Fantastic, thank you. Yes, diversitree works well for my data. I fit a
3-state model, comparing symmetric vs. asymmetric rates and found that the
asymmetric rates model was the best fit. The marginal likelihood node
reconstructions make more sense than did the results from ace.

Thank you for your help!

On Mon, Dec 5, 2016 at 10:52 AM, Liam J. Revell <liam.rev...@umb.edu> wrote:

> Hi Katharine.
>
> You can also do ancestral state estimation for the model "ARD" using the
> packages diversitree. There is a worked example on my blog here:
> https://urldefense.proofpoint.com/v2/url?u=http-3A__blog.phy
> tools.org_2016_09_possible-2Dbug-2Din-2Dacemodelard-2Dand-
> 2Dother.html&d=CwIC-g&c=-dg2m7zWuuDZ0MUcV7Sdqw&r=xoGnL4
> 0RVzN6D2MIG8KmZ26dy3o8eec0rBKUtCA6gh4&m=rIQpuCeVkjAvCCk1mmLY
> Le-xQKuhvk1LA_V4YQ1hglQ&s=uHgZqwdDk6rAgVazzwKjjUdTrk7gGJbR0agrKcCaSag&e=
> (also highlighting a possible bug in ace for model="ARD" & other
> non-reversible models). Let us know if this helps.
>
> All the best, Liam
>
> Liam J. Revell, Associate Professor of Biology
> University of Massachusetts Boston
> web: https://urldefense.proofpoint.com/v2/url?u=http-3A__faculty.
> umb.edu_liam.revell_&d=CwIC-g&c=-dg2m7zWuuDZ0MUcV7Sdqw&r=xoG
> nL40RVzN6D2MIG8KmZ26dy3o8eec0rBKUtCA6gh4&m=rIQpuCeVkjAvCCk1m
> mLYLe-xQKuhvk1LA_V4YQ1hglQ&s=1xd3YzpUZ_dGrHVJ0c_UnTkz3T1Koxf
> racHjlH7_8Os&e= email: liam.rev...@umb.edu
> blog: https://urldefense.proofpoint.com/v2/url?u=http-3A__blog.phy
> tools.org&d=CwIC-g&c=-dg2m7zWuuDZ0MUcV7Sdqw&r=xoGnL40RVzN6D2
> MIG8KmZ26dy3o8eec0rBKUtCA6gh4&m=rIQpuCeVkjAvCCk1mmLYLe-xQKuh
> vk1LA_V4YQ1hglQ&s=sOkLdKstR35Im3KMDgRA9caOvPT4PgnQqEleSi1O6XU&e=
> On 12/5/2016 10:07 AM, Katharine Walter wrote:
>
>> Hi,
>>
>> I am interested in estimating discrete ancestral states in ace using the
>> calls:
>> fitER<-ace(tipRegion,tree,model="ER",type="discrete")
>> fitARD<-ace(tipRegion,tree,model="ARD",type="discrete", use.expm=TRUE)
>>
>> When I fit the ARD model (with either use.expm=TRUE or use.eigen=TRUE), I
>> get the following warning:
>>  1: In nlminb(rep(ip, length.out = np), function(p) dev(p), lower = rep(0,
>>  : imaginary parts discarded in coercion
>>
>> Additionally, the two rates which I expect to be the highest are estimated
>> as 0. There are 3 tip states for a tree of 146 tips and 145 internal
>> nodes.
>> A likelihood ratio test supports the ARD model, but I cannot trust model
>> results. I am wondering:
>> 1) is there an obvious error that is creating this warning and unexpected
>> output?
>> 2) should I use a simpler model (i.e. SYM)? Or should I reclassify tip
>> states so that I examine transitions between only 2 states?
>>
>> Thank you in advance for your help! This is a fantastic package!
>> Best,
>>
>>         [[alternative HTML version deleted]]
>>
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>

        [[alternative HTML version deleted]]

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