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Starting from a linear model1 = lm(temp~alt+sdist) i need to develop a prediction model, where new data will come in hand and predictions about temp will be made.

I have tried doing something like this:

model2 = predict.lm(model1, newdata=newdataset)

However, I am not sure this is the right way. What I would like to know here is, if this is the right way to go in order to make prediction about temp. Also I am a bit confused when it comes to the newdataset. Which values should be filled in etc.?

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    You can just use predict instead of predict.lm it will do the same thing. For the newdata you need a data.frame with the same predictors as the original model - in your case alt and sdist. Commented Mar 24, 2014 at 14:37
  • @JohnPaul ok i got this. the only difference is that my newdataset comes from a text file by read.table. So how what does this means? and how should i use the data.frame? Update your comment into an answer if you may Commented Mar 24, 2014 at 14:42
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    The object created by read.table will be a data.frame by default, so no worries there. So just do NewDataSet<-read.table(whatever) and then use NewDataSet in the predict() function and all should be well. This assumes that NewDataSet has columns named alt and sdist. Commented Mar 24, 2014 at 14:45
  • @JohnPaul Ok so i guess i am good since what you describing above is exactly what i have done. Is there any way to verify the predictions made though? Commented Mar 24, 2014 at 14:48

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I am putting everything from the comments into this answer.

1) You can use predict rather than predict.lm as predict will know your input is of class lm and do the right thing automatically.

2 The newdataset should be a data.frame with the same variables as your original predictors - in this case alt and sdist.

3) If you are bringing in you data using read.table by default it will create a data.frame. This assumes that the new data has columns named alt and sdist Then you can do:

NewDataSet<-read.table(whatever)
NewPredictions<- predict(model1, newdata=NewDatSet)

4) After you have done this if you want to check the predictions - you can do the following

summary(model1)

This will give you the intercept and the coefficients for alt and sdist NewDataSet[1,] This should give you the alt and sdist values for the first row, you can change the 1 in the bracket to be any row you want. Then use the information from summary(model1) to calculate what the predicted value should be using any method that you trust.

Finally use NewPredictions[1] to get what predict() gave you for the first row (or change the 1 to any other row)

Hopefully that should all work out.

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