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! Thanks again, Matthew ________________________________________ From: Nikhil Kaza [nikhil.l...@gmail.com] Sent: Wednesday, December 16, 2009 4:14 PM To: Petr PIKAL Cc: whitaker m. (mw1006); r-help@r-project.org Subject: Re: [R] Odp: Creating Dummy Variables in R I don't think R will complain, if you use the approach below. However, IF, VVS1 and VVS2 are linearly dependent. Better use the factor approach and define which factor should be the contrast Nikhil On 16 Dec 2009, at 10:12AM, Petr PIKAL wrote: > what commands did you use for regression > > I suppose > > lm(Price~Weight+IF+VVS1+VVS2, data=your.data) > > shall not complain if your.data is a data frame. > > Regards > Petr
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 "588,573.41" 5.02 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 "194,167.82" 4.26 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 "108,311.58" 4.17 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 "62,235.49" 4.09 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 "70,524.68" 4.05 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 "179,324.96" 4.02 0 0 0 0 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 "437,787.74" 4.01 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 "437,787.74" 4.01 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 "80,791.07" 4.01 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 "54,912.00" 4 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 "309,816.78" 3.58 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 "19,888.05" 3.5 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 "68,185.73" 3.14 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 "32,111.35" 3.12 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 "69,070.17" 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