Steady State Probability Vector In Exercises 47-54, find the steady state probability vector for the matrix. An eigenvector v of an n × n matrix A is a steady state probability vector when A v = v and the components of v sum to 1. A = [ 0.7 0.1 0.1 0.2 0.7 0.1 0.1 0.2 0.8 ]
Steady State Probability Vector In Exercises 47-54, find the steady state probability vector for the matrix. An eigenvector v of an n × n matrix A is a steady state probability vector when A v = v and the components of v sum to 1. A = [ 0.7 0.1 0.1 0.2 0.7 0.1 0.1 0.2 0.8 ]
Solution Summary: The author explains the steady state probability vector for the given matrix: A=left[cc
Steady State Probability Vector In Exercises 47-54, find the steady state probability vector for the matrix. An eigenvector v of an
n
×
n
matrix A is a steady state probability vector when
A
v
=
v
and the components of v sum to 1.
A
=
[
0.7
0.1
0.1
0.2
0.7
0.1
0.1
0.2
0.8
]
Quantities that have magnitude and direction but not position. Some examples of vectors are velocity, displacement, acceleration, and force. They are sometimes called Euclidean or spatial vectors.
Finding a Steady State Matrix In Exercises 41-44,
find the steady state matrix X of the absorbing Markov
chain with matrix of transition probabilities P.
Find the equilibrium vector for the transition matrix.
0.70 0.10 0.20
0.10 0.80 0.10
0.10 0.35 0.55
The equilibrium vector is
(Type an integer or simplified fraction for each matrix element.)
Chapter 7 Solutions
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