89 lines
3.2 KiB
R
89 lines
3.2 KiB
R
|
library(nlme)
|
||
|
|
## if(require("Hmisc")) { -- no longer: depending on ggplot2 -> total +22 pkgs is too much
|
||
|
|
T.aug <- Orthodont
|
||
|
|
## now manually label(T.aug$age) <- 'anyL'
|
||
|
|
## now manually:
|
||
|
|
T.aug$age <- structure(T.aug$age, label = "anyL", class = c("labelled", "numeric"))
|
||
|
|
foo <- augPred(lme(distance ~ age, random = ~1|Subject, data=T.aug))
|
||
|
|
## failed in 3.1-72
|
||
|
|
stopifnot(length(foo$age) == 1485L, inherits(foo$age, "labelled"),
|
||
|
|
attr(foo$age,"label") == "anyL")
|
||
|
|
## }
|
||
|
|
|
||
|
|
## failed even if there is a variable with a class that is not being used.
|
||
|
|
T.aug <- Orthodont
|
||
|
|
T.aug$newage <- T.aug$age
|
||
|
|
class(T.aug$newage) <- 'anyC'
|
||
|
|
foo <- augPred(lme(distance ~ age, random = ~1|Subject, data=T.aug))
|
||
|
|
## failed in 3.1-72
|
||
|
|
|
||
|
|
## [Bug 16715] New: nlme: unable to use predict and augPredict functions in non linear mixed models
|
||
|
|
## Date: Wed, 17 Feb 2016
|
||
|
|
|
||
|
|
M1.lis <- nlsList( SSlogis, data=Soybean)
|
||
|
|
## prints "Error in qr.solve(QR.B, cc): singular matrix 'a' in solve"
|
||
|
|
## ==> MM: 2016-03-11 "fixed": now prints it as warning [you could suppress or catch]
|
||
|
|
## ==> one NA row '1989P8' in this:
|
||
|
|
M1.lis
|
||
|
|
## Nonlinear Logistic Growth -- each of the 3 par. (Asym, xmid, scal) has RE term
|
||
|
|
## Model: weight ~ SSlogis(Time, Asym, xmid, scal) | Plot
|
||
|
|
|
||
|
|
M1.nlme <- nlme( M1.lis )
|
||
|
|
summary(M1.nlme)
|
||
|
|
## R 3.2.2 (nlme 3.1-121) :
|
||
|
|
## Nonlinear mixed-effects model fit by maximum likelihood
|
||
|
|
## Model: weight ~ SSlogis(Time, Asym, xmid, scal)
|
||
|
|
## Data: Soybean
|
||
|
|
## AIC BIC logLik
|
||
|
|
## 1499.671 1539.881 -739.8354
|
||
|
|
|
||
|
|
## Random effects:
|
||
|
|
## Formula: list(Asym ~ 1, xmid ~ 1, scal ~ 1)
|
||
|
|
## Level: Plot
|
||
|
|
## Structure: General positive-definite, Log-Cholesky parametrization
|
||
|
|
## StdDev Corr
|
||
|
|
## Asym 5.201186 Asym xmid
|
||
|
|
## xmid 4.197467 0.721
|
||
|
|
## scal 1.404737 0.711 0.958
|
||
|
|
## Residual 1.123461
|
||
|
|
|
||
|
|
## Fixed effects: list(Asym ~ 1, xmid ~ 1, scal ~ 1)
|
||
|
|
## Value Std.Error DF t-value p-value
|
||
|
|
## Asym 19.25301 0.8031921 362 23.97062 0
|
||
|
|
## xmid 55.01985 0.7272721 362 75.65235 0
|
||
|
|
## scal 8.40333 0.3152893 362 26.65276 0
|
||
|
|
## Correlation:
|
||
|
|
## Asym xmid
|
||
|
|
## xmid 0.724
|
||
|
|
## scal 0.620 0.807
|
||
|
|
|
||
|
|
## Standardized Within-Group Residuals:
|
||
|
|
## Min Q1 Med Q3 Max
|
||
|
|
## -6.08691772 -0.22160816 -0.03390491 0.29741145 4.84688248
|
||
|
|
|
||
|
|
## Number of Observations: 412
|
||
|
|
## Number of Groups: 48
|
||
|
|
|
||
|
|
M1.Fix <- fixef(M1.nlme)
|
||
|
|
## add fixed effect 'Variety' :
|
||
|
|
M2.nlme <- update(M1.nlme, fixed = Asym + xmid + scal ~ Variety,
|
||
|
|
start = c(M1.Fix[1], 1, M1.Fix[2], 1, M1.Fix[3], 1))
|
||
|
|
summary(M2.nlme)
|
||
|
|
pred.m2 <- predict(M2.nlme, level = 0:1)
|
||
|
|
stopifnot(is.data.frame(pred.m2), dim(pred.m2) == c(412, 3))
|
||
|
|
|
||
|
|
augp.m2 <- augPred(M2.nlme, level = 0:1)
|
||
|
|
## failed in nlme-3.1-124/5
|
||
|
|
|
||
|
|
stopifnot(is.data.frame(augp.m2), dim(augp.m2) == c(5308, 4)
|
||
|
|
,
|
||
|
|
all.equal(colMeans(augp.m2[,c("Time","weight")]),
|
||
|
|
c(Time = 48.585908, weight =7.8599693), tolerance = 1e-6)# was 1e-7, 2e-9 but failed with ATLAS builds
|
||
|
|
,
|
||
|
|
identical(c(table(augp.m2[,".type"])),
|
||
|
|
c(predict.fixed = 2448L, predict.Plot = 2448L, original = 412L))
|
||
|
|
,
|
||
|
|
identical(c(table(as.vector(table(augp.m2[,".groups"])))),
|
||
|
|
c("110" = 33L, "111" = 2L, "112" = 13L))
|
||
|
|
)
|