A 5-State Markov Chain Weather Model whose transition probabilites are inferred from pre-existing daily weather data (https://www.kaggle.com/datasets/ananthr1/weather-prediction) pertaining to Seattle, USA. Examples of state vectors at later steps are calculated, and the conditions for the Ergodic Theorem are examined. By numerical examination we conclude that the Ergodic Theorem does not apply, and there exist no stationary transition probabilites.
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A 5-State Markov Chain Weather Model whose transition probabilites are inferred from pre-existing daily weather data (https://www.kaggle.com/datasets/ananthr1/weather-prediction).
Gregoritsch3/Markov_Weather_Model
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A 5-State Markov Chain Weather Model whose transition probabilites are inferred from pre-existing daily weather data (https://www.kaggle.com/datasets/ananthr1/weather-prediction).
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