Find the posterior distribution when

$$x|\sigma\sim \mathcal N(0,\sigma^2),\:\:\: 1/\sigma^2\sim \mathsf{Gamma}(1,2)$$

I'm stuck in this exercise, I know that $$\pi(x|\sigma)\approx f(x|\sigma)\pi(\sigma)\cdot\frac{1}{m(x)}$$

Maybe I am thinking wrong, but I would not have to find a prior of $\sigma$?

  • $\begingroup$ Is that the quotient of $x, \sigma$, or $x$ given $\sigma$? $\endgroup$ Mar 10, 2016 at 19:19
  • $\begingroup$ @SeanEaster the pdf is given and the other is $\frac{1}{\sigma^2}$ $\endgroup$
    – user72621
    Mar 10, 2016 at 19:20
  • 1
    $\begingroup$ Please add the [self-study] tag & read its wiki. $\endgroup$ Mar 10, 2016 at 21:49
  • $\begingroup$ @amoeba, I believe I voted to close as SS, although I don't really remember anymore. You can vote to reopen if you like. $\endgroup$ Mar 17, 2016 at 20:31
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    $\begingroup$ Could you explain what the symbols "$m$", "$f$", and "$\pi$" mean to you? $\endgroup$
    – whuber
    Mar 28, 2016 at 14:51

1 Answer 1


In effect, you know the prior on $\sigma^2$: It's inverse gamma. After expressing the posterior as the product of normal likelihood and inverse-gamma prior, one can manipulate the posterior until it's recognizable as another inverse gamma. (Left as an exercise, but confirmed in Michael I. Jordan - The Conjugate Prior for the Normal Distribution)


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