Many thanks Rolf,
These codes below are ok :
LinearModel.1 <- lm(GDP.per.head ~ Competitivness.score + Quality.score, data=Dataset)
summary(LinearModel.1)
predict(LinearModel.1, se.fit = FALSE, scale = NULL, df = Inf,interval = c("prediction"),level = 0.95, type = c("response"))
One problem remains : If I want to plot out (in a same graph) the predicted values as well as the upper and lower limits of the prediction intervals for those values. How can I do, many thanks once more.
Best,
Le Mercredi 26 février 2014 4h59, varin sacha a écrit :
Hi,
I have realized a multiple linear regression.
To know how well my model does in terms of prediction, I can compute prediction intervals bands and decide if they are narrow enough to be of use. If they are too wide, then they probably are not useful.
So what I am trying to do is :
Theoretically I know that I can use the "predict" command in R to generate the prediction interval for a set of points. The idea is to find the linear regression using the lm command. Then I can use the predict command to get the prediction interval for a set of points in the domain. Then I plot out the predicted values as well as the upper and lower limits of the prediction intervals for those values.
My problem is to practice what I theoretically know, especially using R.
My linear model is the following :
LinearModel.1 <- lm(GDP.per.head ~ Competitivness.score + Quality.score, data=Dataset)
summary(LinearModel.1)
predict(LinearModel.1, se.fit = FALSE, scale = NULL, df = Inf,interval = c("none", "confidence", "prediction"),level = 0.95, type = c("response", "terms"),terms = NULL)
Could you please help me with my R codes ?
Thanks for your precious help,
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