Tafsiri ya Laplace
Tafsiri ya Laplace ni mbinu ya kawaida ya uchanganuzi ambayo inachukua nafasi ya usambazaji wa nyuma usioweza kutatuliwa na Gaussiani yenye vigezo vingi iliyo katikati kwenye modi ya nyuma, ikitumia mkunjo wa log-posterior kwenye modi hiyo kuweka kofaktori. Imeandaliwa rasmi kwa takwimu za Bayesian na Tierney na Kadane (1986) katika karatasi yao muhimu ya Journal of the American Statistical Association, inatoa mbadala wa haraka, wa uhakika kwa Msururu wa Monte Carlo na huunda msingi wa hisabati wa Tafsiri za Laplace zilizojumuishwa (INLA).
Soma mbinu kamili
Ingia kwa akaunti ya bure ili kusoma sehemu hii.
Method map
The neighbourhood of related methods — select a node to explore.
Vyanzo
- Tierney, L. & Kadane, J. B. (1986). Accurate approximations for posterior moments and marginal densities. Journal of the American Statistical Association, 81(393), 82–86. DOI: 10.1080/01621459.1986.10478240 ↗
- MacKay, D. J. C. (2003). Information Theory, Inference, and Learning Algorithms. Cambridge University Press. ISBN: 978-0521642989
- Rue, H., Martino, S. & Chopin, N. (2009). Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations. Journal of the Royal Statistical Society: Series B, 71(2), 319–392. DOI: 10.1111/j.1467-9868.2008.00700.x ↗
Jinsi ya kunukuu ukurasa huu
ScholarGate. (2026, June 3). Laplace Approximation to the Posterior. ScholarGate. https://scholargate.app/sw/bayesian/laplace-approximation
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Usajili wa BayesianMbinu za Bayes↔ compare
- Uenezi wa Matarajio (EP)Mbinu za Bayes↔ compare
- Markov Chain Monte Carlo (MCMC)Mbinu za Bayes↔ compare
Imerejelewa na
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