Hi there, I was wondering whether someone would be able to help me separate these 2 in my mind regarding Chapter 29 on modelling. When I think of distributions from my previous studies (the CTs)... I get it! But sometimes it seems (to me) that this chapter (29) refers to Parameters and Variables as if they were the same thing?? Can someone give me a good example, maybe in a deterministic model setting as well as a stochastic model setting, to illustrate the difference between parameters and variables? Thanks Kris
There's no universally accepted distinction between the two, but you could think of a parameter as a value that doesn't change during the run of the model, whereas a variable will. For example, a parameter could be a particular mortality table. As the model is run, it's unlikely that the table will change. The values extracted from this table will of course change because the age of the policyholder will increase, and so policyholder age would be a good example of a variable. In a stochastic model you will want to identify which variable is to be modelled stochastically. For example, investment returns, interest rates or claim sizes.
