The output from head() suggests that the first variable is YEAR.PBE and that the PBE data has gotten merged with the YEAR variable, probably because of some issue with the delimiters in use in the file you read in. You need to go back and look at the file that you loaded these data into R from. Here's the result of View(beef) as suggested by Patrick: % RFP = Retail food price index adjusted by the CPI (1947-1949 = 100) % RDINC = Index of real disposable income per capita (1947-1949 = 100) % CFO = Food consumption per capita index (1947-1949 = 100) % DINC = Disposable income per capita index (1947-1949 = 100) % CPO = Consumption of pork per capita (lbs)
% CBE = Consumption of beef per capita (lbs) % an economic analysis of price and/or consumption of beef and pork % annually from 1925 to 1941 together with other variables relevant to % Description: Price and consumption per capita of beef and pork Waugh, Graphic Analysis in Agricultural Economics,
% Story Names: Agricultural Economics Studies % Datafile Subjects: Agriculture, Economics, Consumer % Datafile Name: Agricultural Economics Studies P.S.: I read the file using beef=read.table("beef.txt", header = TRUE, sep = "\t", comment.char="%") and the file looks like the following: % Invalid type (NULL) for variable 'beef$PBEĬan you please give me some insight where the typo/error is lying? So I decided to try the followings but all have some errors: > lm(formula=PBE~YEAR,data=beef)Įrror in (formula = beef$PBE ~ beef$YEAR, = TRUE) : + DINC + CFO+RDINC+RFP+YEAR, data = beef)Įrror in eval(expr, envir, enclos) : object 'PBE' not found Following the tutorial in this link I think I should do something the following code: > lm(formula = PBE ~ CBE + PBO + CPO + PFO +
I want to create a multiple linear regression model for PBE depending on the other variables.
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