03557nam a22005415i 4500 978-3-031-55855-9 DE-He213 20251030114620.0 cr nn 008mamaa 241216s2024 sz | s |||| 0|eng d 9783031558559 978-3-031-55855-9 10.1007/978-3-031-55855-9 doi QA276-280 PBT bicssc MAT029000 bisacsh PBT thema Rudas, Tamás. author. aut http://id.loc.gov/vocabulary/relators/aut 88987 Lectures on Advanced Topics in Categorical Data Analysis [electronic resource] / by Tamás Rudas. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. XII, 377 p. 29 illus., 4 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Springer Texts in Statistics, 2197-4136 1. Introduction -- 2. Undirected graphical models -- 3. Directed graphical models -- 4. Marginal models: definition -- 5. Marginal log-linear models: applications -- 6. Path models -- 7. Relational models: definition and interpretation -- 8. Relational models as exponential families -- 9. Relational models: estimation and testing -- 10. Model testing -- 11. The mixture index of fit. This book continues the mission of the previous text by the author, Lectures on Categorical Data Analysis, by expanding on the introductory concepts from that volume and providing a mathematically rigorous presentation of advanced topics and current research in statistical techniques which can be applied in the social, political, behavioral, and life sciences. It presents an intuitive and unified discussion of an array of themes in categorical data analysis, and the emphasis on structure over stochastics renders many of the methods applicable in machine learning environments and for the analysis of big data. The book focuses on graphical models, their application in causal analysis, the analytical properties of parameterizations of multivariate discrete distributions, marginal models, and coordinate-free relational models. To guide the readers in future research, the volume provides references to original papers and also offers detailed proofs of most of the significant results. Like the previous volume, it features exercises and research questions, making it appropriate for graduate students, as well as for active researchers. Statistics. 65982 Social sciences Statistical methods. 75236 Biometry. 65981 Statistical Theory and Methods. Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy. 75237 Biostatistics. 65985 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031558542 Printed edition: 9783031558566 Printed edition: 9783031558573 Springer Texts in Statistics, 2197-4136 72551 https://doi.org/10.1007/978-3-031-55855-9 ZDB-2-SMA ZDB-2-SXMS 65741 65741