Paola,
It sounds like one or both of your exponents (v2_h and v5_h) are getting
too large. I tried fitting the model without those exponents, then I used
the estimates from that simpler model as starting parameters for the full
model, and it worked.
nov2hv5h <- nls(slope_pp2_mrna ~ ( (k1*v2_Kd*p1) / (v2_Kd + p1) ) *
( 1/(1 + (p6/v5_Kd)) ) - pp2_mrna,
data=Data_pp2_mrna, start=list(k1=1, v2_Kd=1, v5_Kd=1))
summary(nov2hv5h)
fm_pp2_mrna <- nls(slope_pp2_mrna ~ ( (k1*v2_Kd*p1^v2_h) /
(v2_Kd^v2_h + p1^v2_h) ) * ( 1/(1 + (p6/v5_Kd)^v5_h) ) - pp2_mrna,
data=Data_pp2_mrna, start=list(k1=3.3, v2_Kd=2.4, v2_h=1,
v5_Kd=1.2, v5_h=1))
summary(fm_pp2_mrna)
Jean
`·.,, ><(((º> `·.,, ><(((º> `·.,, ><(((º>
Jean V. Adams
Statistician
U.S. Geological Survey
Great Lakes Science Center
223 East Steinfest Road
Antigo, WI 54409 USA
From:
Paola Lecca <pllcc...@gmail.com>
To:
r-help@r-project.org
Date:
08/05/2011 09:44 AM
Subject:
[R] problemsn in using nls
Sent by:
r-help-boun...@r-project.org
Dear all,
I tried to use nls, but I got the following error
Error in numericDeriv(form[[3L]], names(ind), env) :
Missing value or an infinity produced when evaluating the model
Any suggestion?
Thanks,
Paola.
The code I wrote is
Data_pp2_mrna <- data.frame(
p1 = protein_1,
p6 = protein_6,
pp2_mrna = protein_2_mrna,
slope_pp2_mrna = stinemanSlopes(times,
protein_2_mrna)
)
fm_pp2_mrna <- nls(slope_pp2_mrna ~ ( (k1 * v2_Kd *p1^v2_h) / (
(v2_Kd^v2_h)
+ p1^v2_h ) ) * ( 1/(1 + (p6/v5_Kd)^v5_h) ) - pp2_mrna,
data = Data_pp2_mrna,
start = list(k1 = 1,
v2_Kd = 1,
v2_h = 1,
v5_Kd = 1,
v5_h = 1
))
The data are as follows
> Data_pp2_mrna
p1 p6 pp2_mrna slope_pp2_mrna
1 1.006 1.234 0.0000000 1.0183976996
2 2.235 0.693 0.5565718 1.2167043185
3 3.744 0.451 1.2300000 1.6962541888
4 4.222 0.441 2.6200000 2.7800000000
5 9.022 0.523 4.0100000 0.1298238635
6 11.326 0.845 3.9179535 -0.2048280861
7 6.899 0.674 3.8050000 -0.4595669210
8 10.709 1.369 3.3860000 -0.8380000000
9 14.084 1.646 2.9670000 -0.5032137310
10 14.922 2.561 2.8220000 -0.2900000000
11 14.340 2.265 2.6770000 -0.3555500152
12 13.066 4.832 2.4634792 -0.4859794757
13 17.553 5.651 2.1880000 -0.7700435122
14 14.803 6.418 1.6045000 -1.1670000000
15 11.945 10.343 1.0210000 -0.3160241819
16 11.427 9.415 1.0435000 0.0450000000
17 11.556 12.610 1.0660000 -0.1700195282
18 20.107 16.171 0.8545000 -0.4230000000
19 15.999 13.189 0.6430000 -0.1721421868
20 16.094 17.022 0.6635000 0.0410000000
21 11.752 14.723 0.6840000 -0.0911220974
22 15.841 15.887 0.5690000 -0.2300000000
23 12.601 15.604 0.4540000 -0.0022539547
24 13.598 18.202 0.5665000 0.2250000000
25 13.879 20.821 0.6790000 -0.0155566571
26 16.270 18.040 0.5490000 -0.2600000000
27 17.176 16.015 0.4190000 -0.1195632728
28 12.332 18.429 0.4250000 0.0120000000
29 12.373 17.723 0.4310000 -0.1118527520
30 14.781 23.100 0.3095000 -0.2430000000
31 17.578 15.396 0.1880000 0.0004440266
32 18.865 21.408 0.3100000 0.2440000000
33 14.735 14.518 0.4320000 0.0473462057
34 16.160 21.351 0.3610000 -0.1420000000
35 13.416 16.689 0.2900000 0.0424156026
36 13.864 17.015 0.4065000 0.2330000000
37 16.219 21.776 0.5230000 0.1567965535
38 13.249 17.371 0.5650035 0.0498847737
39 14.445 19.218 0.5730000 -0.0435396634
40 13.210 21.309 0.5211514 -0.1713939796
41 12.358 24.966 0.4000000 -0.3132118164
--
*Paola Lecca, PhD*
*The Microsoft Research - University of Trento*
*Centre for Computational and Systems Biology*
*Piazza Manci 17 38123 Povo/Trento, Italy*
*Phome: +39 0461282843*
*Fax: +39 0461282814*
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and provide commented, minimal, self-contained, reproducible code.
