Curve fitting in R using nls

Question

I'm trying to fit a curve over (the tail of) the following data:

 [1]   1   1   1   1   1   1   2   1   2   2   3   2   1   1   4   3   2  11   6   2  16   7  17  36
[25]  27  39  41  33  42  66  92 138 189 249 665 224 309 247 641 777 671 532 749 506 315 292 281 130
[49] 137  91  40  27  34  19   1

I'm using the following function in R to accomplish this:

nls(y~a*x*exp(-b*x^2),start=list(a=1,b=1),trace=TRUE)

However, I'm getting the following error:

3650202 : 1 1

Error in numericDeriv(form[[3L]], names(ind), env) : Missing value or an infinity produced when evaluating the model

When using the following, artificial values for x and y, everything works just fine:

y=x*exp(-.5*x^2)+rnorm(length(x),0,0.1)

x
  [1] 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60 0.65 0.70 0.75 0.80 0.85 0.90
 [20] 0.95 1.00 1.05 1.10 1.15 1.20 1.25 1.30 1.35 1.40 1.45 1.50 1.55 1.60 1.65 1.70 1.75 1.80 1.85
 [39] 1.90 1.95 2.00 2.05 2.10 2.15 2.20 2.25 2.30 2.35 2.40 2.45 2.50 2.55 2.60 2.65 2.70 2.75 2.80
 [58] 2.85 2.90 2.95 3.00 3.05 3.10 3.15 3.20 3.25 3.30 3.35 3.40 3.45 3.50 3.55 3.60 3.65 3.70 3.75
 [77] 3.80 3.85 3.90 3.95 4.00 4.05 4.10 4.15 4.20 4.25 4.30 4.35 4.40 4.45 4.50 4.55 4.60 4.65 4.70
 [96] 4.75 4.80 4.85 4.90 4.95 5.00
y
  [1] -0.080214106  0.075247488  0.076355116 -0.020087646  0.181314038  0.075832658  0.248303254
  [8]  0.364244010  0.453655908  0.347854869  0.514373164  0.384051249  0.618584696  0.515684390
 [15]  0.534737770  0.609279111  0.618936091  0.534443863  0.739118585  0.677679546  0.526011452
 [22]  0.645645150  0.578274968  0.589619834  0.476186241  0.621638333  0.601663144  0.535981735
 [29]  0.518434367  0.581735107  0.423872948  0.445335110  0.340884242  0.317121065  0.342683141
 [36]  0.278351104  0.402947372  0.429483276  0.276655872  0.108164828  0.389994138  0.372300257
 [43] -0.057320612  0.131271986  0.226212869  0.131171973  0.245970674  0.009926555  0.173465207
 [50]  0.141220590  0.280616078  0.108515613  0.117697407  0.130700771  0.058540888  0.251613512
 [57]  0.168094899 -0.058382571  0.123306762 -0.048605186 -0.010131767  0.076701962 -0.051982924
 [64]  0.058427540  0.144665070  0.063998841 -0.010495697  0.119868854  0.114447318  0.006759691
 [71]  0.025041761 -0.178145771  0.041547126  0.122084819  0.034283141  0.209140060  0.197024853
 [78] -0.005491966 -0.033260219 -0.028123314 -0.005775553 -0.040781462  0.090024896  0.116390743
 [85] -0.017811031  0.094039200 -0.147064060 -0.057249278  0.211587898 -0.066153592  0.032100332
 [92] -0.092756136 -0.125906598  0.136937364  0.046453010  0.002000336 -0.134047101  0.089748847
 [99] -0.019355567 -0.042158950  0.149594368

Can anyone point out what I'm doing wrong? Thanks for your help.

Entrance

Hard to say cause you provide only one vector (x or y?). An if you post sample data look at this question: #1265629 – Daedal

Marek: the vector posted is <pre>y</pre>. As you can see from the example, <pre>x</pre> should be a sequence from 0 to length(y). – Entrance

Answer 1

Well I found the answer to my problem. The starting values for the real data are completely different from the dummy values: a=500 and b=.1 result in a nice fit. Just thought it might be useful to mention that here.

Entrance