Bernstein–von Mises theorem
theorem that the posterior converges in the infinite-data limit 𝑁≫1 to a multivariate normal distribution centred at the maximum likelihood estimator with covariance 𝑁⁻¹𝐼(𝜃₀)⁻¹ with 𝜃₀ the true population parameter and 𝐼(𝜃₀) the Fisher information
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Bernstein–von Mises theorem
Summary
Bernstein–von Mises theorem is a theorem[1]. It draws 33 Wikipedia views per month (theorem category, ranking #244 of 1,306).[2]
Key Facts
- Bernstein–von Mises theorem's instance of is recorded as theorem[3].
- Richard von Mises is named after Bernstein–von Mises theorem[4].
- Sergei Natanovich Bernstein is named after Bernstein–von Mises theorem[5].
- Bernstein–von Mises theorem's Freebase ID is recorded as /m/0gyts5j[6].
- Bernstein–von Mises theorem's facet of is recorded as Bayesian statistics[7].
- Bernstein–von Mises theorem's proved by is recorded as Joseph Leo Doob[8].
- Bernstein–von Mises theorem's proved by is recorded as Lucien Le Cam[9].
- Bernstein–von Mises theorem's proved by is recorded as Lorraine Schwartz[10].
- Bernstein–von Mises theorem's proved by is recorded as David A. Freedman[11].
- Bernstein–von Mises theorem's proved by is recorded as Persi Diaconis[12].
- Bernstein–von Mises theorem's defining formula is recorded as P(\theta|x_1,\dots x_n)= \mathcal{N}(\theta_0, n^{-1}I(\theta_0)^{-1}) \text{ for } n\to \infty[13].
- Bernstein–von Mises theorem's maintained by WikiProject is recorded as WikiProject Mathematics[14].
- Bernstein–von Mises theorem's Microsoft Academic ID is recorded as 168408371[15].
- Bernstein–von Mises theorem's in defining formula is recorded as P[16].
- Bernstein–von Mises theorem's in defining formula is recorded as \mathcal{N}[17].
- Bernstein–von Mises theorem's in defining formula is recorded as n[18].
- Bernstein–von Mises theorem's in defining formula is recorded as I[19].
Why It Matters
Bernstein–von Mises theorem draws 33 Wikipedia views per month (theorem category, ranking #244 of 1,306).[2]