On 17/12/2009, at 11:14 AM, whitaker m. (mw1006) wrote:
I have a much larger dataset than in my original email (attached -
price dependent upon weight, Clarity (different levels IF-SI2),
colour(levels D-L) and Cut (ideal-fair), and tried the regression
command:
diamond.lm<-lm(price~weight+IF+VVS1+VVS2+VS1+VS2+SI1+SI2+I1+I2+D+E
+F+G+H+I+J+K+L+ideal+excellent+very.good+good+fair,
data="Diamonds2.txt")
Error in eval(predvars, data, env) : invalid 'envir' argument
Which lead to the error message below the command. I have tried
searching for this, and assumed this was down to having categrocial
variables within the data, is this a correct assumption or am i
doing something else wrong? Apologies if this is a bit of a basic
question!
(a) You don't want the quote marks around the data argument. That is
the source
of the "invalid 'envir' argument" error.
(b) You are not using the power of R. ***Don't*** create your own
dummy variables;
let lm() do it for you. Learn something about how R works, for
crying out loud.
Essentially you should be doing something like
diamond.lm <- lm(price ~ weight + Clarity + colour + Cut, data =
Diamond.txt)
where price, weight, Clarity, colour, and Cut are columns of the data
frame
Diamond.txt. The columns price and weight should be numeric vectors;
Clarity,
colour, and Cut should be ***factors***.
It is slightly worrying that you refer to ``Diamond.txt''. That
``.txt'' suffix
would lead me to believe that ``Diamond.txt'' is a (text) file
containing your
data. If that is the case, this won't work. The ``data'' argument
to lm() must
be an ***R object***. You have to read the data file into an R
object before trying
to use the data in a call to lm(). Something like
Diamond <- read.table("Diamond.txt") # Note that you ***do*** want
to quote the file name.
Then
diamond.lm <- lm(price ~ weight + Clarity + colour + Cut, data =
Diamond)
should do what you want. The dummy variable encoding used will be
determined
by the (first) value of options()$contrasts, which by default i
contr.treatment.
Read up on factors and contrasts.
cheers,
Rolf Turner
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