A Long-term Prediction of Covid-19 by Building a Transition Probability Matrix

Author(s)	Biplob Saikia
Country	India
Abstract	The outbreak of the covid-19 pandemic caused a devastating scenario in the human lives for a long period of time. Since the outbreak of the pandemic, many researchers have published papers on the prediction of covid-19 using machine learning techniques, artificial intelligence, statistical techniques such as regression analysis, Markov chain models etc. In this paper a transition probability matrix is introduced by building a first order Markov chain. This first order Markov chain is built by generating sequences from the data. Later with the help of Chapman Kolmogorov theorem and ergodic theorem, higher order transition probabilities and limiting probabilities are obtained.
Keywords	Covid-19, transition probabilities, Markov chain, ergodic theorem
Field	Mathematics > Statistics
Published In	Volume 5, Issue 3, May-June 2023
Published On	2023-06-29
Cite This	A Long-term Prediction of Covid-19 by Building a Transition Probability Matrix - Biplob Saikia - IJFMR Volume 5, Issue 3, May-June 2023. DOI 10.36948/ijfmr.2023.v05i03.3850
DOI	https://doi.org/10.36948/ijfmr.2023.v05i03.3850
Short DOI	https://doi.org/gsd5b5

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