| 000 | 01537nam a22002657a 4500 | ||
|---|---|---|---|
| 003 | EG-NbEJU | ||
| 005 | 20241127231604.0 | ||
| 008 | 240718t2015 enka gr 001 0 eng d | ||
| 020 | _a9781118326558 | ||
| 040 |
_aEG-NbEJU _beng _cEG-NbEJU _dEG-NbEJU |
||
| 041 | _aeng | ||
| 050 | 0 | 0 |
_aQA279.5 _bB53 2015 |
| 100 | 1 | _aBlangiardo , Marta | |
| 245 | 1 | 0 |
_aSpatial and Spatio-temporal Bayesian Models with R - INLA / _cMarta Blangiardo , Michela Cameletti |
| 260 |
_aChichester : _bJohn Wiley & Sons, Ltd , _c2015 |
||
| 300 |
_a308 Pages : _bIllustrations ; _c24 cm |
||
| 520 | _aSpatial and Spatio-Temporal Bayesian Models with R-INLA provides a much needed, practically oriented & innovative presentation of the combination of Bayesian methodology and spatial statistics. The authors combine an introduction to Bayesian theory and methodology with a focus on the spatial and spatio-temporal models used within the Bayesian framework and a series of practical examples which allow the reader to link the statistical theory presented to real data problems. The numerous examples from the fields of epidemiology, biostatistics and social science all are coded in the R package R-INLA, which has proven to be a valid alternative to the commonly used Markov Chain Monte Carlo simulations | ||
| 650 | 0 | _aBayesian statistical decision theory | |
| 650 | 0 | _aSpatial analysis (Statistics) | |
| 700 | 1 |
_aCameletti , Michela _eCo-author |
|
| 901 | _aنورهان | ||
| 902 | _aENG_03_ (356) | ||
| 902 | _aENG_03_(999) | ||
| 942 |
_2lcc _cBK |
||
| 999 |
_c2814 _d2814 |
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