Explore: Markov Spectrum

In mathematics, the Markov spectrum, devised by Andrey Markov, is a complicated set of real numbers arising in Markov Diophantine equations and also in

Gauss–Markov theorem Gauss–Markov process Markov blanket Markov boundary Markov chain Markov chain central limit theorem Additive Markov chain Markov additive

A Markov number or Markoff number is a positive integer x, y or z that is part of a solution to the Markov Diophantine equation x 2 + y 2 + z 2 = 3 x y

Gauss–Markov stochastic processes (named after Carl Friedrich Gauss and Andrey Markov) are stochastic processes that satisfy the requirements for both

mathematicians successfully formalizing contemporary mathematics. Markov spectrum Plünnecke–Ruzsa inequality Kneser's theorem (combinatorics) Freiman

that the conclusion holds for a set of denominators of density 1. Markov spectrum Rockett, Andrew M.; Szüsz, Peter (1992). Continued Fractions. World

The spectrum of a linear operator T {\displaystyle T} that operates on a Banach space X {\displaystyle X} is a fundamental concept of functional analysis

paper by Andrew D. Martin and Kevin M. Quinn. The Martin–Quinn score uses Markov chain Monte Carlo (MCMC) methods to fit a Bayesian model of ideal points

In number theory, specifically in Diophantine approximation theory, the Markov constant M ( α ) {\displaystyle M(\alpha )} of an irrational number α {\displaystyle

and business, such as finite probability spaces, matrix multiplication, Markov processes, finite graphs, or mathematical models. These topics were used