Markov matrix - meaning and definition. What is Markov matrix
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What (who) is Markov matrix - definition

MATRIX USED TO DESCRIBE THE TRANSITIONS OF A MARKOV CHAIN
Transition probability matrix; Markov transition matrix; Markov matrix; Stachastic matrix; Right stochastic matrix; Left stochastic matrix; Markov Matrices; Markov matrices; Probability matrix; Stochastic matrices; Stochastic operator
  • [[Andrey Markov]] in 1886

Stochastic matrix         
In mathematics, a stochastic matrix is a square matrix used to describe the transitions of a Markov chain. Each of its entries is a nonnegative real number representing a probability.
Markov process         
  • Russian mathematician [[Andrey Markov]]
STOCHASTIC MODEL DESCRIBING A SEQUENCE OF POSSIBLE EVENTS IN WHICH THE PROBABILITY OF EACH EVENT DEPENDS ONLY ON THE STATE ATTAINED IN THE PREVIOUS EVENT
Markov process; Markov sequence; Markov chains; Markov analysis; Markovian process; Markovian property; Markov predictor; Markoff chain; Markov Chain; Markoff Chain; Transition probabilities; Absorbing state; Markov Chaining; Equilibrium distribution; Markov-Chain; Markhow chain; Irreducible Markov chain; Transition probability; Markov Chains; Homogeneous Markov chain; Markov Processes; Markov Sequences; Markov Process; Markovian chain; Embedded Markov chain; Positive recurrent; Transition density; Transitional probability; Markov text generators; Markov text; Applications of Markov chains
<probability, simulation> A process in which the sequence of events can be described by a Markov chain. (1995-02-23)
Markov chain         
  • Russian mathematician [[Andrey Markov]]
STOCHASTIC MODEL DESCRIBING A SEQUENCE OF POSSIBLE EVENTS IN WHICH THE PROBABILITY OF EACH EVENT DEPENDS ONLY ON THE STATE ATTAINED IN THE PREVIOUS EVENT
Markov process; Markov sequence; Markov chains; Markov analysis; Markovian process; Markovian property; Markov predictor; Markoff chain; Markov Chain; Markoff Chain; Transition probabilities; Absorbing state; Markov Chaining; Equilibrium distribution; Markov-Chain; Markhow chain; Irreducible Markov chain; Transition probability; Markov Chains; Homogeneous Markov chain; Markov Processes; Markov Sequences; Markov Process; Markovian chain; Embedded Markov chain; Positive recurrent; Transition density; Transitional probability; Markov text generators; Markov text; Applications of Markov chains
<probability> (Named after Andrei Markov) A model of sequences of events where the probability of an event occurring depends upon the fact that a preceding event occurred. A Markov process is governed by a Markov chain. In simulation, the principle of the Markov chain is applied to the selection of samples from a probability density function to be applied to the model. Simscript II.5 uses this approach for some modelling functions. [Better explanation?] (1995-02-23)

Wikipedia

Stochastic matrix

In mathematics, a stochastic matrix is a square matrix used to describe the transitions of a Markov chain. Each of its entries is a nonnegative real number representing a probability.: 9–11  It is also called a probability matrix, transition matrix, substitution matrix, or Markov matrix.: 9–11  The stochastic matrix was first developed by Andrey Markov at the beginning of the 20th century, and has found use throughout a wide variety of scientific fields, including probability theory, statistics, mathematical finance and linear algebra, as well as computer science and population genetics.: 1–8  There are several different definitions and types of stochastic matrices:: 9–11 

A right stochastic matrix is a real square matrix, with each row summing to 1.
A left stochastic matrix is a real square matrix, with each column summing to 1.
A doubly stochastic matrix is a square matrix of nonnegative real numbers with each row and column summing to 1.

In the same vein, one may define a stochastic vector (also called probability vector) as a vector whose elements are nonnegative real numbers which sum to 1. Thus, each row of a right stochastic matrix (or column of a left stochastic matrix) is a stochastic vector.: 9–11  A common convention in English language mathematics literature is to use row vectors of probabilities and right stochastic matrices rather than column vectors of probabilities and left stochastic matrices; this article follows that convention.: 1–8  In addition, a substochastic matrix is a real square matrix whose row sums are all 1. {\displaystyle \leq 1.}