Weather simulation using stochastic modeling

InterviewQs

Weather simulation using stochastic modeling

Python Data Structures Arrays Markov Simulation Markov Chains Statistics

Forward this email to a friend or colleague and challenge them to solve it.

Hi, 

In a particular area, there are 2 types of weather: sunny and rainy. The following is observed across a couple year period.

  • Assuming it's sunny, the probability of the weather staying sunny the following day is 80%
  • Assuming it's sunny, the probability the weather will change from sunny to rainy is 20%
  • Assuming it's rainy, the probability the weather staying rainy the following day is 70%
  • Assuming it's rainy, the probability the weather will change from rainy to sunny is 30%

Given this information, create a transition matrix and run a simulation of the weather over a 1000 day period. Next, using your simulation results, estimate the stationary distribution.

If you need a refresher, here is a resource on Markov Chains.

Solution will be written in Python for premium users.



 

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