Hi, folks,
Here are the codes:
##############
y=1:10
x=c(1:9,1)
lin=lm(log(y)~x) ### log(y) is following Normal distribution
x=5:14
prediction=predict(lin,newdata=x) ##prediction=predict(lin)
###############
1. The codes do not work, and give the error message: Error in
eval(predvars, data, env) :
numeric 'envir' arg not of length one. But if I use the code after the
pound sign, it works. I mean the name of the newdata is x, why it does not
work though?
2. Because the prediction is conducted for log(y). I need to get the
expected value of y, which is LN distribution, for the new data sets. I need
to know the expectation of log(y) and variance of log(y).
#####
mean=mean(prediction)
sd=sd(prediction)
mean_y=exp(mean+0.5*sd^2) ### formula from Normal to LN
######
Is sd(prediction) the correct why to calculate the sigma of the prediction?
Or should I just use the value of Residual standard error from summary(lin)?
Answer to either question will be appreciated!
Thanks
Yi
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