FYI. The devtools package has a function dev_mode() which allows a user to
switch between stable and development versions of a package.

Kevin


On Thu, Feb 9, 2012 at 11:16 AM, Douglas Bates <bates@stat.wisc.edu> wrote:

> On Wed, Feb 8, 2012 at 6:32 PM, Joshua Wiley <jwiley.psych@gmail.com>
> wrote:
> > Thanks to the authors for fantastic work.
> >
> > Once the new version is pushed to CRAN, does anyone know if it will be
> > called lme4Eigen or the familiar lme4?
>
> Current plan is that the new version will still be called lme4 but we
> will also release to CRAN a package lme4preEigen as a bacikup for
> users whose code gets broken by the new version.  At present Martin is
> on vacation and the plan has not been confirmed by him (and he knows
> more about the packaging system and CRAN than Ben or I do).  We will
> wait until he returns next week before confirming.
>
> > On Tue, Feb 7, 2012 at 9:11 AM, Douglas Bates <bates@stat.wisc.edu>
> wrote:
> >> We (the lme4 authors) have mentioned on this list that we are
> >> preparing a new version of lme4 that will provide enhanced
> >> capabilities.  That's the good news.  The bad news is that the
> >> internal representation of the model has been changed yet again.  If
> >> your use of the lme4 package is through the exported functions only
> >> you should be okay.  However, if you find problems then please report
> >> them to us either in email <lme4-authors@r-forge.wu-wien.ac.at> or on
> >> the bug-tracker at R-forge,
> >>
> >> https://r-forge.r-project.org/tracker/?func=add&group_id=60&atid=298
> >>
> >> One major, and unfortunately inevitable, problem that will affect many
> >> users is the inability of the new code to load saved objects created
> >> with the old code.  Unfortunately that is what happens when you change
> >> the class representation.  If possible it is best to save the code and
> >> data that generated the fitted model and re-fit after the change.
> >>
> >> If your usage involved access to components or slots in the object
> >> then there will be changes.  To ease the transition, Martin created a
> >> function called getME that is available in the current lme4 and in the
> >> new lme4, available as lme4Eigen on R-forge.  This function takes a
> >> fitted model and a character variable naming a component and returns
> >> the desired component.  For example, if you want the fixed-effects
> >> model matrix from fitted model fm1 then use
> >>
> >> getME(fm1, "X")
> >>
> >> Similarly for the random-effects model matrix, "Z", or its transpose,
> >> "Zt", the sparse Cholesky factor, "L" and many others.  Use
> >>
> >> library(lme4)
> >> example(getME)
> >>
> >> to get some examples.
> >>
> >> The new lme4 will provide
> >>
> >>  - profiling of the deviance function with respect to the parameters
> >>   in a linear mixed model (and soon generalized linear mixed models).
> >>   The profiles allow for creation of realistic confidence intervals
> >>   on the parameters and for various plots that show the sensitivity
> >>   of the deviance to the values of the parameters.
> >>
> >>  - a more reliable and flexible implementation of generalized linear
> >>   mixed models, including the use of adaptive Gauss-Hermite
> >>   quadrature for evaluating an approximation to the deviance.
> >>
> >>  - short-cut functions such as refitML and refit to re-evaluate a
> >>   model under the maximum likelihood criterion or with a new response
> >>   vector.
> >>
> >>  - a cleaner internal representations that provides, in most cases,
> >>   faster and more reliable model fits.
> >>
> >>  - choice of optimizer when estimating the parameters.  Current
> >>   choices are "NelderMead" and "bobyqa".  Both are generally faster
> >>   and more reliable than the optimizer used in the current lme4,
> >>   which is based on the code in R's nlminb() function, the one that
> >>   gives those annoying "false convergence" messages.
> >>
> >>  - smaller memory footprint.  The need for copying large objects is
> >>   reduced through the use of reference classes in R.  In the past
> >>   there were circumstances where it was possible to fit a model to a
> >>   large data set but not to print or show the results because a new
> >>   copy of the entire object was created during the process of
> >>   creating a summary.  This no longer occurs.
> >>
> >>  - nlmer has been improved and will, by the time of release, allow
> >>   adaptive Gauss-Hermite quadrature.
> >>
> >> An alpha-test release will be made available on the R-forge archive
> >> but *not* uploaded to CRAN.  If you use lme4 extensively please test
> >> this release by installing from the R-forge archive and telling us if
> >> there are problems with your code.  This way you can still back out to
> >> the current release by removing the lme4 package and reinstalling from
> >> CRAN.  Once the new lme4 has been released to CRAN it will be much
> >> more difficult to back out that installation.
> >>
> >> Authors of packages that depend on lme4 will get a separate message
> >> off-list about testing and suggested modifications.
> >>
> >> Thanks for your cooperation.  We do honestly believe that this change
> >> will provide an improved capability for fitting and analyzing
> >> mixed-effects models.
> >>
> >> _______________________________________________
> >> R-sig-mixed-models@r-project.org mailing list
> >> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
> >
> >
> >
> > --
> > Joshua Wiley
> > Ph.D. Student, Health Psychology
> > Programmer Analyst II, Statistical Consulting Group
> > University of California, Los Angeles
> > https://joshuawiley.com/
> >
> > _______________________________________________
> > R-sig-mixed-models@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>
> _______________________________________________
> R-sig-mixed-models@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>



-- 
Kevin Wright

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