问题
I have a dataset like this
df
x y
7.3006667 -0.14383333
-0.8983333 0.02133333
2.7953333 -0.07466667
and I would like to fit an exponential function like y = a*(exp(bx)).
This is what I tried and the error I get
f <- function(x,a,b) {a * exp(b * x)}
st <- coef(nls(log(y) ~ log(f(x, a, b)), df, start = c(a = 1, b = -1)))
Error in qr.qty(QR, resid) : NA/NaN/Inf in foreign function call (arg 5)
In addition: Warning messages:
1: In log(y) : NaNs produced
2: In log(y) : NaNs produced
fit <- nls(y ~ f(x, a, b), data = df, start = list(a = st[1], b = st[2]))
Error in nls(y ~ exp(a + b * x), data = df, start = list(a = st[1], :
singular gradient
I believe it has to do with the fact that the log is not defined for negative numbers but I don't know how to solve this.
回答1:
I'm having trouble seeing the problem here.
f <- function(x,a,b) {a * exp(b * x)}
fit <- nls(y~f(x,a,b),df,start=c(a=1,b=1))
summary(fit)$coefficients
# Estimate Std. Error t value Pr(>|t|)
# a -0.02285668 0.03155189 -0.7244157 0.6008871
# b 0.25568987 0.19818736 1.2901422 0.4197729
plot(y~x, df)
curve(predict(fit,newdata=data.frame(x)), add=TRUE)
The coefficients are very poorly estimated, but that's not surprising: you have two parameters and three data points.
As to why your code fails: the first call to nls(...)
generates an error, so st
is never set to anything (although it may have a value from some earlier code). Then you try to use that in the second call to nls(...)
.
来源:https://stackoverflow.com/questions/32251853/exponential-fitting-with-r