Dear Douglas Bates. I just downloaded the compiled version (I'm a poor
Windows devil, not yet having found the time to move to a more advanced
platform...) from NT- the files are dated 30.5-1999 so they are not old - and
the problem persisted....wonder what I did wrong ?
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Version 0.64.0 Patched (May 3, 1999)
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> library(lme)
> data(Orthodont)
> fm1 <- lme(distance ~ age, data = Orthodont) # random is ~ age
Error: Singular precision matrix in level 1, block 1>
> fm2 <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1)
warning: NA/Inf replaced by maximum positive value
Error: Singularity in backsolve at level 2, block 1>
Troels Ring, MD
Department of Nephrology
Aalborg Hospital
Aalborg Denmark
-----Oprindelig meddelelse-----
Fra: Douglas Bates <bates at stat.wisc.edu>
Til: Troels Ring <tring at mail1.stofanet.dk>
Cc: Jose Pinheiro <jcp at research.bell-labs.com>; Saikat DebRoy
<saikat at stat.wisc.edu>
Dato: 2. juni 1999 22:38
Emne: Re: [R] lme problem ?
>"Troels Ring" <tring at mail1.stofanet.dk> writes:
>
>> Dear friends. I tried the session below with 10 MB in both vsize and
>> nsize but didn't get the example work. Is this a problem in LME or
>> in me or both or somewhere else or undefined ?
>
>> > library(lme)
>> > data(Orthodont)
>> > fm1 <- lme(distance ~ age, data = Orthodont) # random is ~ age
>> Error: Singularity in backsolve at level 2, block 1>
>> > fm2 <- lme(distance ~ age + Sex, data = Orthodont, random = ~
1)
>> Error: singular matrix in chol
>
>That looks to me like a relatively old version of lme. I would
>suggest installing a new version. Your example works fine with the
>"lme du jour" which is version 3.0b8-1, available at the CRAN
sites in
>the src/contrib directory.
>
> R> fm1 <- lme(distance ~ age, data = Orthodont) # random is ~ age
> R> fm2 <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1)
> R> gc() # check amounts of storage in use
> free total
> Ncells 575483 800000
> Vcells 2015987 2097152
>
>I'm currently working on the 3.0b8a version that corrects some minor
>gliches in 3.0b8 and enhances the nls capabilities. I hope to upload
>that tomorrow.
>
>This is as good a time as any to announce that we uploaded an nls
>(nonlinear least squares) package for R last weekend. For historical
>reasons the nls package requires that you have the lme package
>installed. Many of the enhancements to nls for S were written as part
>of the NLME library and the R version of NLME is the lme package.
>(Now that I write this all out it doesn't make as much sense as it
>seemed to earlier but ...)
>
>There is also a package for R called NISTnls. This package includes
>the data and models for the nonlinear least squares examples at the
>U.S. National Institute for Standards and Technology (NIST). By
>running the examples in that package you can check the nls function
>itself.
>
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