singular convergence with lmer()
Finally I have reproduced the crash. Before running lme4 I log-transform the response of the original dataset in R. Attached are the
original dataset and the R code.
library(lme4)
setwd("...")
dat <- read.csv("zzz.csv", header=TRUE, na.strings = "",
??? colClasses=c("factor", "factor","factor","factor","numeric"))
str(dat)
??? dat$Operator <- dat$Operator:dat$Day
??? dat$Part <- dat$Sample
??? dat$y <- log10(dat$Response)
??? dat <- droplevels(subset(dat, subset= !is.na(dat$y)))
lmer(y ~ (1|Operator)+(1|Part)+(1|Part:Operator),? data=dat)
The dataset "zzz.csv" :
NumDos Day Operator Sample Response
2010_0402 1 1 1 5.3
2010_0402 1 1 1 5
2010_0402 1 1 2 35.8
2010_0402 1 1 2 34.3
2010_0402 1 1 3 61.1
2010_0402 1 1 3 61.6
2010_0402 1 1 4 130.9
2010_0402 1 1 4 135.1
2010_0402 1 1 5 206.3
2010_0402 1 1 5 195.2
2010_0402 1 1 6 479.7
2010_0402 1 1 6 462.2
2010_0402 1 1 7 780.9
2010_0402 1 1 7 818.2
2010_0402 1 1 8 1522.9
2010_0402 1 1 8 1549.8
2010_0402 1 1 9 2443.8
2010_0402 1 1 9 3150.9
2010_0402 1 1 10 5406.3
2010_0402 1 1 10 5304.8
2010_0402 1 1 11 6686.4
2010_0402 1 1 11 6536.1
2010_0402 1 1 12 9864.9
2010_0402 1 1 12 9448
2010_0402 1 2 1 5.2
2010_0402 1 2 1 5.2
2010_0402 1 2 2 36
2010_0402 1 2 2 37
2010_0402 1 2 3 67.3
2010_0402 1 2 3 69.2
2010_0402 1 2 4 146.3
2010_0402 1 2 4 138.9
2010_0402 1 2 5 210.4
2010_0402 1 2 5 210.8
2010_0402 1 2 6 534.9
2010_0402 1 2 6 506.1
2010_0402 1 2 7 757.2
2010_0402 1 2 7 813.2
2010_0402 1 2 8 1659.9
2010_0402 1 2 8 1790.3
2010_0402 1 2 9 3478.3
2010_0402 1 2 9 3469.4
2010_0402 1 2 10 6377.7
2010_0402 1 2 10 5758.9
2010_0402 1 2 11 8258.3
2010_0402 1 2 11 7317.2
2010_0402 1 2 12 10461
2010_0402 1 2 12 10155.5
2010_0402 2 1 1 4.9
2010_0402 2 1 1 5.2
2010_0402 2 1 2 35
2010_0402 2 1 2 31
2010_0402 2 1 3 57.9
2010_0402 2 1 3 60.1
2010_0402 2 1 4 133.8
2010_0402 2 1 4 136.9
2010_0402 2 1 5 173.7
2010_0402 2 1 5 179.9
2010_0402 2 1 6 457.2
2010_0402 2 1 6 489.8
2010_0402 2 1 7 773.9
2010_0402 2 1 7 799.2
2010_0402 2 1 8 1435.1
2010_0402 2 1 8 1536.5
2010_0402 2 1 9 3714.1
2010_0402 2 1 9 3880.5
2010_0402 2 1 10 5327.9
2010_0402 2 1 10 5548.3
2010_0402 2 1 11 7548.1
2010_0402 2 1 11 7206.5
2010_0402 2 1 12 9947.5
2010_0402 2 1 12 10477.1
2010_0402 2 2 1 5.7
2010_0402 2 2 1 5.4
2010_0402 2 2 2 37.6
2010_0402 2 2 2 37.3
2010_0402 2 2 3 66.2
2010_0402 2 2 3 51.6
2010_0402 2 2 4 121.3
2010_0402 2 2 4 139.8
2010_0402 2 2 5 199
2010_0402 2 2 5 231.7
2010_0402 2 2 6 514.7
2010_0402 2 2 6 605.7
2010_0402 2 2 7 856.6
2010_0402 2 2 7 867.6
2010_0402 2 2 8 1539.2
2010_0402 2 2 8 1691.8
2010_0402 2 2 9 4337.8
2010_0402 2 2 9 4744.2
2010_0402 2 2 10 8121.6
2010_0402 2 2 10 6447.1
2010_0402 2 2 11 8577
2010_0402 2 2 11 8148.4
2010_0402 2 2 12 13747.7
2010_0402 2 2 12 12335
2010_0402 3 1 1 4.8
2010_0402 3 1 1 4.8
2010_0402 3 1 2 36.6
2010_0402 3 1 2 35.6
2010_0402 3 1 3 69.3
2010_0402 3 1 3 70.6
2010_0402 3 1 4 147.3
2010_0402 3 1 4 141.4
2010_0402 3 1 5 190.9
2010_0402 3 1 5 162.5
2010_0402 3 1 6 525.6
2010_0402 3 1 6 488.7
2010_0402 3 1 7 885.3
2010_0402 3 1 7 866.9
2010_0402 3 1 8 1590.9
2010_0402 3 1 8 1662.9
2010_0402 3 1 9 4146.9
2010_0402 3 1 9 4962.8
2010_0402 3 1 10 5005.8
2010_0402 3 1 10 5787.6
2010_0402 3 1 11 7605.6
2010_0402 3 1 11 7996.6
2010_0402 3 1 12 10513.9
2010_0402 3 1 12 11256.8
2010_0402 3 2 1 5.4
2010_0402 3 2 1 5.4
2010_0402 3 2 2 34.8
2010_0402 3 2 2 37.6
2010_0402 3 2 3 63.7
2010_0402 3 2 3 65.4
2010_0402 3 2 4 149.5
2010_0402 3 2 4 152.5
2010_0402 3 2 5 201.4
2010_0402 3 2 5 210.9
2010_0402 3 2 6 470
2010_0402 3 2 6 459.5
2010_0402 3 2 7 885.3
2010_0402 3 2 7 829
2010_0402 3 2 8 1781.6
2010_0402 3 2 8 1555.1
2010_0402 3 2 9 4215.3
2010_0402 3 2 9 3966.9
2010_0402 3 2 10 5063.7
2010_0402 3 2 10 5365.4
2010_0402 3 2 11 7441.6
2010_0402 3 2 11 7592.1
2010_0402 3 2 12 10769.1
2010_0402 3 2 12 10955.4
2010_0402 5 1 1 6
2010_0402 5 1 1 5.8
2010_0402 5 1 2 38.8
2010_0402 5 1 2 38.5
2010_0402 5 1 3 68.4
2010_0402 5 1 3 67.4
2010_0402 5 1 4 149.8
2010_0402 5 1 4 158.2
2010_0402 5 1 5 193.1
2010_0402 5 1 5 190.6
2010_0402 5 1 6 478.6
2010_0402 5 1 6 499.9
2010_0402 5 1 7 914
2010_0402 5 1 7 897.2
2010_0402 5 1 8 1543.3
2010_0402 5 1 8 1387.3
2010_0402 5 1 9 3574.1
2010_0402 5 1 9 3640.9
2010_0402 5 1 10 5371.4
2010_0402 5 1 10 5583.8
2010_0402 5 1 11 8196.4
2010_0402 5 1 11 7754.8
2010_0402 5 1 12 10663
2010_0402 5 1 12 12536.7
2010_0402 5 2 1 6.7
2010_0402 5 2 1 6.2
2010_0402 5 2 2 38.9
2010_0402 5 2 2 40.4
2010_0402 5 2 3 65.9
2010_0402 5 2 3 65.2
2010_0402 5 2 4 139.8
2010_0402 5 2 4 137.3
2010_0402 5 2 5 231.3
2010_0402 5 2 5 217.4
2010_0402 5 2 6 540.9
2010_0402 5 2 6 500.9
2010_0402 5 2 7 807.5
2010_0402 5 2 7 866.3
2010_0402 5 2 8 1539.8
2010_0402 5 2 8 1531.4
2010_0402 5 2 9 3556.9
2010_0402 5 2 9 3328.2
2010_0402 5 2 10 5113.4
2010_0402 5 2 10 5553.9
2010_0402 5 2 11 7782.7
2010_0402 5 2 11 6404.3
2010_0402 5 2 12 9499.8
2010_0402 5 2 12 9876.5
________________________________
De?: Ben Bolker <bbolker at gmail.com>
??: r-sig-mixed-models at r-project.org
Envoy? le : Dimanche 8 juillet 2012 21h58
Objet?: Re: [R-sig-ME] singular convergence with lmer()
laurent stephane <laurent_step at ...> writes:
Dear all, Using the latest CRAN version of lme4 ? I get the following warning from lmer() : Warning message: In mer_finalize(ans) : singular convergence (7)
My model is not complicated and it works fine with SAS (if you are interested in the details of my model see forums.cirad.fr/logiciel-R/viewtopic.php?t=5071 )
What argument could I change in lmer() to overcome this warning ?
? This warning emerges from the nlminb optimizer used in the guts of lme4, and I don't think there's much you can do to suppress it or change the behavior of nlminb to avoid it.? The best you could do would be to use other packages (SAS, other versions of lme4 or nlme, etc.) to see if the correct answer was achieved despite the warning. ? Ben Bolker _______________________________________________ R-sig-mixed-models at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models