Chapter 12Using masks

Masks refers to the temporary fixing of one or more parameters and optimizing over the rest. This can be very helpful when one parameter is a setting or control that we later wish to optimize. It can also be useful to fix a parameter to which the objective function is particularly sensitive. In this chapter, we explore this idea, noting that some tools allow such options.

12.1 An example

We return to our Hobbs weeds example with maximum likelihood estimation of the three logistic parameters plus the dispersion. That is, given a set of values of the growth of some quantity c12-math-0001, for example, density of weeds, at times c12-math-0002, we wish to maximize the product of terms of the form

12.1 equation

where

12.2 equation

(see Section 1.2)

Our parameters to adjust are again the c12-math-0005, c12-math-0006, and c12-math-0007, which here are ...

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