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mscnvrsy
  • Member for 8 years, 5 months
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Parameterization of Gamma Distribution
Okay, thank you very much! Astonishingly, I found another paper with the exact same typo but from 2008.
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Parameterization of Gamma Distribution
I added a screenshot for clarification.
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Parameterization of Gamma Distribution
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Parameterization of Gamma Distribution
Sure, for instance: Jumps in Equity Index Returns Before and During the Recent Financial Crisis: A Bayesian Analysis (2016, by Kou, Yu and Zhong) on p. 5 in the footnote
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RW Metropolis and ARMS fail
I put a more detailed model description and information on the proposal distribution.
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RW Metropolis and ARMS fail
State-space model and parameter distributions, clarification of proposal distribution
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Truncated Normal distribution: Theoretical mean outside truncation boundaries
I'm rather trying to sample from $x \sim N(-8.0;0.2)1_{x\geq0}$. But I guess your reasoning still holds?
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Sampling from an Inverse Gamma distribution
But how can I infer whether they provide $\theta$ or $\beta$ just from the expression $X \sim IG(m,M)$ with neither the $(\alpha,\beta)$ nor the $(k,\theta)$ specification, nor the formula for the pdf? I think we're talking past each other right now
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Sampling from an Inverse Gamma distribution
But from $IG(m,M)$ it's not that obvious, is it? Anyway, thank you very much (again)! I've been dealing with that issue for 3 weeks now... Finally, it's solved.
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Sampling from an Inverse Gamma distribution
I have two papers in front of me, where one indeed specifies the parameters of the inverse gamma as $\alpha$ and $\beta$. In the other paper they are named m and M instead. So, I assume there is no way to find out the terminology used by the authors by just looking at the expression $X \sim IG(p_1, p_2)$? Cause they neither call the latter parameter scale nor rate. Thank you!
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