An algorithm for constructing integral row stochastic matrices
Let $\textbf{M}_{n}$ be the set of all $n$-by-$n$ real matrices, and let $\mathbb{R}^{n}$ be the set of all $n$-by-$1$ real (column) vectors. An $n$-by-$n$ matrix $R=[r_{ij}]$ with nonnegative entries is called row stochastic, if $\sum_{k=1}^{n} r_{ik}$ is equal to 1 for all $i$, $(1\leq i \leq...
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Veröffentlicht in: | Journal of Mahani Mathematical Research Center 2022-01, Vol.11 (1), p.69-77 |
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Sprache: | eng |
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Zusammenfassung: | Let $\textbf{M}_{n}$ be the set of all $n$-by-$n$ real matrices, and let $\mathbb{R}^{n}$ be the set of all $n$-by-$1$ real (column) vectors. An $n$-by-$n$ matrix $R=[r_{ij}]$ with nonnegative entries is called row stochastic, if $\sum_{k=1}^{n} r_{ik}$ is equal to 1 for all $i$, $(1\leq i \leq n)$. In fact, $Re=e$, where $e=(1,\ldots,1)^t\in \mathbb{R}^n$. A matrix $R\in \textbf{M}_{n}$ is called integral row stochastic, if each row has exactly one nonzero entry, $+1$, and other entries are zero. In the present paper, we provide an algorithm for constructing integral row stochastic matrices, and also we show the relationship between this algorithm and majorization theory. |
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ISSN: | 2251-7952 2645-4505 |
DOI: | 10.22103/jmmrc.2021.13883.1089 |