Model Averaging
Mentés helye:
| Szerző: | |
|---|---|
| Testületi szerző: | |
| Különgyűjtemény: | e-book |
| Formátum: | könyv |
| Nyelv: | angol |
| Megjelenés: |
Berlin, Heidelberg : : Springer Berlin Heidelberg : : Imprint: Springer,,
2018
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| Kiadás: | 1st ed. 2018. |
| Sorozat: | SpringerBriefs in Statistics,, ISSN 2191-544X |
| Tárgyszavak: | |
| Online elérés: | https://doi.org/10.1007/978-3-662-58541-2 |
| Címkék: |
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| 100 | 1 | |a Fletcher, David. |e szerző |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Model Averaging |c by David Fletcher. |
| 250 | |a 1st ed. 2018. | ||
| 260 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg : |b Imprint: Springer, |c 2018 | ||
| 300 | |a X, 107 p. 4 illus. |b online forrás | ||
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| 347 | |a szövegfájl |b PDF |2 rda | ||
| 490 | 1 | |a SpringerBriefs in Statistics, |x 2191-544X | |
| 505 | 0 | |a Why Model Averaging? -- Bayesian Model Averaging -- Frequentist Model Averaging -- Summary and Future Directions. | |
| 520 | |a This book provides a concise and accessible overview of model averaging, with a focus on applications. Model averaging is a common means of allowing for model uncertainty when analysing data, and has been used in a wide range of application areas, such as ecology, econometrics, meteorology and pharmacology. The book presents an overview of the methods developed in this area, illustrating many of them with examples from the life sciences involving real-world data. It also includes an extensive list of references and suggestions for further research. Further, it clearly demonstrates the links between the methods developed in statistics, econometrics and machine learning, as well as the connection between the Bayesian and frequentist approaches to model averaging. The book appeals to statisticians and scientists interested in what methods are available, how they differ and what is known about their properties. It is assumed that readers are familiar with the basic concepts of statistical theory and modelling, including probability, likelihood and generalized linear models. | ||
| 580 | |a Nyomtatott kiadás: ISBN 9783662585405 | ||
| 580 | |a Nyomtatott kiadás: ISBN 9783662585429 | ||
| 506 | |a Az e-könyvek a teljes ELTE IP-tartományon belül online elérhetők. | ||
| 598 | |a könyv | ||
| 595 | |a e-book | ||
| 650 | 0 | |a Mathematical statistics. | |
| 650 | 0 | |a Ecology. | |
| 650 | 0 | |a Statistical methods. | |
| 650 | 0 | |a Statistics. | |
| 650 | 1 | 4 | |a Statistical Theory and Methods. |
| 650 | 2 | 4 | |a Theoretical Ecology/Statistics. |
| 650 | 2 | 4 | |a Biostatistics. |
| 650 | 2 | 4 | |a Statistics for Business, Management, Economics, Finance, Insurance. |
| 650 | 2 | 4 | |a Statistics for Life Sciences, Medicine, Health Sciences. |
| 653 | |a elektronikus könyv | ||
| 710 | 2 | |a SpringerLink (Online service) |e közreadó testület | |
| 830 | 0 | |a SpringerBriefs in Statistics, |x 2191-544X | |
| 856 | 4 | 0 | |y Online változat |u https://doi.org/10.1007/978-3-662-58541-2 |
| 850 | |a B2 | ||
| 264 | 1 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg : |b Imprint: Springer, |c 2018 | |