Message-ID: <CAO7JsnR=mus-9y8KoSmwh6cZTjMjZOOZB_fodj2sTKEPaXo3Cw@mail.gmail.com>
Date: 2016-02-17T20:43:56Z
From: Douglas Bates
Subject: "Non-positive definite approximate variance-covariance" output
In-Reply-To: <CAOES0VhrWFysqUs7RXt2x0v61hHr5=t7ua8=R_FNpDzFZ5KDQQ@mail.gmail.com>
The standard errors are for the fixed-effects parameters. The apVar
component includes approximate variances of the estimators of (functions
of) the variance components, which is where the positive-definiteness
failure may be occurring..
On Wed, Feb 17, 2016 at 2:28 PM Jacob Bukoski <jbukoski1 at gmail.com> wrote:
> Hi all,
>
> I was in a discussion with my advisor today, and the issue of "non-positive
> definite approximate variance-covariance" errors in R when using the lme()
> function arose.
>
> Depending on the varFunc specification that I use, I receive the
> "non-positive definite approximate variance-covariance" output when calling
> myModel$apVar -- however, there are standard errors returned for my model
> coefficients in the model summary.
>
> My understanding is that if the variance-covariance cannot be approximated,
> neither should the standard errors... how is the lme() function returning
> standard errors without a variance-covariance approximation?
>
> Many thanks,
> Jacob
>
> --
> Jacob J. Bukoski
> Master of Environmental Science Candidate, 2016
> School of Forestry and Environmental Studies, Yale University
> jbukoski1 at gmail.com | jacob.bukoski at yale.edu | LinkedIn
> <
> https://www.linkedin.com/profile/view?id=AAIAAAdWVW8BMzqU_2EGNbEkyuy8O7K1Jyhd8ps&trk=nav_responsive_tab_profile_pic
> >
>
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