Pinglei Gao
2016-Oct-10  14:41 UTC
[R] Finding starting values for the parameters using nls() or nls2()
Thanks very much for your kindness help. I run your script then came out
lots of outputs and I also studied the solution you posted. Forgive my
ignorance, I still can't find the suitable starting values. Did I
misunderstand something?
Best,
Pinglei Gao
-----????-----
???: ProfJCNash [mailto:profjcnash at gmail.com] 
????: 2016?10?10? 10:41
???: Gabor Grothendieck; Pinglei Gao
??: Re: [R] Finding starting values for the parameters using nls() or
nls2()
I forgot to post the "solution" found by nlmrt:
nlmrt class object: x
residual sumsquares =  1086.8  on  15 observations
    after  5001    Jacobian and  6991 function evaluations
  name            coeff          SE       tstat      pval      gradient
JSingval
b0            5.3274e-14            NA         NA         NA  -6.614e+13
1.735e+16
b1               33.5574            NA         NA         NA      -3.466
11518
th           -0.00721203            NA         NA         NA      -740.8
0.004635
Note the singular values -- this is the worst SV(max)/SV(min) ratio I've
observed!
JN
ProfJCNash
2016-Oct-10  15:26 UTC
[R] Finding starting values for the parameters using nls() or nls2()
The key lines are library(nlmrt) test <- nlxb(expf2, start= c(b0=.1, b1=1, th=.1), trace=TRUE, data=cl) Thus I started with .1 1 and .1. The "solution" from nlxb, which is using analytic derivatives and a very aggressive Marquardt code to keep trying even in bad situations, was as you included below. Note that the singular values of the Jacobian are given (they are recorded on the same table as the parameters, but do NOT correspond to the parameters. The placement was simply a tidy place to put these numbers.) The ratio of these sv's is 1.735e+16/0.004635 or approx 4E+18, so the condition number of the traditional Gauss Newton approach is about 1E+37. Not a nice problem! You probably should reformulate. JN On 16-10-10 10:41 AM, Pinglei Gao wrote:> Thanks very much for your kindness help. I run your script then came out > lots of outputs and I also studied the solution you posted. Forgive my > ignorance, I still can't find the suitable starting values. Did I > misunderstand something? > > Best, > > Pinglei Gao > > -----????----- > ???: ProfJCNash [mailto:profjcnash at gmail.com] > ????: 2016?10?10? 10:41 > ???: Gabor Grothendieck; Pinglei Gao > ??: Re: [R] Finding starting values for the parameters using nls() or > nls2() > > I forgot to post the "solution" found by nlmrt: > > nlmrt class object: x > residual sumsquares = 1086.8 on 15 observations > after 5001 Jacobian and 6991 function evaluations > name coeff SE tstat pval gradient > JSingval > b0 5.3274e-14 NA NA NA -6.614e+13 > 1.735e+16 > b1 33.5574 NA NA NA -3.466 > 11518 > th -0.00721203 NA NA NA -740.8 > 0.004635 > > > Note the singular values -- this is the worst SV(max)/SV(min) ratio I've > observed! > > JN > > >