nls麻烦:评估模型时产生的缺失值或无穷大

Question

我是一个R新手试图将植物光合作用光响应曲线(饱和,曲线)适合专家接受的特定模型.目标是获得Am,Rd和LCP的估计系数值.这是我一直得到的错误:

Error in numericDeriv(form[[3L]], names(ind), env) : 
  Missing value or an infinity produced when evaluating the model

我已多次切换起始值,但仍然没有运气.救命？提前谢谢你.下面的示例数据集.

photolrc= c(3.089753, 6.336478, 7.737142, 8.004812, 8.031599)
PARlrc= c(48.69624, 200.08539, 499.29840, 749.59222, 1250.09363)
curvelrc<-data.frame(PARlrc,photolrc)
curve.nlslrc = nls(photolrc ~ Am*(1-((1-(Rd/Am))^(1-(PARlrc/LCP)))),start=list(Am=(max(photolrc)-min(photolrc)),Rd=-min(photolrc),LCP= (max(photolrc)-1)))
coef(curve.nlslrc)

Answer 1

minpack.lm救援:

library(minpack.lm)
curve.nlslrc = nlsLM(photolrc ~ Am*(1-((1-(Rd/Am))^(1-(PARlrc/LCP)))),
                   start=list(Am=(max(photolrc)-min(photolrc)),
                              Rd=-min(photolrc),
                              LCP= (max(photolrc)-1)),
                   data = curvelrc)
coef(curve.nlslrc)
  #      Am         Rd        LCP 
  #8.011311   1.087484 -20.752957

plot(photolrc ~ PARlrc, data = curvelrc)
lines(0:1300, 
      predict(curve.nlslrc, 
              newdata = data.frame(PARlrc = 0:1300)))

如果你传递start = list(Am = 8, Rd = 1, LCP = -20)给nls你也可以获得成功.

考虑到背后的科学原因,我不知道参数值是否是合理的估计值.LCP可以消极吗？