Use nonlinear regression to fit the von Bertalanffy function to these data. To get starting values, first guess at L∞ from the scatterplot to be a value larger than any of the observed values in the...

Use nonlinear regression to fit the von Bertalanffy function to these data. To get starting values, first guess at L∞ from the scatterplot to be a value larger than any of the observed values in the data. Next, divide both sides of (11.22) by the initial estimate of L∞, and rearrange terms to get just exp(−K(t − t0)) on the right of the equation. Take logarithms, to get a linear mean function, and then use ols for the linear mean function to get the remaining starting values. After getting the fitted model, draw the fitted mean function on your scatterplot.

Obtain a 95% confidence interval for L∞ using the large sample approximation, and using the bootstrap.