Document1 - WordPatrick Fiifi DadziePicture ToolsFileHomeInsertDesignLayoutReferencesMailingsReviewViewHelpGrammarlyFormatO Tell me what you want to do& ShareAnswer the following question below:a. Provide a general markov state diagram for the variable described.b. Assuming the below factor, A, affected the state in the table above, produce the statediagram for, A, and calculate the final state.25 20 .25 .3020 30 .25 3025 20 40 .1030 30 .10 30A =c. Discuss the significance of hidden markov chain in a historic data.Page 1 of 1O words+ 100%4) 10:02 PM Document1 - WordPicture ToolsPatrick Fiifi DadzieFileHomeInsertDesignLayoutReferencesMailingsReviewViewHelpGrammarlyFormatO Tell me what you want to do& ShareAn artificial intelligence system was design to forecast the financial trading market andpredict change based on observed variables from the business environment. A machinelearning model is to be designed in understand and forecast trends based on Markov chain.The variables to be observed are• Population(A)• Poverty rate(8)• Inflation (C)• Available resources(D)Theses variables can affect each other or impact upon one another.Pu Pa P AsP Pa ... P ... PP-Pu Pa.. P PsP PaThe matix P represent the general form of an state matrix.Pss .. PssBelow is a table of the variables with their effect on each other.ADA0.10.10.10.7B0.20.30.20.3C0.30.40.10.20.40.20.20.2Page 1 of 1O words+ 100%A O 9 4) 10:00 PM

Note: In transition probability matrix sum of any row probabilities must be equal to one to find…

Answer the following question below: a. Provide a general markov state diagram for the variable described. b. Assuming the below factor, A, affected the state in the table above, produce the state diagram for, A, and calculate the final state. 25 20 .25 .30 20 30 .25 .30 25 20 40 .10 30 30 .10 .30 A = c. Discuss the significance of hidden markov chain in a historic data.

Answer the following question below: a. Provide a general markov state diagram for the variable described. b. Assuming the below factor, A, affected the state in the table above, produce the state diagram for, A, and calculate the final state. 25 20 .25 .30 20 30 .25 .30 25 20 40 .10 30 30 .10 .30 A = c. Discuss the significance of hidden markov chain in a historic data.

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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Consider the Markov chain specified by the following transition diagram. a. Find the steady-state probabilities of all states. 0.4 b. If the initial state is 7, what is the expected 0.3 0.4 0.2 number of steps to reach state 1 or 3? 0.8 0.2 c. If at step 0 the system was in state 4, what is the probability that after step 3 it was in state 3 and after step 47 it was in state 3 again?
64. Employee training. All welders in a factory begin as apprentices. Every year the performance of each appren- tice is reviewed. Past records indicate that after each review, 10% of the apprentices are promoted to profes- sional welder, 20% are terminated for unsatisfactory per- formance, and the remainder continue as apprentices. (A) Draw a transition diagram. (B) Write the transition matrix. (C) What is the probability that an apprentice is promoted to professional welder within 2 years? Within 4 years?
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7. The following 4-state Markov model with constant intensities a, B and y is used to model a pension scheme for male members aged 55. Age is defined as age last birthday on January 1". The states are w: Active, a: Preserved Benefit, b: Drawing pension and d: Dead. The following data were collected over an observation period covering a single calendar year on 1000 male members of the above pension scheme, all of whom are aged 55: Total waiting time in state w: 800 years Total number of transfers from state w to state a: 200 Total number of transfers from state w to state b: 200 Total number of transfers from state w to state c: 20 Find the likelihood function L(a, B.y) for these data and hence find the maximum likelihood estimates of a,ß and y.
5. Explain what is meant by BLUE estimates and the Gauss-Markov theorem. Mathematics relevant proofs will be rewarded. [:
Suppose a two state experiment has the following transition matrix: 0.2] 0.4 0.8 P = 0.6 Answer the following questions: 1. Find P(2). ... ... ... ... ... 2. If the experiment is in state 1 on the first observation, what is the probability that it will be in state 2 on the third observation? ... ... 3. If the experiment is in state 1 on the first observation, what is the probability it is in state 2 on the next two observations? ...
60. The following is the transition probability matrix of a Markov chain with states 1, 2, 3, 4 P= .4 .2 .25 .2 .3 .2 .1 .2 .2 .4 25 50 .1 .4 .3 If Xo = 1 (a) find the probability that state 3 is entered before state 4; (b) find the mean number of transitions until either state 3 or state 4 is entered.
Please do the following questions with handwritten working out. Answer is in other image
Given a Markov chain whose transition matrix is given by 1 3 0 0 0.1 0.2 0.5 0.2 0.1 0.2 0.6 0.1 1 The probability of absorption into state 3 starting from state 2 is closest to а. 0.55 O b. 0.41 с. 0.5 d. None of the choices 2.
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What is the probability that those units in states 3 and 4 end up in each of the absorbing states?