a) corresponds to catching a salmon
We want to find
This is given by the matrix element
b) We want to find
Which is
But
Which is
And
So the probability is
Required probability is is the probability that the next fish we catch will have length less than or equal to 15 cm given that the first fish was a salmon
1. Suppose that we catch either salmon (state 1) or sea bass (state 2) according to a Markov Model where the transition matrix is given by 0.8 0.2 A= 0.4 0.6 Suppose that we compare the length, x, of...
6. Suppose that fish come in two classes, salmon (class 1) and sea bass (class 2). We take a picture of a fish and measure its length, x, and wish to make a decision on the identity of the fish based on the value of x. Determine the decision regions in x for the Bayes classifier corresponding to the two classes under the following conditions (a) We assume that the class conditional densities are Gaussian with the following means, variances...
1. A Markov chain {X,,n0 with state space S0,1,2 has transition probability matrix 0.1 0.3 0.6 P=10.5 0.2 0.3 0.4 0.2 0.4 If P(X0-0)-P(X0-1) evaluate P[X2< X4]. 0.4 and P 0-2) 0.2. find the distribution of X2 and
Let Xn be a Markov chain with state space {0, 1, 2}, and transition probability matrix and initial distribution π = (0.2, 0.5, 0.3). Calculate P(X1 = 2) and P(X3 = 2|X0 = 0) 0.3 0.1 0.6 p0.4 0.4 0.2 0.1 0.7 0.2
(n)," 2 0) be the two-state Markov chain on states (. i} with transition probability matrix 0.7 0.3 0.4 0.6 Find P(X(2) 0 and X(5) X() 0)
-1,2,3,4,5,63 and transition matrix Consider a discrete time Markov chain with state space S 0.8 0 0 0.2 0 0 0 0.5 00 0.50 0 0 0.3 0.4 0.2 0.1 0.1 0 0 0.9 0 0 0 0.2 0 0 0.8 0 0.1 0 0.4 0 0 0.5 (a) Draw the transition probability graph associated to this Markov chain. (b) It is known that 1 is a recurrent state. Identify all other recurrent states. (c) How many recurrence classes are...
(2.) A discrete-tim e Markov chan X, E {0,1,2) has the following transition probability matrix: 0.1 0.2 0.7 P-10.8 0.2 0 0.1 0.8 0.1 Suppose Pr(Xo = 0) = 0.3, Pr(X,-1) = 0.4, and Pr(Xo = 2) = 0.3. Compute the following. .lrn( (a) Pr (X0-0, X,-2, X2-1). (b) Pr(X2-iXoj) for all i,j
P= 0.8 0.2 0 0 0 1 Jis the transition probability matrix of a Markov chain. Compute the steady-state probabilityes. (100) oli VIU VIGO VICE [ 5 1 11 [7 77
11. Consider a Markov process with transition matrix State 1 State 2 State 1 0.2 0.11 State 2 0.8 0.9 (a) What does the entry 0.2 represent? (b) What does the entry 0.1 represent? (c) If the system is in state 1 initially, what is the probability that it will be in state 2 at the next observation? (d) If the system has a 50% chance of being in state 1 initially, what is the probability that it will be...
thank you Consider a Markov chain with state space S - {1,2), with transition matrix 0.2 0.8 0.6 0.4 and initial state 1 (so Xo - 1 with probability 1). Decide which of the following is a stopping time: (a) Ti mintn 27: Xn 1 12 min{n > 1 : Xn+1-1) (c) T - min^n 2 2 Xn-1 1 (d) T4 - minfn 2 10: Xn - Xn-1)
1.13. Consider the Markov chain with transition matrix: 1 0 0 0.1 0.9 2 0 0 0.6 0.4 3 0.8 0.2 0 0 4 0.4 0.6 0 0 (a) Compute p2. (b) Find the stationary distributions of p and all of the stationary distributions ofp2. (c) Find the limit of p2n(x, x) as n → oo.