[R-sig-ME] pMCMC and HPD in MCMCglmm

[Jarrod Hadfield]

Hi Massimo,

They only need to be slightly skewed (even up to Monte Carlo error  
probably) - conclusions drawn from HPDinterval and pMCMC are in  
reality almost identical in your example, it is the consequences  of  
the (arbitrary) distinction between <0.05 and >0.05  that makes them  
"feel" different.  Lets say we used the cutoff <0.06 and >0.06.  Does  
HPDinterval(m1$Sol[,3], prob=0.94) overlap zero? If not then  
HPDinterval and pMCMC "agree" with respect to which side of the cutoff  
the probability lies ? It may make us happier, but it shouldn't.

Jarrod




On 24 Aug 2011, at 11:45, m.fenati at libero.it wrote:

> The posterior distribution seem to be only slightly skewed.
> However the question remains: what is the sense of the discrepancy  
> between HPD
> and pMCMC?
>
> Thanks
>
> Massimo
>
>
>
> ----Messaggio originale----
> Da: ndjido at gmail.com
> Data: 24/08/2011 11.43
> A: "m.fenati at libero.it"<m.fenati at libero.it>
> Cc: <r-sig-mixed-models at r-project.org>
> Ogg: Re: [R-sig-ME] pMCMC and HPD in MCMCglmm
>
> Check your posterior distributions, the one corresponding to GENDER  
> seems to
> be skewed.
> Ardo.
> On Wed, Aug 24, 2011 at 11:33 AM, m.fenati at libero.it <m.fenati at libero.it 
> >
> wrote:
> As suggested by Ben Bolker, I re-post the following question in this  
> list.
> Thanks
>
>> Dear R users,
>> I’d like to pose aquestion about pMCMC and HDP.
>> I have performed a mixed logistic regression by MCMCglmm (a very good
> package)
>> obtaining the following results:
>>
>> Iterations = 250001:799901
>> Thinning interval = 100
>> Sample size = 5500
>>
>> DIC: 10.17416
>>
>> G-structure: ~ID_an
>>
>> post.mean l-95% CI u-95% CIeff.samp
>> ID_an 0.7023 0.0001367 3.678 2126
>>
>> R-structure: ~units
>>
>> post.mean l-95% CIu-95% CI eff.samp
>> units 1 1 1 0
>>
>> Location effects: febbreq~ as.factor(sex)
>>
>> post.mean l-95% CIu-95% CI eff.samp pMCMC
>> (Intercept) -3.6332 -5.6136 -1.7719 3045 <2e-04 ***
>> as.factor(sex)M -2.9959 -6.0690 0.1969 2628 0.0455 *
>> ---
>> Signif. codes: 0 ‘***’0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
>>
>>
>> As you can see, pMCMC for gender is just less than 5%, but the  
>> credible
>> interval (HPD) is wide and includes the 0 value.
>> How can I interpret these different results?
>>
>> Thank you in advance
>>
>> Massimo
>>
>> -----------------------
>> Massimo Fenati
>> DVM
>> Padova - Italy
>
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