A population growth model due to Cooke et alia [3]
describes the population y(t) at time t by the equation

For each set of parameter values, solve the problem using three values of the delay, namely T = 0.2,1.0, 2.4 , and plot the solutions on the same figure. Structures can be indexed, so this can be coded as
for i = 1:3 T = Delays(i); sol(i) = dde23('prob6f',T,3.5,[0, 25],opts); endOn exit from the loop, the solution for the first delay is sol(1).x,sol(1).y and so forth. Note that T must be communicated to prob6f as a parameter or global variable because it appears in the equation. In the code fragment it is communicated as a global variable along with the parameters of the data set. You should use tolerances more stringent than the defaults, e.g.,
opts = ddeset('RelTol',1e5,'AbsTol',1e8);You might find it interesting to compare your solutions with those of Figure 3 in [3]. The following figures show the solutions for two of the data sets. Obviously the delay has a profound effect on the solution.