000 | 02441nam a22003738i 4500 | ||
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001 | CR9781108604574 | ||
003 | UkCbUP | ||
005 | 20240920190058.0 | ||
006 | m|||||o||d|||||||| | ||
007 | cr|||||||||||| | ||
008 | 180411s2019||||enk o ||1 0|eng|d | ||
020 | _a9781108604574 (ebook) | ||
020 | _z9781108476591 (hardback) | ||
020 | _z9781108701112 (paperback) | ||
040 |
_aUkCbUP _beng _erda _cUkCbUP |
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050 | 0 | 0 |
_aQA276.7 _b.S86 2019 |
082 | 0 | 0 |
_a519.5 _223 |
100 | 1 |
_aSundberg, Rolf, _d1942- _eauthor. |
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245 | 1 | 0 |
_aStatistical modelling by exponential families / _cRolf Sundberg. |
264 | 1 |
_aCambridge : _bCambridge University Press, _c2019. |
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300 |
_a1 online resource (xiv, 282 pages) : _bdigital, PDF file(s). |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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490 | 1 |
_aInstitute of Mathematical Statistics textbooks ; _v12 |
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500 | _aTitle from publisher's bibliographic system (viewed on 17 Jul 2019). | ||
520 | _aThis book is a readable, digestible introduction to exponential families, encompassing statistical models based on the most useful distributions in statistical theory, including the normal, gamma, binomial, Poisson, and negative binomial. Strongly motivated by applications, it presents the essential theory and then demonstrates the theory's practical potential by connecting it with developments in areas like item response analysis, social network models, conditional independence and latent variable structures, and point process models. Extensions to incomplete data models and generalized linear models are also included. In addition, the author gives a concise account of the philosophy of Per Martin-Löf in order to connect statistical modelling with ideas in statistical physics, including Boltzmann's law. Written for graduate students and researchers with a background in basic statistical inference, the book includes a vast set of examples demonstrating models for applications and exercises embedded within the text as well as at the ends of chapters. | ||
650 | 0 |
_aExponential families (Statistics) _vProblems, exercises, etc. |
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650 | 0 |
_aDistribution (Probability theory) _vProblems, exercises, etc. |
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776 | 0 | 8 |
_iPrint version: _z9781108476591 |
830 | 0 |
_aInstitute of Mathematical Statistics textbooks ; _v12. |
|
856 | 4 | 0 | _uhttps://doi.org/10.1017/9781108604574 |
942 |
_2ddc _cEB |
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999 |
_c9844 _d9844 |