Thomas Baruchel
2005-Aug-28 07:48 UTC
[R] [newbie] Want to perform some simple regressions.
Hi, I am a very newbie to R, and also have no knowledge concerning statistics. Nevertheless I think R might be the right software for a very specific number theory problem I sometime have. Studying some properties, I often get sequences of real numbers (let's call them y, the index x being 0, 1, 2, 3, 4, ...). For instance the list below. After a quick look, it seems that the sequence below is very close to something like (a.x + b) ln (c.x + d) but I didn't manage to find something very good for (a,b,c,d). My number theory software (maxima and pari/gp) don't seem to be much helpful for this. Is R the right choice ? Please, could you step by step show me how you would do on this example (data below) in order to let me do it on other examples. It would be very nice to join a script of the session since I don't know yet the syntax of R commands. Regards, -- Thomas Baruchel
Thomas Baruchel
2005-Aug-28 07:51 UTC
[R] [newbie] Want to perform some simple regressions.
On Sun, Aug 28, 2005 at 09:48:15AM +0200, Thomas Baruchel wrote:> Is R the right choice ? Please, could you step by step show me > how you would do on this example (data below) in order to let meI forgot my data :-( 0 2.205954909440447 1 8.150580118785099 2 15.851323727378597 3 22.442795956953574 4 29.358579800271354 5 36.46060528847214 6 43.7516923268591 7 51.223688311610026 8 58.86610205087116 9 66.66821956399055 10 74.61990268453171 11 82.71184423952718 12 90.93560520053082 13 99.28356700194489 14 107.74885489906521 15 116.3252559311549 16 125.00714110112291 17 133.78939523822717 18 142.6673553086964 19 151.63675679510055 20 160.69368733376777 21 169.834546691509 22 179.05601219606618 23 188.35500882314003 24 197.72868324657364 25 207.17438125936408 26 216.68962806440814 27 226.2721110130965 28 235.9196644372003 29 245.63025627606442 30 255.40197624835042 31 265.23302535689197 32 275.12170654792556 33 285.06641637317705 34 295.0656375259694 35 305.1179321414606 36 315.2219357669857 37 325.3763519217964 38 335.5799471767038 39 345.8315466936063 40 356.13003017290697 41 366.4743281636434 42 376.8634186969678 43 387.2963242085816 44 397.77210871999046 45 408.2898752521091 46 418.8487634479048 47 429.44794738349896 48 440.08663354951693 49 450.76405898653184 50 461.479489560246 51 472.2322183636179 52 483.02156423451737 53 493.84687037869463 54 504.707503088911 55 515.6028505520102 56 526.5323217365377 57 537.4953453542455 58 548.4913688894654 59 559.5198576909147 60 570.5802941210067 61 581.6721767581994 62 592.7950196483222 63 603.9483516011882 64 615.1317155291274 65 626.3446678243708 66 637.5867777724806 67 648.8576269992603 68 660.1568089487967 69 671.4839283904737 70 682.838600952985 71 694.2204526835204 72 705.6291196304554 73 717.0642474479981 74 728.5254910213728 75 740.0125141112243 76 751.5249890160294 77 763.062596251391 78 774.6250242451752 79 786.2119690475241 80 797.8231340548524 81 809.4582297469931 82 821.1169734367211 83 832.7990890309349 84 844.5043068028273 85 856.2323631744205 Regards, -- Thomas Baruchel
Sean O'Riordain
2005-Aug-28 08:16 UTC
[R] [newbie] Want to perform some simple regressions.
Hi Thomas,
I'm not an expert - so I might use incorrect terminology, but
hopefully you'll get the picture!
Assuming that you've got your data in a .CSV file, you'd first read in
your data, where the first three lines might look like...
x,y
0,2.205954909440447
1,8.150580118785099
# load the info into a data.frame called mydata
mydata <- read.csv("mycsvfile.csv",header=TRUE)
# now "attach" to this data.frame, so that the internal
attach(mydata)
# now do the regression and store it in the object "myregr"
myregr <- lm(y~x)
# print out the info from myregr
myregr
# to get more info from myregr use the summary() method...
summary(myregr)
There is an enormous quantity of documentation available, though it
takes a little while to learn to use it properly and get the full
effectiveness from it...
I strongly recommend that you read the "Posting Guide"
http://www.R-project.org/posting-guide.html
which will help you.
For more information, have a look at the introduction to R; which is a
tad terse in places - so read it slowly :-)
Have a look also at the other documentation
http://www.r-project.org/other-docs.html
In particular I'd recommend John Maindonalds online book at
http://cran.r-project.org/other-docs.html
cheers!
Sean
On 28/08/05, Thomas Baruchel <archaiesteron at laposte.net>
wrote:> On Sun, Aug 28, 2005 at 09:48:15AM +0200, Thomas Baruchel wrote:
> > Is R the right choice ? Please, could you step by step show me
> > how you would do on this example (data below) in order to let me
>
> I forgot my data :-(
>
> 0 2.205954909440447
> 1 8.150580118785099
> 2 15.851323727378597
> 3 22.442795956953574
> 4 29.358579800271354
> 5 36.46060528847214
> 6 43.7516923268591
> 7 51.223688311610026
> 8 58.86610205087116
> 9 66.66821956399055
> 10 74.61990268453171
> 11 82.71184423952718
> 12 90.93560520053082
> 13 99.28356700194489
> 14 107.74885489906521
> 15 116.3252559311549
> 16 125.00714110112291
> 17 133.78939523822717
> 18 142.6673553086964
> 19 151.63675679510055
> 20 160.69368733376777
> 21 169.834546691509
> 22 179.05601219606618
> 23 188.35500882314003
> 24 197.72868324657364
> 25 207.17438125936408
> 26 216.68962806440814
> 27 226.2721110130965
> 28 235.9196644372003
> 29 245.63025627606442
> 30 255.40197624835042
> 31 265.23302535689197
> 32 275.12170654792556
> 33 285.06641637317705
> 34 295.0656375259694
> 35 305.1179321414606
> 36 315.2219357669857
> 37 325.3763519217964
> 38 335.5799471767038
> 39 345.8315466936063
> 40 356.13003017290697
> 41 366.4743281636434
> 42 376.8634186969678
> 43 387.2963242085816
> 44 397.77210871999046
> 45 408.2898752521091
> 46 418.8487634479048
> 47 429.44794738349896
> 48 440.08663354951693
> 49 450.76405898653184
> 50 461.479489560246
> 51 472.2322183636179
> 52 483.02156423451737
> 53 493.84687037869463
> 54 504.707503088911
> 55 515.6028505520102
> 56 526.5323217365377
> 57 537.4953453542455
> 58 548.4913688894654
> 59 559.5198576909147
> 60 570.5802941210067
> 61 581.6721767581994
> 62 592.7950196483222
> 63 603.9483516011882
> 64 615.1317155291274
> 65 626.3446678243708
> 66 637.5867777724806
> 67 648.8576269992603
> 68 660.1568089487967
> 69 671.4839283904737
> 70 682.838600952985
> 71 694.2204526835204
> 72 705.6291196304554
> 73 717.0642474479981
> 74 728.5254910213728
> 75 740.0125141112243
> 76 751.5249890160294
> 77 763.062596251391
> 78 774.6250242451752
> 79 786.2119690475241
> 80 797.8231340548524
> 81 809.4582297469931
> 82 821.1169734367211
> 83 832.7990890309349
> 84 844.5043068028273
> 85 856.2323631744205
>
> Regards,
>
> --
> Thomas Baruchel
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide!
http://www.R-project.org/posting-guide.html
>
try 'nls' Here is your data applied to it. It looks like you had an 'exact' fit:> x.1[1:10,]V1 V2 1 0 2.205955 2 1 8.150580 3 2 15.851324 4 3 22.442796 5 4 29.358580 6 5 36.460605 7 6 43.751692 8 7 51.223688 9 8 58.866102 10 9 66.668220> x.p <- nls(V2 ~ (a*V1+b)*log(c*V1+d),x.1,start=list(a=1,b=1,c=1,d=1)) > x.pNonlinear regression model model: V2 ~ (a * V1 + b) * log(c * V1 + d) data: x.1 a b c d 1.994722 6.807986 1.495003 1.301922 residual sum-of-squares: 1.006867 On 8/28/05, Thomas Baruchel <archaiesteron at laposte.net> wrote:> On Sun, Aug 28, 2005 at 09:48:15AM +0200, Thomas Baruchel wrote: > > Is R the right choice ? Please, could you step by step show me > > how you would do on this example (data below) in order to let me > > I forgot my data :-( > > 0 2.205954909440447 > 1 8.150580118785099 > 2 15.851323727378597 > 3 22.442795956953574 > 4 29.358579800271354 > 5 36.46060528847214 > 6 43.7516923268591 > 7 51.223688311610026 > 8 58.86610205087116 > 9 66.66821956399055 > 10 74.61990268453171 > 11 82.71184423952718 > 12 90.93560520053082 > 13 99.28356700194489 > 14 107.74885489906521 > 15 116.3252559311549 > 16 125.00714110112291 > 17 133.78939523822717 > 18 142.6673553086964 > 19 151.63675679510055 > 20 160.69368733376777 > 21 169.834546691509 > 22 179.05601219606618 > 23 188.35500882314003 > 24 197.72868324657364 > 25 207.17438125936408 > 26 216.68962806440814 > 27 226.2721110130965 > 28 235.9196644372003 > 29 245.63025627606442 > 30 255.40197624835042 > 31 265.23302535689197 > 32 275.12170654792556 > 33 285.06641637317705 > 34 295.0656375259694 > 35 305.1179321414606 > 36 315.2219357669857 > 37 325.3763519217964 > 38 335.5799471767038 > 39 345.8315466936063 > 40 356.13003017290697 > 41 366.4743281636434 > 42 376.8634186969678 > 43 387.2963242085816 > 44 397.77210871999046 > 45 408.2898752521091 > 46 418.8487634479048 > 47 429.44794738349896 > 48 440.08663354951693 > 49 450.76405898653184 > 50 461.479489560246 > 51 472.2322183636179 > 52 483.02156423451737 > 53 493.84687037869463 > 54 504.707503088911 > 55 515.6028505520102 > 56 526.5323217365377 > 57 537.4953453542455 > 58 548.4913688894654 > 59 559.5198576909147 > 60 570.5802941210067 > 61 581.6721767581994 > 62 592.7950196483222 > 63 603.9483516011882 > 64 615.1317155291274 > 65 626.3446678243708 > 66 637.5867777724806 > 67 648.8576269992603 > 68 660.1568089487967 > 69 671.4839283904737 > 70 682.838600952985 > 71 694.2204526835204 > 72 705.6291196304554 > 73 717.0642474479981 > 74 728.5254910213728 > 75 740.0125141112243 > 76 751.5249890160294 > 77 763.062596251391 > 78 774.6250242451752 > 79 786.2119690475241 > 80 797.8231340548524 > 81 809.4582297469931 > 82 821.1169734367211 > 83 832.7990890309349 > 84 844.5043068028273 > 85 856.2323631744205 > > Regards, > > -- > Thomas Baruchel > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html >-- Jim Holtman Convergys +1 513 723 2929 What the problem you are trying to solve?