Problem with predict.lm()

Since you passed a matrix to lm() and then a data.frame to predict(), predict can't match up what variables to use for the prediction so it falls back on the original data. This seems to work:

set.seed(42)
y <- rnorm(100)
X <- matrix(rnorm(100*10), ncol=10)
Xd <- data.frame(X)
lm <- lm(y~., Xd)
Xnew <- matrix(rnorm(100*20), ncol=10)
Xnewd <- data.frame(Xnew)
ynew <- predict(lm, newdata=Xnewd)
head(ynew)

1           2           3           4           5           6 
 0.35404067  0.14073495 -0.45442499  0.31065562 -0.02091366  0.25358175

head(predict(lm))

1           2           3           4           5           6 
 0.75474817  0.06024122 -0.27221466 -0.20344713  0.20218135 -0.24045859

-------------------------------------
David L Carlson
Department of Anthropology
Texas A&M University
College Station, TX 77840-4352

-----Original Message-----
From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Martin Spindler
Sent: Wednesday, April 29, 2015 9:21 AM
To: r-help at r-project.org
Subject: [R] Problem with predict.lm()

Dear all,
?
the following example somehow uses the "old data" (X) to make the predictions, but not the new data Xnew as intended.
?
y <- rnorm(100)
X <- matrix(rnorm(100*10), ncol=10)
lm <- lm(y~X)
Xnew <- matrix(rnorm(100*20), ncol=10)
ynew <- predict(lm, newdata=as.data.frame(Xnew)) #prediction in not made for Xnew
?
How can I foce predict.lm to use use the new data?
?
Thank you very much for your efforts in advance!
?
Best,
?
Martin

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