Answered: Po O and Bi <0. The Gatuss-Markov… | bartleby

Elementary Linear Algebra (MindTap Course List)

Elementary Linear Algebra (MindTap Course List)

8th Edition

ISBN:9781305658004

Author:Ron Larson

Publisher:Ron Larson

Chapter2: Matrices

Section2.5: Markov Chain

Problem 47E: Explain how you can determine the steady state matrix X of an absorbing Markov chain by inspection.

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Question

5

2. Consider the following regression where typo, is the number of typing errors and hours, is the number of
hours spent in practicing:
typo, = Bo + Byhours, + u,, Var(u,|hours,) =
hours,
where it is known that Bo > 0 and B1 < 0. The Gauss-Markov assumptions other than the constant error
variance assumption hold.
(a) Draw a graph of typo on hours illustrating the heteroskedasticity in the above regression.
(b) Are the OLS estimates, Bo and B from the regression of typo on hours BLUE? Lf not. how would
you transform the regression equation so that you would get BLUE estimates by running OLS on the
transformed regression? Write down the transformed equation with homoskedasticity.

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Explain how you can determine the steady state matrix X of an absorbing Markov chain by inspection.
What are the difficulties in estimating the following model? Use as much detail as possible in answering this question while considering the Gauss-Markov assumptions and OLS estimator. Economic productivity = β0 + β1Unemployment + β2Innovation + θiControls + ei Where unemployment is the average unemployment rate of a country and innovation is an index of R&D performance.
1- The number of items produced in a factory during a week is known to be a randomvariable with mean 50● Using Markov's inequality, what can you say about the probability that this week'sproduction exceeds 75?● If the variance of one week's production is equal to 25, then using Chebyshev'sinequality, what can be said about the probability that this week's production isbetween 40 and 60?
In the simple linear regression model , the Gauss Markov ( classical ) assumptions guarantee that the OLS estimator of the unknown parameters is BLUE. Among those assumptions , in order to have consistency of the OLS estimator we need ( this is a question on the necessary condition ): Question 4Select one: a. we need that the errors are not correlated with each others and that they have zero mean b. we need that the errors are homoscedastic ( all have the same variance) c. we need that the residuals are not correlated with the explanatory variables and that the residuals have zero mean d. we need that the errors have zero mean and that they are not correlated with the regressors ( no endogeneity) e. we need that the errors are homoscedastic ( all have the same variance) and not correlated with each others ( no serial correlation)
1) Assuming you have a data matrix X that has n rows and p variables and you know both µ and Σ. How is (X- µ)‘Σ-1(X- µ) distributed? 2) Assuming that you don’t know the values of µ and Σ. How is the statistical distance distributed as n-p gets large?
Suppose you toss a six-sided die repeatedly until the product of the last two outcomes is equal to 12. What is the average number of times you toss your die? Construct a Markov chain and solve the problem.
Consider the problem of sending a binary message, 0 or 1, through a signal channelconsisting of several stages, where transmission through each stage is subject to a fixedprobability of error α. Suppose that X0 = 0 is the signal that is sent and let Xn, be thesignal that is received at the nth stage. Assume that {Xn} is a Markov chain with transitionprobabilities, Poo = P11 = 1- α and P01 = P10 = α, where 0 < α < 1.(a) Determine P {Xo = 0, X1 = 0, X2 = 0}, the probability that no error α occurs up tostage n = 2.(b) Determine the probability that a correct signal is received at stage 2.
The following are some applications of the Markovinequality of Exercise 29:(a) The scores that high school juniors get on the verbalpart of the PSAT/NMSQT test may be looked upon asvalues of a random variable with the mean μ = 41. Findan upper bound to the probability that one of the studentswill get a score of 65 or more.(b) The weight of certain animals may be looked uponas a random variable with a mean of 212 grams. If noneof the animals weighs less than 165 grams, find an upperbound to the probability that such an animal will weigh atleast 250 grams.
A cellphone provider classifies its customers as low users (less than 400 minutes per month) or high users (400 or more minutes per month). Studies have shown that 80% of people who were low users one month will be low users the next month, and that 70% of the people who were high users one month will high users next month. a. Set up a 2x2 stochastic matrix with columns and rows labeled L and H that displays these transitions b. Suppose that during the month of January, 50% of the customers are low users. What percent of customers will be low users in February? In March?
Suppose Xn is an IID Gaussian process, withµX[n]=1, and σ2 X[n]=1Now, another stochastic process Yn = Xn − Xn−1. Please find:(a) The mean µY (n).(b) The variance σ2Y (n).(c) The auto-correlation RY (n, k)
Suppose that a production process changes state according to a Markov chain on [25] state space S = {0, 1, 2, 3} whose transition probability matrix is given by a) Determine the limiting distribution for the process. b) Suppose that states 0 and 1 are “in-control,” while states 2 and 3 are deemed “out-of-control.” In the long run, what fraction of time is the process out-of-control?
Consider the OLS estimator β^j. Under the Gauss-Markov assumptions, a) the estimator has the properties stated in the other three possible answers. b) the estimator is consistent. c) the estimator is the best linear unbiased estimator. d) the estimator is asymptotically normally distributed.

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