library(nlme)
Loblolly$age2 <- as.factor(ifelse(Loblolly$age < 12.5, 0, 1))
这里我定义了一个我感兴趣的二进制协变量。
model <- nlme(height ~ (R0) + 1,
data = Loblolly,
fixed = list(R0 ~ 1 + (age2)),
random = list(Seed = pdDiag(list(R0 ~ 1))),
start = list(fixed = c(R0 = -8.5, age2 = 1)))
运行它会给我错误,
Error in nlme.formula(height ~ (R0) + 1, data = Loblolly, fixed = list(R0 ~ :
step halving factor reduced below minimum in PNLS step
更改起始值后,它可以正常工作。
model2 <- nlme(height ~ (R0) + 1,
data = Loblolly,
fixed = list(R0 ~ 1 + (age2)),
random = list(Seed = pdDiag(list(R0 ~ 1))),
start = list(fixed = c(R0 = 0, age2 = 30)), verbose=TRUE)
选择age2
的起始值有哪些方法?我考虑使用nls2
拟合非线性最小二乘模型,但这也需要指定一组起始值。
我想也许我可以绘制数据height ~ age2
,但是因为age2
是二进制的...我不知道如何去做。
答案 0 :(得分:1)
请尝试lm
,如下所示:
fm.lm <- lm(height ~ age2, Loblollly) # modified Loblolly as per question
st <- coef(fm.lm)
names(st)[1] <- "R0"
nlme(height ~ (R0) + 1, data = Loblolly,
fixed = list(R0 ~ 1 + (age2)),
random = list(Seed = pdDiag(list(R0 ~ 1))),
start = list(fixed = st))
,并提供:
Nonlinear mixed-effects model fit by maximum likelihood
Model: height ~ (R0) + 1
Data: Loblolly
Log-likelihood: -305.1093
Fixed: list(R0 ~ 1 + (age2))
R0.(Intercept) R0.age21
12.96167 36.80548
Random effects:
Formula: R0 ~ 1 | Seed
R0.(Intercept) Residual
StdDev: 0.0002791602 9.145988
Number of Observations: 84
Number of Groups: 14