CODEWITHSUNDEEP
r
user3292755
user3292755

Reputation: 423

trouble using lm function regression using R

  No  Issuer     LR1     LR2      LR3       LR4      LR5     DR1
  1  CompanyA 1.41470 1.32430 -0.16422 139.30633  8.49702 0.85071
  2  CompanyB 1.44627 0.42427  0.40415   8.77173  6.66632 0.53576
  3  CompanyC 1.54267 1.52505  0.81449 261.21500 35.86433 0.53681
  4  CompanyD 3.64603 2.70640  2.32230 107.33922  1.79202 0.48101
  5  CompanyE 1.00592 0.98415  0.78911  82.44725 27.00442 0.68071
  6  CompanyF 2.59738 1.70374  0.92933 145.01431  1.81996 0.43577
      DR2     DR3      AR1      AR2     AR3     AR4     AR5     PR1     PR2     PR3
 5.84882 0.60382  2.62012  8.49702 4.68022 0.51531 0.00822 0.06236 0.05199 0.01595
 1.15546 0.33039 41.61093  6.66632 4.04257 2.24779 0.00677 0.06957 0.00083 0.00301
 1.16084 0.40417  1.39732 35.86433 0.32469 0.21293 0.04110 0.33770 0.25534 0.19301
 0.92684 0.38246  3.40043  1.79202 1.10595 0.46242 0.03522 0.41886 0.14047 0.07617
 2.13194 0.60695  4.42707 27.00442 0.23780 0.19290 0.05958 0.42816 0.39135 0.30883
 1.00352 0.33506  2.51699  1.81996 1.07226 0.46796 0.04559 0.24596 0.16839 0.09742
       PR4     PR5     PR6      PR7     RR1     RR2 Rating
 -0.26783 0.00822 0.05651 -0.13802 0.00822 0.05651      4
  0.03071 0.00677 0.01460  0.06903 0.00677 0.01460      3
  0.02213 0.04110 0.08887  0.00471 0.04110 0.08887      3
  0.23080 0.03522 0.06787  0.10673 0.03522 0.06787      3
  0.09979 0.05958 0.18659  0.01925 0.05958 0.18659      3
  0.10664 0.04559 0.10498  0.04990 0.04559 0.10498      3

Above is from the head(data) using R. I wanted to use SVM, but before doing so, i want to regress the data. The Y is "Rating" variable, located in the last column, the rest is X which are LR1,LR2,...,RR1,RR2. Here is my steps :

x <- data[,3:24]
y <- data[,25]
lm <- (y~x)

but this is what i get from the warning

Error in model.frame.default(formula = y ~ x, drop.unused.levels = TRUE) : 
  invalid type (list) for variable 'x'

I have tried couple of times , including using the data.frame(x) first, but the result are the same. The "Rating" variable determines the performance of the company, Rating 1 is the best performance while 4 is the worst performance. Why i get such trouble? Please help thank you

Upvotes: 3

Views: 118

Answers (2)

user2038587
user2038587

Reputation: 21

attach(data)
reg <- lm(Rating ~ LR1 + LR2 + ... + RR2, data=data)

Or you can separate the X and Y.

x <- LR1+LR2+ ... + RR2
y <- Rating
reg <- lm(y~x, data=data)

Upvotes: 1

Gopala
Gopala

Reputation: 10483

You can regress one variable against all the others by using the 'dot' notation like below:

fit <- lm(Rating ~ ., data = data)

Upvotes: 6

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