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I am taking inverse chi square as my prior distribution for variance of normal sampling distribution. I am little confuse about the choice of value for V0 the parameter of inverse chi prior, that is df and it usually n-1 for one parameter case. If i have n=10 and i choose V0 as 9 it is a reasonable choice for this hyper parameter?

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No. That would make the data and the prior equally strong (10 observations strong).

I would recommend using inverse gamma instead.

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  • $\begingroup$ Thanks for your suggestion.... But than i have to choose the possible hyper parameter values for IG... Can you recommend me how i can choose these values, if i don't use prior predictive distribution. $\endgroup$ – Tahir Malik Jan 4 '15 at 11:26
  • $\begingroup$ You should use IG(a,b) - match mean and variance to what you want to figure out a and b, see en.wikipedia.org/wiki/Inverse-gamma_distribution $\endgroup$ – TA72 Jan 4 '15 at 17:32

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