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Gotowe bibliografie tematyczne / CLUSTER VARIANCE

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Gotowa bibliografia na temat „CLUSTER VARIANCE”

Autor: Grafiati

Data publikacji: 11 września 2023

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Rozprawy doktorskie na temat "CLUSTER VARIANCE"

1

Akdemir, Deniz. "Components Of Response Variance For Cluster Samples." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/1206044/index.pdf.

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Measures of data quality are important for the evaluation and improvement of survey design and procedures. A detailed investigation of the sources, magnitude and impact of errors is necessary to identify how survey design and procedures may be improved and how resources allocated more efficiently among various aspects of the survey operation. A major part of this thesis is devoted to the overview of statistical theory and methods for measuring the contribution of response variability to the overall error of a survey. A very common practice in surveys is to select groups (clusters) of elements

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You, Zhiying. "Power and sample size of cluster randomized trials." Thesis, Birmingham, Ala. : University of Alabama at Birmingham, 2008. https://www.mhsl.uab.edu/dt/2009r/you.pdf.

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Park, Misook. "Design and Analysis Methods for Cluster Randomized Trials with Pair-Matching on Baseline Outcome: Reduction of Treatment Effect Variance." VCU Scholars Compass, 2006. http://hdl.handle.net/10156/2195.

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Dunning, Allison. "Comparing Bootstrap and Jackknife Variance Estimation Methods for Area Under the ROC Curve Using One-Stage Cluster Survey Data." VCU Scholars Compass, 2009. http://scholarscompass.vcu.edu/etd/1849.

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The purpose of this research is to examine the bootstrap and jackknife as methods for estimating the variance of the AUC from a study using a complex sampling design and to determine which characteristics of the sampling design effects this estimation. Data from a one-stage cluster sampling design of 10 clusters was examined. Factors included three true AUCs (.60, .75, and .90), three prevalence levels (50/50, 70/30, 90/10) (non-disease/disease), and finally three number of clusters sampled (2, 5, or 7). A simulated sample was constructed for each of the 27 combinations of AUC, prevalence

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5

Randriatsiferana, Rivo Sitraka A. "Optimisation énergétique des protocoles de communication des réseaux de capteurs sans fil." Thesis, La Réunion, 2014. http://www.theses.fr/2014LARE0019/document.

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Pour augmenter la durée de vie des réseaux de capteurs sans fil, une solution est d'améliorer l'efficacité énergétique des protocoles de communication. Le regroupement des nœuds du réseau de capteurs sans fil en cluster est l'une des meilleures méthodes. Cette thèse présente propose plusieurs améliorations en modifiant les paramètres du protocole de référence LEACH. Pour améliorer la distribution énergétique des "cluster-heads", nous proposons deux protocoles de clustering centralisés k-LEACH et sa version optimisée k-LEACH-VAR. Un algorithme distribué, appelé e-LEACH, est également proposé po

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Diaz, Acosta Beatriz. "Experiments in Image Segmentation for Automatic US License Plate Recognition." Thesis, Virginia Tech, 2004. http://hdl.handle.net/10919/9988.

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License plate recognition/identification (LPR/I) applies image processing and character recognition technology to identify vehicles by automatically reading their license plates. In the United States, however, each state has its own standard-issue plates, plus several optional styles, which are referred to as special license plates or varieties. There is a clear absence of standardization and multi-colored, complex backgrounds are becoming more frequent in license plates. Commercially available optical character recognition (OCR) systems generally fail when confronted with textured or poorly c

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Piana, Clause Fátima de Brum. "Regionalização para o cultivo do feijão no Rio Grande do Sul com base na interação genótipo x ambiente." Universidade Federal de Pelotas, 2009. http://repositorio.ufpel.edu.br/handle/ri/2081.

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Made available in DSpace on 2014-08-20T14:06:15Z (GMT). No. of bitstreams: 1 Tese_ Clause_Fatima_ Piana.pdf: 1906168 bytes, checksum: 6bfd8bec615dee869166bbd0c0269e0d (MD5) Previous issue date: 2009-03-13<br>In Brazil, common bean (Phaseolus vulgaris L.) is cultivated in a range of ecologically differentiated environments. For being a culture highly influenced by the environment variation, its average productivity in the Country is unstable and low. An origin of this variation of productivity is the genotype x environment interaction, which has been one of the largest impediments for o

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8

Sartorio, Simone Daniela. "Aplicações de técnicas de análise multivariada em experimentos agropecuários usando o software R." Universidade de São Paulo, 2008. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-06082008-172655/.

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O uso das técnicas de análise multivariada está reservado aos grandes centros de pesquisa, µas grandes empresas e ao ambiente acad^emico. Essas técnicas s~ao muito interessantes porque utilizam simultaneamente todas as variáveis respostas na interpretação teórica do conjunto de dados, levando em conta as correlações existentes entre elas. Uma das principais barreiras para a utilização dessas técnicas é o seu desconhecimento pelos pesquisadores interessados na pesquisa quantitativa. A outra dificuldade é que a grande maioria de softwares que permitem esse tipo de análise (SAS, MINITAB, BMDP, ST

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9

Dimitrakopoulou, Vasiliki. "Bayesian variable selection in cluster analysis." Thesis, University of Kent, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.594195.

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Statistical analysis of data sets of high-dimensionality has met great interest over the past years, with great applications on disciplines such as medicine, nellascience, pattern recognition, image analysis and many others. The vast number of available variables though, contrary to the limited sample size, often mask the cluster structure of the data. It is often that some variables do not help in distinguishing the different clusters in the data; patterns over the samp•.l ed observations are, thus, usually confined to a small subset of variables. We are therefore interested in identifying th

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10

Rastelli, Riccardo, and Nial Friel. "Optimal Bayesian estimators for latent variable cluster models." Springer Nature, 2018. http://dx.doi.org/10.1007/s11222-017-9786-y.

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In cluster analysis interest lies in probabilistically capturing partitions of individuals, items or observations into groups, such that those belonging to the same group share similar attributes or relational profiles. Bayesian posterior samples for the latent allocation variables can be effectively obtained in a wide range of clustering models, including finite mixtures, infinite mixtures, hidden Markov models and block models for networks. However, due to the categorical nature of the clustering variables and the lack of scalable algorithms, summary tools that can interpret such samples ar

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