从 Fabens von Bertalanffy 生长曲线的 nls() 模型中获取预测值

如何解决从 Fabens von Bertalanffy 生长曲线的 nls() 模型中获取预测值

我有一个基于重新捕获的增长数据集。有一些列包含捕获长度、重新捕获长度和基于重新捕获减去捕获的时间（以年为单位）。

> str(data)
'data.frame':   60 obs. of  3 variables:
 $ sizecapture  : num  40.3 43 38.3 41.5 37.6 ...
 $ sizerecapture: num  43 48.7 39.5 42 46.7 43.5 43.5 47.2 45.7 59.9 ...
 $ timeinterval : num  0.945 1.036 0.997 0.997 2.471 ...

我正在关注 R 中的 Ogle 2013 小插图 (http://derekogle.com/fishR/examples/oldFishRVignettes/VonBertalanffyExtra.pdf)，用于尝试推导年龄大小的 Fabens 方法。对于这种方法，我不需要初始年龄（因为我根本不知道年龄）。我对推断不感兴趣，而只是估计我所测量的个体的年龄。

我可以轻松地按照说明计算通知 nls 模型所需的两个参数：k 和 Linf。我的目标是用增长数据创建一个年龄曲线，但是当我尝试 fitPlot 时出现错误。我收到错误“mdl$model[[gpos[2]]] 中的错误：下标越界”。我也试过曲线（）并得到错误“FVB1（x）中的错误：找不到函数“FVB1”。

我也不知道如何提取符合预测数据的置信区间。

我已经搜索并发现了一些类似的案例，但没有任何效果。我会继续研究，但我是否遗漏了一些非常基本的东西？下面是数据的子样本。我很感激任何帮助。

谢谢

install.packages("FSA")
install.packages("FSAdata")
install.packages("nlstools")
install.packages(car)

library(FSA)
library(FSAdata)
library(nlstools)
library(car)


sizecapture <- c(40.30,43.00,38.30,41.50,37.60,41.63,41.80,38.40,40.00,41.20,37.70,41.70,43.70,42.70,44.60,45.50,44.50,45.60,44.80,47.00,49.20,45.20,46.40,46.90,49.40,61.00,36.50,42.10,43.90,47.20,64.30,59.90,39.60,36.80)

sizerecapture < c(43.0,48.7,39.5,42.0,46.7,43.5,47.2,45.7,59.9,48.1,46.5,49.1,47.1,46.9,48.3,53.7,52.0,51.2,56.2,56.3,57.5,57.7,55.4,74.5,45.6,44.9,51.0,49.4,58.0,56.8,71.6,43.8,44.6,43.7,41.9)

timeinterval <-c(0.9452055,1.0356164,0.9972603,2.4712329,0.9534247,1.1945205,2.0027397,1.3178082,4.5342466,2.1863014,0.9178082,1.1315068,2.3698630,2.0575342,1.3835616,1.1726027,1.1972603,3.1698630,1.9589041,1.0712329,0.9150685,2.5671233,2.7780822,3.2000000,2.2246575,1.9150685,4.1753425,0.9287671,1.0328767,1.3945205,2.6739726,0.9205479,3.1479452,1.9506849,1.7178082,1.0520548,3.0767123,1.3726027,1.2520548)

data <- data.frame(sizecapture,sizerecapture,timeinterval)

### using Ogle 2013 to calculate Linf and k 

# k and Linf
with(data,mean((log(sizerecapture)-log(sizecapture))/timeinterval)) 
#0.0676`
max(data$sizerecapture) # largest size is 74.5
Fabens.sv <- list(Linf=74.5,K=0.0676)

# declare the model
fvb <- vbFuns("Fabens")

# fit and summarize
FVB1<- nls(sizerecapture~ 
fvb(sizecapture,timeinterval,Linf,K),start=Fabens.sv,data=data)
summary(FVB1,correlation=TRUE)

# confidence intervals through bootstrapping
boot <- nlsBoot(FVB1,niter=500)
confint(boot,plot=TRUE)

# plotting a fitted line plot 
ages2plot <- 0:40
LCI <- UCI <- numeric(length(ages2plot))
fitPlot(FVB1,xlim=range(ages2plot))
estes <- boot$coefboot
for (i in 1:length(ages2plot))  {
pv <-estes[,"Linf"]*(1-exp(-ests[,"K]*(ages2plot)))
LCI[i] <- quantile(pv,0.025)
UCI[i] <- quantile(pv,0.975)
}
lines(UCI~ages2plot,type="1")
lines(LCI~ages2plot,type="1")

# tried to just get a visual and errors arise
curve(FVB1)