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Fori 2 1, let X G1/2 be distributed Geometrically with parameter 1/2. Ai G/ be distributed...
The answer .8414 was found to be incorrect Fori 2 1, let X G1/2 be distributed...
The answer .8414 was found to be incorrect
Fori 2 1, let X G1/2 be distributed Geometrically with parameter 1/2 Defin Vn Approximate P(-1 < < 2) with large enough n. Hint, note that Yn is not "properly" normalized 8414
Fori 2 1, let XiG1/2 be distributed Geometrically with parameter 1/2. Define Vn. i-1 Approximate P-1...
Fori 2 1, let XiG1/2 be distributed Geometrically with parameter 1/2. Define Vn. i-1 Approximate P-1 Yn < 2) with large enough n Hint, note that Yn is not "properly" normalized
For i 1, let X G1/2 be distributed Geometrically with parameter 1/2 Define Xi -2 Approximate...
For i 1, let X G1/2 be distributed Geometrically with parameter 1/2 Define Xi -2 Approximate P (-1 < -2) with large enough n.
Problem 41.3 Let X and Y be independent random variables each geometrically distributed with parameter p,...
Problem 41.3 Let X and Y be independent random variables each geometrically distributed with parameter p, i.e. p(1- p otherwise. Find the probability mass function of X +Y
8. Let X1...., X, be i.i.d. ~E(1) random variables (i.e., they are independent and identically distributed,...
8. Let X1...., X, be i.i.d. ~E(1) random variables (i.e., they are independent and identically distributed, all with the exponential distribution of parameter 1 = 1). a) Compute the cdf of Yn = min(X1,...,xn). b) How do P({Y, St}) and P({X1 <t}) compare when n is large and t is such that t<? c) Compute the odf of Zn = max(X1...., X.). d) How do P({Zn2 t}) and P({X1 2 t}) compare when n is large and t is such...
Suppose a system of ive components Ai,1 Si S 5 is arranged as follows 2 Assum e the lifetime of each component is exponentially distributed with parameter) and the components function independently....
Suppose a system of ive components Ai,1 Si S 5 is arranged as follows 2 Assum e the lifetime of each component is exponentially distributed with parameter) and the components function independently. Let of the i-th component, that is the random variable defined by (Xi - t) means that the the i-th component stops working at time t. Saying that Xi has an exponenti distribution with parameter X means X, be the lifetime random variable and P(Xi s t)-1-e*. be...
Question 6: Let n 2 2 be an integer and let ai,a2,...,an be a permutation of...
Question 6: Let n 2 2 be an integer and let ai,a2,...,an be a permutation of the set (1, 2, . . . ,n). Define ao = 0 and an+1 = 0, and consider the sequence do, 1, d2, l3, . . . , Un, Un+1 A position i with 1 i n is called auesome, if ai > ai-1 and ai > ai+1. In words, i is awesome if the value at position i is larger than both its...
2. Asymptotic Maximum Likelihood. 25 Let X1, ..., Xn be independently Poisson distributed with parameter 1,...
2. Asymptotic Maximum Likelihood. 25 Let X1, ..., Xn be independently Poisson distributed with parameter 1, i.e. fx, (x) = exto is X= 0, 1, 2, ... =0,1,2,... (a) Derive the maximum likelihood estimator în of 1 based on n measurements. 5 (b) Show that în is consistent. 5 (c) Is în (asymptotically) efficient? 5 (d) Derive the asymptotic distribution of vn(în – 1). 10
I don't understand a iii and b ii, What's the procedure of deriving the limit distribution? Thanks. 6. Extreme...
I don't understand a iii and b ii, What's the procedure of
deriving the limit distribution? Thanks.
6. Extreme values are of central importance in risk management and the following two questions provide the fundamental tool used in the extreme value theory. (a) Let Xi,... , Xn be independent identically distributed (i. i. d.) exp (1) random variables and define max(Xi,..., Xn) (i) Find the cumulative distribution of Zn (ii) Calculate the cumulative distribution of Vn -Zn - Inn (iii)...
2. Let X be an exponentially distributed random variable with parameter 1 = 2. Determine P(X...
2. Let X be an exponentially distributed random variable with parameter 1 = 2. Determine P(X > 4). 3. Let X be a continuous random variable that only takes on values in the interval [0, 1]. The cumulative distribution function of X is given by: F(x) = 2x² – x4 for 0 sxsl. (1) (a) How do we know F(x) is a valid cumulative distribution function? (b) Use F(x) to compute P(i sX så)? (c) What is the probability density...
The answer .8414 was found to be incorrect
Fori 2 1, let X G1/2 be distributed Geometrically with parameter 1/2 Defin Vn Approximate P(-1 < < 2) with large enough n. Hint, note that Yn is not "properly" normalized 8414
Fori 2 1, let XiG1/2 be distributed Geometrically with parameter 1/2. Define Vn. i-1 Approximate P-1 Yn < 2) with large enough n Hint, note that Yn is not "properly" normalized
For i 1, let X G1/2 be distributed Geometrically with parameter 1/2 Define Xi -2 Approximate P (-1 < -2) with large enough n.
Problem 41.3 Let X and Y be independent random variables each geometrically distributed with parameter p, i.e. p(1- p otherwise. Find the probability mass function of X +Y
8. Let X1...., X, be i.i.d. ~E(1) random variables (i.e., they are independent and identically distributed, all with the exponential distribution of parameter 1 = 1). a) Compute the cdf of Yn = min(X1,...,xn). b) How do P({Y, St}) and P({X1 <t}) compare when n is large and t is such that t<? c) Compute the odf of Zn = max(X1...., X.). d) How do P({Zn2 t}) and P({X1 2 t}) compare when n is large and t is such...
Suppose a system of ive components Ai,1 Si S 5 is arranged as follows 2 Assum e the lifetime of each component is exponentially distributed with parameter) and the components function independently. Let of the i-th component, that is the random variable defined by (Xi - t) means that the the i-th component stops working at time t. Saying that Xi has an exponenti distribution with parameter X means X, be the lifetime random variable and P(Xi s t)-1-e*. be...
Question 6: Let n 2 2 be an integer and let ai,a2,...,an be a permutation of the set (1, 2, . . . ,n). Define ao = 0 and an+1 = 0, and consider the sequence do, 1, d2, l3, . . . , Un, Un+1 A position i with 1 i n is called auesome, if ai > ai-1 and ai > ai+1. In words, i is awesome if the value at position i is larger than both its...
2. Asymptotic Maximum Likelihood. 25 Let X1, ..., Xn be independently Poisson distributed with parameter 1, i.e. fx, (x) = exto is X= 0, 1, 2, ... =0,1,2,... (a) Derive the maximum likelihood estimator în of 1 based on n measurements. 5 (b) Show that în is consistent. 5 (c) Is în (asymptotically) efficient? 5 (d) Derive the asymptotic distribution of vn(în – 1). 10
I don't understand a iii and b ii, What's the procedure of
deriving the limit distribution? Thanks.
6. Extreme values are of central importance in risk management and the following two questions provide the fundamental tool used in the extreme value theory. (a) Let Xi,... , Xn be independent identically distributed (i. i. d.) exp (1) random variables and define max(Xi,..., Xn) (i) Find the cumulative distribution of Zn (ii) Calculate the cumulative distribution of Vn -Zn - Inn (iii)...
2. Let X be an exponentially distributed random variable with parameter 1 = 2. Determine P(X > 4). 3. Let X be a continuous random variable that only takes on values in the interval [0, 1]. The cumulative distribution function of X is given by: F(x) = 2x² – x4 for 0 sxsl. (1) (a) How do we know F(x) is a valid cumulative distribution function? (b) Use F(x) to compute P(i sX så)? (c) What is the probability density...
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