Differentiate between Stochastic and Deterministic model ?
- Here the output of the model is fully determined by the parameter values and initial conditions. This model assumes that its outcome is certain if input is fixed. No matter how many times one recalculates, one obtains exactly the same result.
- Good example is Linear programming. If we want to minimize the cost by selecting the decision how you want to transport the goods from one place to another , then you are dealing with deterministic model for every data.
- Stochastic models possess some inherent randomness. The same set of parameter values and initial conditions will lead to different outputs. Every time you run the model , you will get the different result.
- When you roll a die, you will get different results.
Note:For Building a stochastic model
Create the Sample space — a list of all possible outcomes,
Assign probabilities to sample space elements,
Identify the events of interest,
Calculate the probabilities for the events of interest.