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|a UAMI
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|a Probabilistic Inference and Statistical Methods in Network Analysis.
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|a Ashland :
|b Arcler Press,
|c 2019.
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|a 1 online resource (501 pages)
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|b txt
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|a Cover; Half Title Page; Title Page; Copyright Page; Declaration; About the Editor; Table of Contents; List of Contributors; List of Abbreviations; Preface; SECTION I: SOCIAL NETWORKS; Chapter 1 Using Social Network Analysis of Human Aspects For Online Social Network Software: A Design Methodology; Abstract; Introduction; Failure and Timeline of Online Social Network Sites; Proposed Design Methodology; Results and Discussion; Conclusion; References; Chapter 2 A Social Network Analysis on Clinical Education of Diabetic Foot; Abstract; Introduction; Methods; Results; Discussion; Acknowledgement
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|a Authors' ContributionsReferences; Chapter 3 Rational Erdös Number And Maximum Flow as Measurement Models For Scientific Social Network Analysis; Abstract; Introduction; Scientific Social Networks and Information Diffusion; Measurement Models To Define Tie Weight; Case Study; Final Remarks; Authors' Contributions; References; Chapter 4 Identifying Network Public Opinion Leaders Based on Markov Logic Networks; Abstract; Introduction; Markov Logic Networks; System Framework; Experimental Verification; Conclusions; Acknowledgments; References
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|a Chapter 5 Constructing, Conducting and Interpreting Animal Social Network AnalysisSummary; Introduction; Overview Of Network Analysis; Defining Network Edges; Data Collection Methods; Inferring Associations From Data; Displaying Social Structures; Interpreting Network Metrics; Constructing Null Models; Hypothesis Testing In Animal Social Networks; Estimating Power and Precision; Remaining Challenges and Future Directions; Conclusion; Acknowledgements; References; SECTION II NEURAL NETWORKS
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|a Chapter 6 Connectivity Inference From Neural Recording Data: Challenges, Mathematical Bases And Research DirectionsAbstract; Introduction; Data Processing Pipeline; Challenges; Model-Free Methods; Model-Based Methods; Case Study; Discussion; Conclusion; Acknowledgments; References; Chapter 7 Generative Models For Network Neuroscience: Prospects and Promise; Abstract; Introduction; Generative Models: A Primer; Generative Models of Biological Neural Networks; A Few Relevant Distinctions; Future Directions; Conclusion; Acknowledgements; References
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|a SECTION III GENE REGULATORY NETWORKS AND BIOLOGICAL SYSTEMSChapter 8 Inferring Regulatory Networks From Expression Data Using Tree-Based Methods; Abstract; Introduction; Methods; Results; Discussion; Author Contributions; References; Chapter 9 Hybrid-Controlled Neurofuzzy Networks Analysis Resulting In Genetic Regulatory Networks Reconstruction; Abstract; Introduction; Algorithm; Results; Discussion; Conclusions; References; SECTION IV BAYESIAN NETWORKS; Chapter 10 Bayesian Networks Analysis of Malocclusion Data; Abstract; Introduction; Methods; Results; Adjusted Data; Discussion
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| 500 |
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|a Acknowledgements
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| 590 |
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|a eBooks on EBSCOhost
|b EBSCO eBook Subscription Academic Collection - Worldwide
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| 650 |
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|a System analysis
|x Statistical methods.
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| 650 |
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|a Social sciences
|x Network analysis.
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| 650 |
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|a Analyse de systèmes
|x Méthodes statistiques.
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| 650 |
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|a Sciences sociales
|x Analyse de réseau.
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| 650 |
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|a Social sciences
|x Network analysis
|2 fast
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| 650 |
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| 700 |
1 |
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|a Moreira, Olga.
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|i Print version:
|a Moreira, Olga.
|t Probabilistic Inference and Statistical Methods in Network Analysis.
|d Ashland : Arcler Press, ©2019
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| 856 |
4 |
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