[R-sig-ME] MCMCglmm error

[Walid Crampton-Mawass]

Definitely a better assumption.

Thank you again.

Walid

On Wed, Mar 20, 2019, 4:05 PM HADFIELD Jarrod <j.hadfield using ed.ac.uk> wrote:

> Hi,
>
> Yes. You make assumptions in doing this - that the individuals with
> unknown mothers aren’t really maternal siblings - but better than assuming
> they were virgin births.
>
> Cheers,
>
> Jarrod
>
> On 20 Mar 2019, at 19:58, Walid Crampton-Mawass <walidmawass10 using gmail.com>
> wrote:
>
> Thank you Jarrod for your reply!
>
> If I understand correctly then, to stop this error I should just give a
> dummy maternal id for the individuals with missing id.
>
> Thank you again for your help
>
> Walid Mawass
>
>
>
>
>
>
> On Wed, Mar 20, 2019, 3:34 PM HADFIELD Jarrod <j.hadfield using ed.ac.uk> wrote:
>
>> Hi,
>>
>> MCMCglmm used to issue a warning if there were NA’s in the random effect
>> predictors. However, people seemed to ignore it when it was inappropriate.
>> The only case I can think of where it should be ignored is in a multi
>> membership model where the number of members varies over observations,
>> which is probably a rare type of model. Consequently, I now just stop
>> people doing what I *think*they didn’t intend. It may be the case that you
>> don’t know who the mother is, but that doesn’t mean they don’t have a
>> mother. Fitting a dummy maternal id is the standard solution.
>>
>> A more informative error message will be in the next release.
>>
>> Cheers,
>>
>> Jarrod
>>
>> > On 20 Mar 2019, at 19:01, Walid Crampton-Mawass <
>> walidmawass10 using gmail.com> wrote:
>> >
>> > Hello everyone,
>> >
>> > I started getting this error when I run an animal model with a maternal
>> > random effect using MCMCglmm. here is my code:
>> >
>> > *prior1 <- list(R=list(V=1, nu=0.002), G=list(G1=list(V=1,
>> > nu=0.002),G2=list(V=1, nu=0.002)))*
>> >
>> > *model_afr_3_1 <- MCMCglmm(AFR~
>> > 1+OffMortality+COEFPAR+I(COEFPAR*COEFPAR)+TWIN+BIRTHYW+mortrate1 ,
>> random =
>> > ~animal + MOTHERW, rcov = ~units, data = IAC, pedigree = prunedPed,
>> family
>> > = "gaussian" , nitt = 3500000, burnin = 500000, thin = 3000, prior =
>> > prior1, verbose = FALSE, pr=TRUE)*
>> > *Error in t(ZZ[[k]]) : invalid object passed to as_cholmod_sparse*
>> > *Calls: MCMCglmm -> buildZ -> t -> t*
>> >
>> > I was able to find out that the variable causing the error is the second
>> > random term "MOTHERW" which represents the id of each individual's
>> mother
>> > as to model maternal variation. However I started getting this error
>> > recently even though it used to work beforehand without any errors. The
>> > variable is set as a multi-level factor just as is done to the "animal"
>> > variable. But there are a few missing values for some individuals (20
>> out
>> > of 572)
>> >
>> > *str(dat$MOTHERW)*
>> > * Factor w/ 297 levels "100007","100032",..: 114 142 207 12 258 168 261
>> 230
>> > 179 107 ...*
>> >
>> > I tried another variable, FATHERW, which is the id of the father of the
>> > individual. I get the same error again : *Error in t(ZZ[[k]]) : invalid
>> > object passed to as_cholmod_sparse*
>> >
>> > However, when using another variable in my data as a random variable
>> > instead, BIRTHYW (birth year of individual; set as a factor), the model
>> > runs without any errors. The only difference is that there are no
>> missing
>> > values in this variable compared MOTHERW  and FATHERW.
>> >
>> > is it probably the case that we can't use a variable with a few missing
>> > values as a random variable in MCMCglmm anymore?
>> >
>> > Thanks for any help!
>> > --
>> > Walid Mawass
>> > Ph.D. candidate in Cellular and Molecular Biology
>> > Population Genetics Laboratory
>> > University of Québec at Trois-Rivières
>> > 3351, boul. des Forges, C.P. 500
>> > Trois-Rivières (Québec) G9A 5H7
>> > Telephone: 819-376-5011 poste 3384
>> >
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>> >
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>>
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>>
>
>

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