Modifications

By modifying the original code, make the following 3 programs:

• Modification A
  
  1. Change MAXTIME to 10000. If you compile it with -o immig-emig, you can capture the output by.

         ./immig-emig > out1

     > is standard output redirection. It creates a file called out1, and all output goes in there.
     CAUTION: Make sure there is no existing file with the same name.

     Now plot the outputs with R.

     # R
     
     > source("/home/progClass/src/immig-emig/immig-emig.r")
     > plot.ie1("out1")
     > q()
     Save workspace image? [y/n/c]: n
     

  2. Modify the line
         seed = 456739853;
     to
         seed = time(NULL);
     Also add
         #include <time.h>

     Run this program a couple times, and repeat plotting. You now notice that every run results in different outputs.

• Modification B
  
  1. We want to run 10000 simulations and print out only the final population sizes (each line for each run). Set MAXTIME to 3000, beta to 0.12.

     The output should look like:

     23
     101
     12
     4
     14
     221
      :
      :
     

     Each line represents the final population size after time 3000 of each simulation run.
     So there should be 10000 lines.

  2. Make a histogram with R.

     # R
     
     > source("/home/progClass/src/immig-emig/immig-emig.r")
     > hist.ie("out2")
     > q()
     Save workspace image? [y/n/c]: n
     

• Modification C
  
  1. Starting from Modification B, make a program which prints out only the average final population size of 10000 runs. In other words, instead of printing out the population size after time 3000 for each run (Modification B), calculate the average of the final population sizes over 10000 runs, and print out only this single value. Set beta to 0.1.
  2. We want to make a program which calculate the average population size at time 200, 400, 600, .... 3000. For each time, run 10000 simulations. HINT: now we need to eliminate the symbolic constant MAXTIME, and use another variable which takes 200, 400, ....

     The output should look like
     

     time     AveN
     0        10
     200      14
     400      12
      :        :
      :        :
     3000     15
     

     Plot outputs with R (you can probably use the same R funcion as Modification A).

  3. Now run the above program by setting alpha = 0.1 and beta = 0.12