[newbie] Want to perform some simple regressions.

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.p
Nonlinear 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 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

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What the problem you are trying to solve?