I'm trying to understand what goes on in the process that nls() uses.
This converges without much drama:
> rate.nls <- nls(Dev ~ exp(rho * (T)) - exp(rho*Tmax - (Tmax - T)/del)+
+ lam , data = xx, trace = TRUE,
+ start = c(rho = 0.15, del = 7, lam = .02, Tmax = 30))
599.7841 : 0.15 7.00 0.02 30.00
4.69849 : 0.14673457 6.83443060 -0.01417782 29.94392535
0.06971343 : 0.14787121 6.75095966 -0.01281743 28.88851217
0.01197127 : 0.1460683 6.8334550 -0.0128118 30.1599472
0.008279834 : 0.14406976 6.92819920 -0.01281783 31.63914711
0.002267513 : 0.1437983 6.9426081 -0.0127973 31.9153204
0.002264977 : 0.14377323 6.94385235 -0.01279224 31.95091153
0.002264977 : 0.14378546 6.94326629 -0.01278643 31.95045828
0.002264977 : 0.14378124 6.94346882 -0.01278843 31.95065902
0.002264977 : 0.14378271 6.94339837 -0.01278772 31.95059050
If I make one parameter further away from optimum, I get this:
> rate.nls <- nls(Dev ~ exp(rho * (T)) - exp(rho*Tmax - (Tmax - T)/del)+
+ lam , data = xx, trace = TRUE,
+ nls.control(warnOnly = TRUE),
+ start = c(rho = 0.15, del = 7, lam = 1.02, Tmax = 30))
59.80968 : 0.15 7.00 1.02 30.00
4.69849 : 0.14673457 6.83443060 -0.01417782 29.94392535
0.06973771 : 0.14787046 6.75099517 -0.01281668 28.88853959
0.0119916 : 0.1460709 6.8333430 -0.0128098 30.1600040
0.008369133 : 0.14406664 6.92834092 -0.01281926 31.63978393
0.002267664 : 0.1438008 6.9424901 -0.0127959 31.9151258
0.002264977 : 0.1437771 6.9436655 -0.0127904 31.9507300
0.002264977 : 0.14378253 6.94340678 -0.01278781 31.95059843
0.002264977 : 0.1437849 6.9432936 -0.0127867 31.9504860
Warning message:
In nls(Dev ~ exp(rho * (T)) - exp(rho * Tmax - (Tmax - T)/del) + :
step factor 0.000488281 reduced below 'minFactor' of 0.000976562
There's no surprise that the traces will be different, but I can't
understand why the first iteration gives exactly the same result in
both cases. *Then* they diverge. What is the explanation? (Maybe if
I knew what the step factor refers to, it could be clearer but I
suspect it doesn't come in at that stage.)
I can't think of a way of making a minimal working example but I'd
guess that it's not necessary to explain the procedure. I could
supply my xx dataframe if it's indispensible to the explanation.
TIA
--
~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.
___ Patrick Connolly
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