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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