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Normal mean-precision Gibbs sampler
...
Area of mathematics
Probability and statistics
Statistical inference
Bayesian statistics
Markov chain Monte Carlo
Gibbs sampler
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Words: 43
For independent
Z
i
∣
μ
,
ω
∼
N
(
μ
,
ω
−
1
)
, a flat prior on
μ
, and an exponential prior of rate
λ
on
ω
, the full conditionals are
μ
∣
ω
,
z
∼
N
(
z
ˉ
,
nω
1
)
,
(240)
and
ω
∣
μ
,
z
∼
Gamma
(
2
n
+
1
,
λ
+
2
1
∑
i
(
z
i
−
μ
)
2
)
,
(241)
where the gamma distribution is parametrized by shape and rate.
Ancestors
(8)
Gibbs sampler
Markov chain Monte Carlo
Bayesian statistics
Statistical inference
Probability and statistics
Area of mathematics
Mathematics
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