如何使用r中的拟合模型预测相关值？

Question

I am fitting a model with:

var4pca <- lm(lg[5:415,1] ~ pcalg1$x[, 1:8] + pcalg2$x[, 1:8] + pcalg3$x[, 1:8] + pcalg4$x[, 1:8])

I now want to predict values for a validation set(83 rows). How can I do this?

I am trying to use:

pred_pca<-predict(var4pca, va)

where va is my validation set. But this is returning me a vector with length 411, whereas I only want length 83

Answer 1

In my experience, lm is very fussy about prediction. It demands that the new data look exactly like the data used to create the model. By that I mean things like col names have to match. What typically will work is to create a data frame of all the data and then create df.train and df.test as the correct rows of the data frame. That should do the trick. As joran says be careful with formulas. One advantage of putting all the data into a df with named cols is that then one can use the formula depvar ~. - typically much easier to write.