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190846626.013.418.
Повний текст джерелаЧастини книг з теми "Multiple robustness"
Boone, Worth. "Multiple Realization and Robustness." In History, Philosophy and Theory of the Life Sciences, 75–94. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01198-7_4.
Повний текст джерелаWei, Zheng, Daeyoung Kim, Tonghui Wang, and Teerawut Teetranont. "A Multivariate Generalized FGM Copulas and Its Application to Multiple Regression." In Robustness in Econometrics, 363–78. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-50742-2_22.
Повний текст джерелаWieber, Frédéric. "Multiple Means of Determination and Multiple Constraints of Construction: Robustness and Strategies for Modeling Macromolecular Objects." In Characterizing the Robustness of Science, 267–88. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-2759-5_11.
Повний текст джерелаNederbragt, Hubertus. "Multiple Derivability and the Reliability and Stabilization of Theories." In Characterizing the Robustness of Science, 121–45. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-2759-5_5.
Повний текст джерелаSiskos, Eleftherios, Giannis Kourousias, and Yannis Siskos. "Bipolar Multicriteria Aggregation-Disaggregation Robustness Approach: Theory and Application on European e-Government Benchmarking." In Multiple Criteria Decision Making, 121–52. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7414-3_7.
Повний текст джерелаKhan, Akhtar A., Elisabeth Köbis, and Christiane Tammer. "Scalarization Methods in Multiobjective Optimization, Robustness, Risk Theory and Finance." In Multiple Criteria Decision Making in Finance, Insurance and Investment, 135–57. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21158-9_6.
Повний текст джерелаPalar, Pramudita Satria, and Koji Shimoyama. "Multiple Metamodels for Robustness Estimation in Multi-objective Robust Optimization." In Lecture Notes in Computer Science, 469–83. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54157-0_32.
Повний текст джерелаHunt, Rachel, Mark Johnston, and Mengjie Zhang. "Improving Robustness of Multiple-Objective Genetic Programming for Object Detection." In AI 2011: Advances in Artificial Intelligence, 311–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25832-9_32.
Повний текст джерелаBrown, Matthew, William B. Haskell, and Milind Tambe. "Addressing Scalability and Robustness in Security Games with Multiple Boundedly Rational Adversaries." In Lecture Notes in Computer Science, 23–42. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12601-2_2.
Повний текст джерелаZhang, Zhenya, Deyun Lyu, Paolo Arcaini, Lei Ma, Ichiro Hasuo, and Jianjun Zhao. "Effective Hybrid System Falsification Using Monte Carlo Tree Search Guided by QB-Robustness." In Computer Aided Verification, 595–618. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81685-8_29.
Повний текст джерелаТези доповідей конференцій з теми "Multiple robustness"
Coraluppi, Stefano. "Robustness in Multiple-Hypothesis Tracking." In 2022 25th International Conference on Information Fusion (FUSION). IEEE, 2022. http://dx.doi.org/10.23919/fusion49751.2022.9841345.
Повний текст джерелаStecha, Jan, Vladimir Havlena, and Jiri Roubal. "Robustness of multiple model LQ control." In 2003 European Control Conference (ECC). IEEE, 2003. http://dx.doi.org/10.23919/ecc.2003.7085277.
Повний текст джерелаPimentel, Benjamin, Alex Bordetsky, and Ralucca Gera. "Robustness in Nonorthogonal Multiple Access 5G Networks." In Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences, 2022. http://dx.doi.org/10.24251/hicss.2022.893.
Повний текст джерелаFan, Wang, Dong Gaogao, Du Ruijin, and Tian Lixin. "Robustness of multiple interdependent networks under shell attack." In 2017 36th Chinese Control Conference (CCC). IEEE, 2017. http://dx.doi.org/10.23919/chicc.2017.8027554.
Повний текст джерелаUbar, Raimund, Sergei Kostin, and Jaan Raik. "About robustness of test patterns regarding multiple faults." In 2012 13th Latin American Test Workshop - LATW. IEEE, 2012. http://dx.doi.org/10.1109/latw.2012.6261243.
Повний текст джерелаFrehse, Stefan, Görschwin Fey, André Suflow, and Rolf Drechsler. "Robustness Check for Multiple Faults Using Formal Techniques." In 2009 12th Euromicro Conference on Digital System Design, Architectures, Methods and Tools (DSD). IEEE, 2009. http://dx.doi.org/10.1109/dsd.2009.218.
Повний текст джерелаSegovia, Juan, Jose L. Marzo, Eusebi Calle, and Pere Vila. "Robustness analysis to multiple failures in GMPLS networks." In 2010 12th International Conference on Transparent Optical Networks (ICTON). IEEE, 2010. http://dx.doi.org/10.1109/icton.2010.5548982.
Повний текст джерелаXie, Xiaoyuan, Ying Duan, Songqiang Chen, and Jifeng Xuan. "Towards the Robustness of Multiple Object Tracking Systems." In 2022 IEEE 33rd International Symposium on Software Reliability Engineering (ISSRE). IEEE, 2022. http://dx.doi.org/10.1109/issre55969.2022.00046.
Повний текст джерелаDasari, Venkateswara R., Billy Geerhart, and David Alexander. "Increasing image segmentation accuracy on small datasets by merging multiple inferences on augmented images." In Security, Robustness, and Trust in Artificial Intelligence and Distributed Architectures, edited by Misty Blowers, Russell D. Hall, and Venkateswara R. Dasari. SPIE, 2022. http://dx.doi.org/10.1117/12.2618571.
Повний текст джерелаMiyauchi, Ryoichi, Akio Yoshida, Shuya Nakano, Hiroki Tamura, Koichi Tanno, Yutaka Fukuchi, Yukio Kawamura, Yuki Kodama, and Yuichi Sekiya. "Novel Fractional-N All Digital Frequency Locked Loop with Robustness for PVT variation." In 2020 IEEE 50th International Symposium on Multiple-Valued Logic (ISMVL). IEEE, 2020. http://dx.doi.org/10.1109/ismvl49045.2020.00-12.
Повний текст джерелаЗвіти організацій з теми "Multiple robustness"
Hurdle, Daniel J. Development of Stability/Robustness Considerations for Control System Design with Multiple Input/Multiple Output Plants. Fort Belvoir, VA: Defense Technical Information Center, June 1988. http://dx.doi.org/10.21236/ada200408.
Повний текст джерелаLettenmaier, D. P., K. L. Brettman, and L. W. Vail. Robustness of a multiple-use reservoir to seasonal runoff shifts associated with climate change. Office of Scientific and Technical Information (OSTI), May 1990. http://dx.doi.org/10.2172/6418073.
Повний текст джерелаMitra, Sudeshna, Amlanjyoti Goswami, Deepika Jha, Sahil Sasidharan, Kaye Lushington, and Tsomo Wangchuk. Land Records Modernisation in India: Himachal Pradesh. Indian Institute for Human Settlements, 2021. http://dx.doi.org/10.24943/9788195648504.
Повний текст джерелаChow, S. I., M. D. Zoltowski, and G. M. Kautz. Multiply-Constrained MVDR Matched Field Processing With A-Posteriori Constraints for Enhanced Robustness to Mismatch. Fort Belvoir, VA: Defense Technical Information Center, December 1991. http://dx.doi.org/10.21236/ada244883.
Повний текст джерелаDahal, Sachindra, and Jeffery Roesler. Passive Sensing of Electromagnetic Signature of Roadway Material for Lateral Positioning of Vehicle. Illinois Center for Transportation, November 2021. http://dx.doi.org/10.36501/0197-9191/21-039.
Повний текст джерелаMcEntee, Alice, Sonia Hines, Joshua Trigg, Kate Fairweather, Ashleigh Guillaumier, Jane Fischer, Billie Bonevski, James A. Smith, Carlene Wilson, and Jacqueline Bowden. Tobacco cessation in CALD communities. The Sax Institute, June 2022. http://dx.doi.org/10.57022/sneg4189.
Повний текст джерела