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Introduction to the Modeling and Analysis of Complex Systems

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5.3. COBWEB PLOTS FOR ONE-DIMENSIONAL ITERATIVE MAPS 69following:1. Draw a square on your paper. Label <strong>the</strong> bot<strong>to</strong>m edge as <strong>the</strong> axis for x t−1 , <strong>and</strong> <strong>the</strong>left edge as <strong>the</strong> axis for x t . Label <strong>the</strong> range <strong>of</strong> <strong>the</strong>ir values on <strong>the</strong> axes (Fig. 5.4).x maxx tx minx minx t-1x maxFigure 5.4: Drawing a cobweb plot (1).2. Draw a curve x t = f(x t−1 ) <strong>and</strong> a diagonal line x t = x t−1 within <strong>the</strong> square (Fig. 5.5).Note that <strong>the</strong> system’s equilibrium points appear in this plot as <strong>the</strong> points where <strong>the</strong>curve <strong>and</strong> <strong>the</strong> line intersect.3. Draw a trajec<strong>to</strong>ry from x t−1 <strong>to</strong> x t . This can be done by using <strong>the</strong> curve x t = f(x t−1 )(Fig. 5.6). Start from a current state value on <strong>the</strong> bot<strong>to</strong>m axis (initially, this is <strong>the</strong>initial value x 0 , as shown in Fig. 5.6), <strong>and</strong> move vertically until you reach <strong>the</strong> curve.Then switch <strong>the</strong> direction <strong>of</strong> <strong>the</strong> movement <strong>to</strong> horizontal <strong>and</strong> reach <strong>the</strong> left axis. Youend up at <strong>the</strong> next value <strong>of</strong> <strong>the</strong> system’s state (x 1 in Fig. 5.6). The two red arrowsconnecting <strong>the</strong> two axes represent <strong>the</strong> trajec<strong>to</strong>ry between <strong>the</strong> two consecutive timepoints.4. Reflect <strong>the</strong> new state value back on<strong>to</strong> <strong>the</strong> horizontal axis. This can be done as asimple mirror reflection using <strong>the</strong> diagonal line (Fig. 5.7). This completes one step<strong>of</strong> <strong>the</strong> “manual simulation” on <strong>the</strong> cobweb plot.

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