我知道在尝试为'initial value in vmmim is not finite'
对象拟合参数时,网页上有关于mle2
错误的问题(和答案)。我在创建mle2
对象时没有出现此错误,但在尝试从mle2
对象中查找参数的95%CI时出现此错误。
这是一个可重复的例子:
以下是数据:
d = structure(list(SST_1YR = c(11.6, 11.7, 11.9, 12, 12.1, 12.2,
12.3, 12.4, 12.5, 12.6, 12.7, 12.8, 12.9, 13, 13.1, 13.2, 13.3,
13.4, 13.5, 13.6, 13.7, 13.8, 13.9, 14, 14.2, 14.3, 14.4, 14.5,
14.6, 14.7, 14.8, 14.9, 15, 15.1, 15.2, 15.3, 15.4, 15.5, 15.6,
15.7, 15.8, 15.9, 16, 16.2, 16.3, 16.5, 16.6, 16.7, 16.9, 17,
17.1, 17.2, 17.3, 17.4, 17.5, 17.6, 17.7, 17.8, 17.9), DML = structure(c(84.5,
71, 114.75, 90.9473684210526, 31.7631578947368, 92.5, 80.4, 98.7021276595745,
70.8, 66.8382352941177, 70.2553191489362, 98.1111111111111, 86.5241379310345,
59.7209302325581, 38.7692307692308, 78.2028985507246, 86.3503649635037,
69.1161290322581, 61.9122807017544, 60.1212121212121, 98.5490196078431,
94.3145161290323, 76.5643564356436, 39.4230769230769, 98.42,
95.6129032258064, 65.9673202614379, 39, 64.0576923076923, 42.4166666666667,
59.6989247311828, 62.8039215686275, 74.5263157894737, 50.8888888888889,
64.35, 40.5, 53.7466666666667, 42, 49.5, 23.8888888888889, 39.6170212765957,
74.8947368421053, 42.8518518518519, 40.0344827586207, 53, 39.3333333333333,
24.1333333333333, 30, 39.4880952380952, 94.4883720930233, 69.1428571428571,
33.7179487179487, 26.1538461538462, 37.8965517241379, 38.4117647058824,
44.2727272727273, 68.3157894736842, 37.3, 43.4444444444444), .Dim = 59L, .Dimnames = list(
c("11.6", "11.7", "11.9", "12", "12.1", "12.2", "12.3", "12.4",
"12.5", "12.6", "12.7", "12.8", "12.9", "13", "13.1", "13.2",
"13.3", "13.4", "13.5", "13.6", "13.7", "13.8", "13.9", "14",
"14.2", "14.3", "14.4", "14.5", "14.6", "14.7", "14.8", "14.9",
"15", "15.1", "15.2", "15.3", "15.4", "15.5", "15.6", "15.7",
"15.8", "15.9", "16", "16.2", "16.3", "16.5", "16.6", "16.7",
"16.9", "17", "17.1", "17.2", "17.3", "17.4", "17.5", "17.6",
"17.7", "17.8", "17.9")))), .Names = c("SST_1YR",
"DML"), row.names = c(NA, -59L), class = "data.frame")
这是mle2
对象的创建(没有警告......)
m = mle2(DML~dgamma(scale=(a+b*SST_1YR)/sh, shape=sh), start=list(a=170, b=-7.4, sh=10), data=d)
这里是我获得NA的地方vmmin
警告参数b
的下限:
confint(m)
我尝试过更改起始值,但我尝试过的任何内容都没有帮助。我已经创建了具有相同数据但具有不同分布且没有错误的其他模型。任何人都可以帮我找出造成这个错误的原因吗?
使用包bbmle-1.0.17
答案 0 :(得分:3)
这里有几件事要尝试。首先看数据(总是一个好主意):
library("ggplot2"); theme_set(theme_bw())
ggplot(d,aes(SST_1YR,DML)) + geom_point()+
geom_smooth(method="glm",family=Gamma(link="identity"))+
geom_smooth(method="lm",colour="red",fill="red")
请注意,在这种情况下,Gamma回归看起来几乎与常规线性回归相同(即形状参数很大)。此外,x值的分布远离原点 - 这可能会导致数字问题。
library("bbmle")
m <- mle2(DML~dgamma(scale=(a+b*SST_1YR)/sh, shape=sh),
start=list(a=170, b=-7.4, sh=10), data=d)
confint(m)
确认问题:
## 2.5 % 97.5 %
## a 132.05952 203.192159
## b NA -4.407289
## sh 6.83566 13.933383
我认为设置parscale
可能会有所帮助,但它似乎会让问题变得更糟而不是更好:
m2 <- update(m,control=list(parscale=c(a=170,b=8,sh=10)))
confint(m2)
## 2.5 % 97.5 %
## a NA 203.153230
## b NA -4.407281
## sh 6.835659 13.933383
以预测变量为中心有帮助吗? scale(x,scale=FALSE)
中心x
但不缩放SST_1YR-mean(SST_1YR)
...(使用scale
可能更清晰,这样我们就不会在表达式中浮动三个m3 <- mle2(DML~dgamma(scale=(a+b*scale(SST_1YR,scale=FALSE))/sh, shape=sh),
start=list(a=170, b=-7.4, sh=10), data=d)
confint(m3)
## 2.5 % 97.5 %
## a 56.462610 66.754118
## b -9.421521 -4.407262
## sh 6.835662 13.933384
。 ..
glm(DML~SST_1YR,family=Gamma(link="identity"),data=d)
看起来不错,虽然将拦截术语恢复到原始比例会有点棘手(尽管我们可以从之前的,未经调整的拟合中获取它们)。
事实证明你也可以通过
来适应这个模型confint()
虽然Error in y/mu: non-conformable arrays
再次神秘失败(mle2(DML~dgamma(scale=pmin((a+b*SST_1YR)/sh,1e-5),
shape=sh),
start=list(a=170, b=-7.4, sh=10), data=d)
)。
我尝试过的其他一些效果不佳(此处仅包含完整性):
dgamma
NA
的惩罚形式返回错误的可能性,而不是x<0
时dgamma_pen <- function(x,...,log=FALSE) {
r <- if (x<0) (-100) else dgamma(x,...,log=TRUE)
if (log) r else exp(r)
}
m4 <- mle2(DML~dgamma_pen(scale=pmin((a+b*SST_1YR)/sh,1e-5),
shape=sh),
start=list(a=170, b=-7.4, sh=10), data=d)
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