![P8.4 [Based on exercise 8.2 from Childers, 2nd ed.] Let Wn be an IID sequence of zero-mean Gaussian random variables with variance σ류. Define a discrete-time random process Xn-p Xn-1 + wn, n-1, 2, , where Xo-W) and p is a constant. (a) Find the mean function Hx(n). (b) Find the auto-correlation function Rx(n1,n2).](http://img.homeworklib.com/questions/0ca5fae0-bf4f-11ea-b343-0d7bef637698.png?x-oss-process=image/resize,w_560)
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P8.4 [Based on exercise 8.2 from Childers, 2nd ed.] Let Wn be an IID sequence of...
2. Suppose that {Yİだi are iid random variables such that P(Y-1) = p and P(Y,--1) =...
2. Suppose that {Yİだi are iid random variables such that P(Y-1) = p and P(Y,--1) = 1-p. Define the process (Xn)000 by the following recursive relationship Xo = 0 and -2 for n 2 1. Show that (a) (Xn)n=0 is a stationary discrete time Markov chain. (b) Find its state space S, and (c) Calculate its transition matrix P (making sure the entries in P are ordered consistently with the ordering you gave for S).
- Let {Xn} denote a sequence of iid random variables such that P(Xi = 1) =...
- Let {Xn} denote a sequence of iid random variables such that P(Xi = 1) = P(X1 = -1) = 1/2. Let Sn = X1 + X2 + ... + xn. (a) Find ES, and var(Sn); (b) Show that Sn is a martingale.
3. Let U1, U2,. be a sequence of independent Ber(p) random variables. Define Xo 0 and...
3. Let U1, U2,. be a sequence of independent Ber(p) random variables. Define Xo 0 and Xn+1-Xn +2Un-1, 1,2,.. (a) Show that X, n 0,1,2, is a Markov chain, and give its transition graph. (b) Find EX and Var(X) c)Give P(X
4. Let Z1, Z2,... be a sequence of independent standard normal random variables. De- fine Xo 0 and n=0, 1 , 2, . . . ....
4. Let Z1, Z2,... be a sequence of independent standard normal random variables. De- fine Xo 0 and n=0, 1 , 2, . . . . TL: n+1 , The stochastic process Xn,n 0, 1,2,3 is a Markov chain, but with a continuous state space. (a) Find EXn and Var(X). (b) Give probability distribution of Xn (c) Find limn oo P(X, > є) for any e> 0. (d) Simulate two realisations of the Markov process from n = 0 until...
13. Let X1, X2, ...,Xy be a sequence of independent and identically distributed discrete random variables,...
13. Let X1, X2, ...,Xy be a sequence of independent and identically distributed discrete random variables, each with probability mass function P(X = k)=,, for k = 0,1,2,3,.... emak (a) Find the expected value and the variance of the sample mean as = N&i=1X,. (b) Find the probability mass function of X. (c) Find an approximate pdf of X when N is very large (N −0).
Let Z1, Z2, . . . be a sequence of independent standard normal random variables. Define X0 = 0 and Xn+1 = (nXn + (Zn+1))...
Let Z1, Z2, . . . be a sequence of independent standard normal random variables. Define X0 = 0 and Xn+1 = (nXn + (Zn+1))/ (n + 1) , n = 0, 1, 2, . . . . The stochastic process {Xn, n = 0, 1, 2, } is a Markov chain, but with a continuous state space. (a) Find E(Xn) and Var(Xn). (b) Give probability distribution of Xn. (c) Find limn→∞ P(Xn > epsilon) for any epsilon > 0.
The answer is one of the following: Please be descriptive!! Thank you :) 2. Suppose that...
The answer is one of the
following:
Please be descriptive!! Thank
you :)
2. Suppose that {Y;R 1 are iid random variables such that PW = 1-p and PĢ--1-1-p Define the process (Xn)n-0 by the following recursive relationship Xo = 0 and for n 21. Show that (a) (Xn)2 is a stationary discrete time Markov chain, (b) Find its state space S, and (c) Calculate its transition matrix P (making sure the entries in P are ordered consistently with the...
iid Let X1,, X, ^ X~P for some unknown distribution P with continuous cdf F. Below...
iid Let X1,, X, ^ X~P for some unknown distribution P with continuous cdf F. Below we describe a ? test for the null and alternative hypotheses We divide the sample space into 5 disjoint subsets refered to as bins A1(-00,-2), A2 -(-2,-0.5), As -(-0.5,0.5), A4 (0.5,2) As -(2, oo). as functions of X, by Now, define discrete random variables For example, if Xi --0.1, then Xi є Аз and so Y;-3. In other words, Y, is the label of...
Problem 4 Define f(x) as follows θ2 -1<=x<0 1-θ2 0<=x>1 0 otherwise Let X1, … Xn be iid random variables with density f for some unknown θ...
Problem 4 Define f(x) as follows θ2 -1<=x<0 1-θ2 0<=x>1 0 otherwise Let X1, … Xn be iid random variables with density f for some unknown θ (0,1), Let a be the number of Xi which are negatives and b be the number of Xi which are positive. Total number of samples n = a+b. Find he Maximum likelihood estimator of θ? Is it asymptotically normal in this sample? Find the asymptotic variance Consider the following hypotheses: H0: X is...
7. Let X a be random variable with probability density function given by -1 < x < 1 fx(x) otherwise (a) Find the...
7. Let X a be random variable with probability density function given by -1 < x < 1 fx(x) otherwise (a) Find the mean u and variance o2 of X (b) Derive the moment generating function of X and state the values for which it is defined (c) For the value(s) at which the moment generating function found in part (b) is (are) not defined, what should the moment generating function be defined as? Justify your answer (d) Let X1,...
2. Suppose that {Yİだi are iid random variables such that P(Y-1) = p and P(Y,--1) = 1-p. Define the process (Xn)000 by the following recursive relationship Xo = 0 and -2 for n 2 1. Show that (a) (Xn)n=0 is a stationary discrete time Markov chain. (b) Find its state space S, and (c) Calculate its transition matrix P (making sure the entries in P are ordered consistently with the ordering you gave for S).
- Let {Xn} denote a sequence of iid random variables such that P(Xi = 1) = P(X1 = -1) = 1/2. Let Sn = X1 + X2 + ... + xn. (a) Find ES, and var(Sn); (b) Show that Sn is a martingale.
3. Let U1, U2,. be a sequence of independent Ber(p) random variables. Define Xo 0 and Xn+1-Xn +2Un-1, 1,2,.. (a) Show that X, n 0,1,2, is a Markov chain, and give its transition graph. (b) Find EX and Var(X) c)Give P(X
4. Let Z1, Z2,... be a sequence of independent standard normal random variables. De- fine Xo 0 and n=0, 1 , 2, . . . . TL: n+1 , The stochastic process Xn,n 0, 1,2,3 is a Markov chain, but with a continuous state space. (a) Find EXn and Var(X). (b) Give probability distribution of Xn (c) Find limn oo P(X, > є) for any e> 0. (d) Simulate two realisations of the Markov process from n = 0 until...
13. Let X1, X2, ...,Xy be a sequence of independent and identically distributed discrete random variables, each with probability mass function P(X = k)=,, for k = 0,1,2,3,.... emak (a) Find the expected value and the variance of the sample mean as = N&i=1X,. (b) Find the probability mass function of X. (c) Find an approximate pdf of X when N is very large (N −0).
The answer is one of the
following:
Please be descriptive!! Thank
you :)
2. Suppose that {Y;R 1 are iid random variables such that PW = 1-p and PĢ--1-1-p Define the process (Xn)n-0 by the following recursive relationship Xo = 0 and for n 21. Show that (a) (Xn)2 is a stationary discrete time Markov chain, (b) Find its state space S, and (c) Calculate its transition matrix P (making sure the entries in P are ordered consistently with the...
iid Let X1,, X, ^ X~P for some unknown distribution P with continuous cdf F. Below we describe a ? test for the null and alternative hypotheses We divide the sample space into 5 disjoint subsets refered to as bins A1(-00,-2), A2 -(-2,-0.5), As -(-0.5,0.5), A4 (0.5,2) As -(2, oo). as functions of X, by Now, define discrete random variables For example, if Xi --0.1, then Xi є Аз and so Y;-3. In other words, Y, is the label of...
7. Let X a be random variable with probability density function given by -1 < x < 1 fx(x) otherwise (a) Find the mean u and variance o2 of X (b) Derive the moment generating function of X and state the values for which it is defined (c) For the value(s) at which the moment generating function found in part (b) is (are) not defined, what should the moment generating function be defined as? Justify your answer (d) Let X1,...
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