Hi all,

I am attempting to apply a nonlinear model developed using nls to a new dataset and assess the fit of that model. At the moment, I am using the fitted model from my fit dataset as the starting point for an nls fit for my test dataset (see below).  I would like to be able to view the t-statistic and p-values for each of the iterations using the trace function, but have not yet worked out how to do this.  Any other suggestions are also welcome.

Many thanks,

Rebecca

> model.wa <- nls(y ~ A*(x^B), start=list(A=107614,B=-0.415)) # create nls() power model for WA data
> summary(model.wa) # model summary

Formula: y ~ A * (x^B)

Parameters:
    Estimate Std. Error t value Pr(>|t|)
A  7.644e+04  1.240e+04   6.165 4.08e-06 ***
B -3.111e-01  4.618e-02  -6.736 1.15e-06 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 5605 on 21 degrees of freedom

Number of iterations to convergence: 6
Achieved convergence tolerance: 7.184e-06
  (6 observations deleted due to missingness)


> model.vic <- nls(y.vic ~ A*(x.vic^B), start = list(A = 7.644e+04, B = -3.111e-01), trace = T)
3430193778 :  76440.0000    -0.3111
2634092902 :  48251.9235397    -0.2552481
2614516166 :  27912.1921354    -0.1772322
2521588892 :  32718.3764594    -0.1862611
2521233646 :  32476.4536126    -0.1836836
2521230904 :  32553.0767231    -0.1841362
2521230824 :  32540.063480    -0.184059
2521230822 :  32542.2970040    -0.1840721




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