Better posted on r-sig-mixed-models , no?
Cheers,
Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Wed, Aug 23, 2017 at 5:17 AM, PIKAL Petr <petr.pi...@precheza.cz> wrote:
> Dear all
>
> I encountered strange behaviour of augPred with virtually the same data
>
> First I made groupedData object.
>> mar.g<-groupedData(rutilizace~doba|int, data=mar)
>
> When I perform nlme on complete dataset I get an error with augPred
>> fit<-nlsList(rutilizace~SSasymp(doba, Asym, R0, lrc), data=mar.g)
> Warning message:
> c("1 error caught in nls(y ~ cbind(1 - exp(-exp(lrc) * x), exp(-exp(lrc) *
> x)), data = xy, : singular gradient", "1 error caught in start = list(lrc
> = lrc), algorithm = \"plinear\"): singular gradient")
>> fit1<-nlme(fit)
>> plot(augPred(fit1, level=0:1))
> Error in `[[<-.data.frame`(`*tmp*`, nm, value = c(6L, 6L, 6L, 6L, 8L, :
> replacement has 60 rows, data has 12
>
> However when I make subset of my data to keep only affected collumns.
>>
>> mar.g<-mar.g[,c(3,4, 21)]
>
>> fit<-nlsList(rutilizace~SSasymp(doba, Asym, R0, lrc), data=mar.g)
> Warning message:
> c("1 error caught in nls(y ~ cbind(1 - exp(-exp(lrc) * x), exp(-exp(lrc) *
> x)), data = xy, : singular gradient", "1 error caught in start = list(lrc
> = lrc), algorithm = \"plinear\"): singular gradient")
>> fit2<-nlme(fit)
>> plot(augPred(fit2, level=0:1))
>>
> augPred works as a charm.
>
> When I compare fit1 and fit2 they are equal
>> all.equal(fit1, fit2)
> [1] TRUE
>>
>
> Does anybody know where I should try to search for problems?
>
> Best regards
> Petr
>
>> traceback()
> 6: stop(sprintf(ngettext(N, "replacement has %d row, data has %d",
> "replacement has %d rows, data has %d"), N, nrows), domain = NA)
> 5: `[[<-.data.frame`(`*tmp*`, nm, value = c(1L, 1L, 1L, 1L, 5L,
> 5L, 5L, 5L, 9L, 9L, 9L, 9L, 4L, 4L, 4L, 4L, 8L, 8L, 8L, 8L, 12L,
> 12L, 12L, 12L, 3L, 3L, 3L, 3L, 7L, 7L, 7L, 7L, 11L, 11L, 11L,
> 11L, 1L, 1L, 1L, 1L, 5L, 5L, 5L, 5L, 9L, 9L, 9L, 9L, 2L, 2L,
> 2L, 2L, 6L, 6L, 6L, 6L, 10L, 10L, 10L, 10L))
> 4: `[[<-`(`*tmp*`, nm, value = c(1L, 1L, 1L, 1L, 5L, 5L, 5L, 5L,
> 9L, 9L, 9L, 9L, 4L, 4L, 4L, 4L, 8L, 8L, 8L, 8L, 12L, 12L, 12L,
> 12L, 3L, 3L, 3L, 3L, 7L, 7L, 7L, 7L, 11L, 11L, 11L, 11L, 1L,
> 1L, 1L, 1L, 5L, 5L, 5L, 5L, 9L, 9L, 9L, 9L, 2L, 2L, 2L, 2L, 6L,
> 6L, 6L, 6L, 10L, 10L, 10L, 10L))
> 3: gsummary(data, groups = groups)
> 2: augPred.lme(fit1, level = 0:1)
> 1: augPred(fit1, level = 0:1)
>
>> version
> _
> platform x86_64-w64-mingw32
> arch x86_64
> os mingw32
> system x86_64, mingw32
> status Under development (unstable)
> major 3
> minor 5.0
> year 2017
> month 07
> day 31
> svn rev 73003
> language R
> version.string R Under development (unstable) (2017-07-31 r73003)
> nickname Unsuffered Consequences
>>
>
> Package nlme version 3.1-131
>
>
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