这个问题建立在我之前问过的一个问题上,Exponential curve fitting with nls using data.table groups。
我使用nls
将指数曲线拟合到多个组的数据表对象。并不是所有的数据都符合指数模型,nls
有时会抛出错误,停止对其余组的所有进一步计算。
我尝试使用tryCatch
跳过有问题的组,但我在下面附加了一个MWE,但我得到了所有新列的错误输出。如何跳过为有问题的组计算nls
值?
## Example data table
DT <- data.table(
x = c(1,2,3,4,5,6,7,8,
1,2,3,4,5,6,7,8,
1,2,3,4,5,6,7,8),
y = c(15.4,16,16.4,17.7,20,23,27,35,
25.4,26,26.4,27.7,30,33,37,45,
27.4,28,28.4,29.7,32,35,39,47),
groups = c(1,1,1,1,1,1,1,1,
2,2,2,2,2,2,2,2,
3,3,3,3,3,3,3,3)
)
## Fit exponential curve using starting values a,b,c for each group
DT[, c("sigma", "a", "b", "c") := {
c.0 <- min(y) * 0.5
model.0 <- lm(log(y - c.0) ~ x, data=.SD)
start <- list(a=exp(coef(model.0)[1]), b=coef(model.0)[2], c=c.0)
model <- nls(y ~ a * exp(b * x) + c,
data=.SD,
start=start,
control=nls.control(maxiter=500))
c(.(sigma=summary(model)$sigma), as.list(coef(model)))
},
by=.(groups)]
## Modify data table to ruin nls model for group 2
set(DT, i=16L, j="y", value=3)
## Calculation works for group 1 but stops for group 2 and onwards
DT[, c("sigma", "a", "b", "c") := {
c.0 <- min(y) * 0.5
model.0 <- lm(log(y - c.0) ~ x, data=.SD)
start <- list(a=exp(coef(model.0)[1]), b=coef(model.0)[2], c=c.0)
model <- nls(y ~ a * exp(b * x) + c,
data=.SD,
start=start,
control=nls.control(maxiter=500))
c(.(sigma=summary(model)$sigma), as.list(coef(model)))
},
by=.(groups)]
## My poor attempt at using a tryCatch just gives NA to every column
DT[, c("sigma","a", "b", "c") := {
c.0 <- min(y) * 0.5
model.0 <- lm(log(y - c.0) ~ x, data=.SD)
start <- list(a=exp(coef(model.0)[1]), b=coef(model.0)[2], c=c.0)
model <- tryCatch(
{
nls(y ~ a * exp(b * x) + c,
data=.SD,
start=start,
control=nls.control(maxiter=500))
c(.(sigma=summary(model)$sigma), as.list(coef(model)))
},
error=function(err){
return(NA_real_)
}
)
},
by=.(groups)]
https://stackoverflow.com/questions/52520710
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