![Problem 10: 10 points Suppose that (Xi, X2,... are independent identically distributed binary variables taking (0 1) values with probability PX here 0<q Introduce the new variable, M such that the event {M = k} occurs when three consecutive successes appear at the first time. In other words, event [M = kj, where k-3, occurs if and only if and there is no previous occurrence of three consecutive successes. Use conditioning techniques to derive the expected value, EM Hint: Recall that for the occurrence of the first success, Mi, we obtained E M]1 and for the first occurrence of two consecutive successes, M2, we derived that EA&J-q-2 +q-1](http://img.homeworklib.com/questions/fd234930-740e-11ea-be47-2f6126b12d4c.png?x-oss-process=image/resize,w_560)
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Problem 10: 10 points Suppose that (Xi, X2,... are independent identically distributed binary...
(a) Suppose that Xi, X2,... are independent and identically distributed random variables each taking the value...
(a) Suppose that Xi, X2,... are independent and identically distributed random variables each taking the value 1 with probability p and the value-1 with probability 1-p For n 1,2,..., define Yn -X1 + X2+ ...+Xn. Is {Yn) a Markov chain? If so, write down its state space and transition probability matrix. (b) Let Xı, X2, ues on [0,1,2,...) with probabilities pi-P(X5 Yn - min(X1, X2,.. .,Xn). Is {Yn) a Markov chain and transition probability matrix. be independent and identically distributed...
4. Let Xi i = 1,2, ... be independent and identically distributed (i.i.d.) Possion. That is...
4. Let Xi i = 1,2, ... be independent and identically distributed (i.i.d.) Possion. That is let Px;(k) = Px(k) = 2*24. Let Zn = ??=1 X; and find Pzn. Hint: use characteristic functions. n • Use Li=
3. Suppose X1, X2, -- are independent identically distributed random variables with mean 0 and va...
3. Suppose X1, X2, -- are independent identically distributed random variables with mean 0 and variance 1.Let Sn denote the partial sum Let Fn denote the information contained in Xi, .X,. Suppoe m n. (1) Compute El(Sn Sm)lFm (2) Compute ESm(Sn Sm)|F (3) Compute ES|]. (Hint: Write S (4) Verify that S -n is a martingale. [Sm(Sn Sm))2)
3. Suppose X1, X2, -- are independent identically distributed random variables with mean 0 and variance 1.Let Sn denote the partial sum...
2. [12 marksj Let Xi and X2 be independent and identically distributed random variables, each having...
2. [12 marksj Let Xi and X2 be independent and identically distributed random variables, each having an exponential distribution with density function (x),foro, 0, elsewbere Pdof W Let W = X1 +X2 and's Use the -method-of transformatiou- to find jhe joint probability density fuactíion of-W andy. AreWandfindependent?AThy? M covered m w, r 201 Instead tyto ind pdf of w b methed of colf
(3) Consider a sequence of independent and identically distributed random variables such that Xk-...
(3) Consider a sequence of independent and identically distributed random variables such that Xk-0, with common mean EĮXk] = 1. Define the Xi, X2, ,Xp, sequence k=1 (a) Compute E[ (b) Show that
(3) Consider a sequence of independent and identically distributed random variables such that Xk-0, with common mean EĮXk] = 1. Define the Xi, X2, ,Xp, sequence k=1 (a) Compute E[ (b) Show that
Let Xi, X2,... , Xn denote independent and identically distributed uniform random variables on the interval...
Let Xi, X2,... , Xn denote independent and identically distributed uniform random variables on the interval 10, 3β) . Obtain the maxium likelihood estimator for B, B. Use this estimator to provide an estimate of Var[X] when r1-1.3, x2- 3.9, r3-2.2
Let Xi,X2, , Xn be independent and identically distributed (ii.d.) Exponential(1) random variable...
Let Xi,X2, , Xn be independent and identically distributed (ii.d.) Exponential(1) random variables. 14] [41 (a) Find the method of moments estimator for X (b) Find the method of moments estimator for (c) Find the bias, variance and MSE (mean square erop) for the essimator in part () Total: [16]
Let Xi,X2, , Xn be independent and identically distributed (ii.d.) Exponential(1) random variables. 14] [41 (a) Find the method of moments estimator for X (b) Find the method of moments...
Question 4 [15 marks] The random variables X1,... , Xn are independent and identically distributed with...
Question 4 [15 marks] The random variables X1,... , Xn are independent and identically distributed with probability function Px (1 -px)1 1-2 -{ 0,1 fx (x) ; otherwise, 0 while the random variables Yı,...,Yn are independent and identically dis- tributed with probability function = { p¥ (1 - py) y 0,1,2 ; otherwise fy (y) 0 where px and py are between 0 and 1 (a) Show that the MLEs of px and py are Xi, n PY 2n (b)...
(a) Suppose that X1, X2,... are independent and identically distributed random variables each taking the value...
(a) Suppose that X1, X2,... are independent and identically distributed random variables each taking the value 1 with probability p and the value -1 with probability 1-p. For n = Yn-X1 + X2 + . . . + Xn. Is {Y, a Markov chain? If so, write down its state space and transition probability matrix 1, 2, . . ., denne
3. (a) (5 points) Let Xi,... be a sequence of independent identically distributed random variables e...
3. (a) (5 points) Let Xi,... be a sequence of independent identically distributed random variables e of tnduqendent idente onm the interval (o, 1] and let Compute the (almost surely) limit of Yn (b) (5 points) Let X1, X2,... be independent randon variables such that Xn is a discrete random variable uniform on the set {1, 2, . . . , n + 1]. Let Yn = min(X1,X2, . . . , Xn} be the smallest value among Xj,Xn. Show...
(a) Suppose that Xi, X2,... are independent and identically distributed random variables each taking the value 1 with probability p and the value-1 with probability 1-p For n 1,2,..., define Yn -X1 + X2+ ...+Xn. Is {Yn) a Markov chain? If so, write down its state space and transition probability matrix. (b) Let Xı, X2, ues on [0,1,2,...) with probabilities pi-P(X5 Yn - min(X1, X2,.. .,Xn). Is {Yn) a Markov chain and transition probability matrix. be independent and identically distributed...
4. Let Xi i = 1,2, ... be independent and identically distributed (i.i.d.) Possion. That is let Px;(k) = Px(k) = 2*24. Let Zn = ??=1 X; and find Pzn. Hint: use characteristic functions. n • Use Li=
3. Suppose X1, X2, -- are independent identically distributed random variables with mean 0 and variance 1.Let Sn denote the partial sum Let Fn denote the information contained in Xi, .X,. Suppoe m n. (1) Compute El(Sn Sm)lFm (2) Compute ESm(Sn Sm)|F (3) Compute ES|]. (Hint: Write S (4) Verify that S -n is a martingale. [Sm(Sn Sm))2)
3. Suppose X1, X2, -- are independent identically distributed random variables with mean 0 and variance 1.Let Sn denote the partial sum...
2. [12 marksj Let Xi and X2 be independent and identically distributed random variables, each having an exponential distribution with density function (x),foro, 0, elsewbere Pdof W Let W = X1 +X2 and's Use the -method-of transformatiou- to find jhe joint probability density fuactíion of-W andy. AreWandfindependent?AThy? M covered m w, r 201 Instead tyto ind pdf of w b methed of colf
(3) Consider a sequence of independent and identically distributed random variables such that Xk-0, with common mean EĮXk] = 1. Define the Xi, X2, ,Xp, sequence k=1 (a) Compute E[ (b) Show that
(3) Consider a sequence of independent and identically distributed random variables such that Xk-0, with common mean EĮXk] = 1. Define the Xi, X2, ,Xp, sequence k=1 (a) Compute E[ (b) Show that
Let Xi, X2,... , Xn denote independent and identically distributed uniform random variables on the interval 10, 3β) . Obtain the maxium likelihood estimator for B, B. Use this estimator to provide an estimate of Var[X] when r1-1.3, x2- 3.9, r3-2.2
Let Xi,X2, , Xn be independent and identically distributed (ii.d.) Exponential(1) random variables. 14] [41 (a) Find the method of moments estimator for X (b) Find the method of moments estimator for (c) Find the bias, variance and MSE (mean square erop) for the essimator in part () Total: [16]
Let Xi,X2, , Xn be independent and identically distributed (ii.d.) Exponential(1) random variables. 14] [41 (a) Find the method of moments estimator for X (b) Find the method of moments...
Question 4 [15 marks] The random variables X1,... , Xn are independent and identically distributed with probability function Px (1 -px)1 1-2 -{ 0,1 fx (x) ; otherwise, 0 while the random variables Yı,...,Yn are independent and identically dis- tributed with probability function = { p¥ (1 - py) y 0,1,2 ; otherwise fy (y) 0 where px and py are between 0 and 1 (a) Show that the MLEs of px and py are Xi, n PY 2n (b)...
(a) Suppose that X1, X2,... are independent and identically distributed random variables each taking the value 1 with probability p and the value -1 with probability 1-p. For n = Yn-X1 + X2 + . . . + Xn. Is {Y, a Markov chain? If so, write down its state space and transition probability matrix 1, 2, . . ., denne
3. (a) (5 points) Let Xi,... be a sequence of independent identically distributed random variables e of tnduqendent idente onm the interval (o, 1] and let Compute the (almost surely) limit of Yn (b) (5 points) Let X1, X2,... be independent randon variables such that Xn is a discrete random variable uniform on the set {1, 2, . . . , n + 1]. Let Yn = min(X1,X2, . . . , Xn} be the smallest value among Xj,Xn. Show...
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