Turkish Journal of Mathematics and Computer Science

Yazarlar: Bülent KARAKAŞ, Şenay BAYDAŞ

Konular:Matematik

DOI:10.47000/tjmcs.797556

Anahtar Kelimeler:Convex polytope,Geometry,Manifold,Markov matrices

Özet: In probability theory and statistics, the term Markov property refers to the memoryless property of a stochastic process. It is named after the Russian mathematician Andrey Andreyevich Markov. Every Markov matrix gives a linear equation system, and the solution of this equation system gives us a subset of $\mathbb{R}_{n}^{n}$. This paper presents the new manifold structure on the set of the Markov matrices. In addition, this paper presents the set of Markov matrices is drawable, and this gives geometrical interpretation to Markov matrices. For the proof, we use the one-to-one corresponding among $n \times n$ Markov matrices, the solution of linear equation system from derived Markov property, and the set of $(n-1)$-polytopes.

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