R预测（）仅返回nls（）模型的拟合值

Question

First of all, I would like to mention I am just a beginner in R. I have encountered a problem when trying to predict data from a model generated by nls(). I fitted the exponential decay function into my data and everything seems to be fine, eg I got a decent regression line. However, when I use predict() on a new data set, it returns only fitted values.

My code is:

df = data.frame(Time = c(0,5,15,30), Value = c(1, 0.38484677,0.18679383, 0.06732328))

model <- nls(Value~a*exp(-b*Time), start=list(a=1, b=0.15), data = df)

plot(Value~Time, data = df)

lines(df$Time, predict(model))

newtime <- data.frame(Time = seq(1,20, by = 1))

pr = predict(model, newdata = newtime$Time)

pr
[1] 0.979457389 0.450112312 0.095058637 0.009225664

Could someone explain me please, what I am doing wrong? I know there are here some answers to that problem, but none helped me.

Thank you in advance for your help!

Answer 1

The newdata parameter should be a data.frame with the same names as your input data. When you use newdata = newtime$Time you are actually passing in newtime$Time which is not a data.frame anymore since it 'dropped' down to a vector. You can just pass in newtime like so

pr = predict(model, newdata = newtime)