Download or read book Appunti delle lezioni di inferenza statistica e campionamento written by Mario Badaloni and published by . This book was released on 2004 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Appunti delle lezioni di inferenza statistica written by Mario Badaloni and published by . This book was released on 2003 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Appunti delle lezioni del Corso di teoria dell inferenza statistica written by Mario Badaloni and published by . This book was released on 1997 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Appunti sull inferenza statistica written by and published by . This book was released on 1996 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Modelli di misurazione e casualit written by Angelo Zanella and published by EDUCatt - Ente per il diritto allo studio universitario dell'Università Cattolica. This book was released on 2008-01-01 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Appunti delle lezioni di statistica 2 written by Angelo Zanella and published by . This book was released on 1999 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Appunti delle lezioni di statistica written by Giuseppe Toniolo and published by . This book was released on 1902 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Appunti di teoria dei campioni written by Lorenzo Fattorini and published by . This book was released on 1976 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Appunti delle lezioni di statistica descrittiva written by Universita degli studi (Bologna). Facolta di scienze politiche and published by . This book was released on 1973 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Elementi di inferenza statistica e di tecniche di campionamento written by Nunziata Ribecco and published by . This book was released on 1984 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Lezioni di statistica written by and published by . This book was released on 2004 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Appunti di inferenza statistica per le scienze sociali written by Emanuela Furfaro (omonimi non identificati) and published by . This book was released on 2018 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Appunti per 10 lezioni di statistica matematica written by Ludovico Piccinato and published by . This book was released on 1969 with total page 83 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Principles of Copula Theory written by Fabrizio Durante and published by CRC Press. This book was released on 2015-07-01 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives readers the solid and formal mathematical background to apply copulas to a range of mathematical areas, such as probability, real analysis, measure theory, and algebraic structures. The authors prove the results as simply as possible and unify various methods scattered throughout the literature in common frameworks, including shuffles of copulas. They also explore connections with related functions, such as quasi-copulas, semi-copulas, and triangular norms, that have been used in different domains.

Download or read book Dependence Modeling written by Harry Joe and published by World Scientific. This book was released on 2011 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: 1. Introduction : Dependence modeling / D. Kurowicka -- 2. Multivariate copulae / M. Fischer -- 3. Vines arise / R.M. Cooke, H. Joe and K. Aas -- 4. Sampling count variables with specified Pearson correlation : A comparison between a naive and a C-vine sampling approach / V. Erhardt and C. Czado -- 5. Micro correlations and tail dependence / R.M. Cooke, C. Kousky and H. Joe -- 6. The Copula information criterion and Its implications for the maximum pseudo-likelihood estimator / S. Gronneberg -- 7. Dependence comparisons of vine copulae with four or more variables / H. Joe -- 8. Tail dependence in vine copulae / H. Joe -- 9. Counting vines / O. Morales-Napoles -- 10. Regular vines : Generation algorithm and number of equivalence classes / H. Joe, R.M. Cooke and D. Kurowicka -- 11. Optimal truncation of vines / D. Kurowicka -- 12. Bayesian inference for D-vines : Estimation and model selection / C. Czado and A. Min -- 13. Analysis of Australian electricity loads using joint Bayesian inference of D-vines with autoregressive margins / C. Czado, F. Gartner and A. Min -- 14. Non-parametric Bayesian belief nets versus vines / A. Hanea -- 15. Modeling dependence between financial returns using pair-copula constructions / K. Aas and D. Berg -- 16. Dynamic D-vine model / A. Heinen and A. Valdesogo -- 17. Summary and future directions / D. Kurowicka

Download or read book Mathematical Modeling in Economics and Finance Probability Stochastic Processes and Differential Equations written by Steven R. Dunbar and published by American Mathematical Soc.. This book was released on 2019-04-03 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical Modeling in Economics and Finance is designed as a textbook for an upper-division course on modeling in the economic sciences. The emphasis throughout is on the modeling process including post-modeling analysis and criticism. It is a textbook on modeling that happens to focus on financial instruments for the management of economic risk. The book combines a study of mathematical modeling with exposure to the tools of probability theory, difference and differential equations, numerical simulation, data analysis, and mathematical analysis. Students taking a course from Mathematical Modeling in Economics and Finance will come to understand some basic stochastic processes and the solutions to stochastic differential equations. They will understand how to use those tools to model the management of financial risk. They will gain a deep appreciation for the modeling process and learn methods of testing and evaluation driven by data. The reader of this book will be successfully positioned for an entry-level position in the financial services industry or for beginning graduate study in finance, economics, or actuarial science. The exposition in Mathematical Modeling in Economics and Finance is crystal clear and very student-friendly. The many exercises are extremely well designed. Steven Dunbar is Professor Emeritus of Mathematics at the University of Nebraska and he has won both university-wide and MAA prizes for extraordinary teaching. Dunbar served as Director of the MAA's American Mathematics Competitions from 2004 until 2015. His ability to communicate mathematics is on full display in this approachable, innovative text.

Download or read book Hands On Machine Learning with R written by Brad Boehmke and published by CRC Press. This book was released on 2019-11-07 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today’s most popular machine learning methods. This book serves as a practitioner’s guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to effectively model and gain insight from their data. The book favors a hands-on approach, providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory. Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a hands-on approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R’s machine learning stack and be able to implement a systematic approach for producing high quality modeling results. Features: · Offers a practical and applied introduction to the most popular machine learning methods. · Topics covered include feature engineering, resampling, deep learning and more. · Uses a hands-on approach and real world data.