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2.48. Let S and T be exponentially distributed with rates λ and μ. Let U = min(S, T), V = max(S, ...
Let Xo and Xı be independent exponentially distributed random variables with re- spective parameters Ao and ^i, so that, P(Xi t)eAit, for t2 0, i = 0,1 Let 0 if Xo X1, N = 1 if X1X0, min{Xo, X1}, M = 1 - N, V = x{X0, X1}, and W = V -U = |X0 - X1]. and U max Verify that U XN and V XM, then find the following: (a) P(N 0, U > t), for t 2...
(5) Let X1,X2,,Xn be independent identically distributed (i.i.d.) random variables from 1.1 U(0,1). Denote V max{Xi,..., Xn) and W min{Xi,..., Xn] (a) Find the distributions and the densities and the distributions of each of V and W. (b) Find E(V) and E(W)
(5) Let X1,X2,,Xn be independent identically distributed (i.i.d.) random variables from 1.1 U(0,1). Denote V max{Xi,..., Xn) and W min{Xi,..., Xn] (a) Find the distributions and the densities and the distributions of each of V and W. (b)...
Suppose d machines are subject to failures and repairs. The failure times are exponentially distributed with parameter μ, and the repair times are exponentially distributed with parameter λ. Let x(t) denote the number of machines that are in satisfactory order at time t. If there is only one repairman, then under appropriate reasonable assumptions, X(t), t 2 0, is a birth and death process on {O, 1,..., d} with birth rates λχ-λ, 0 x < d, and death rates μΧ_xp,...
Let X be an exponentially distributed random variable with parameter λ. Prove that P(X > s + tK > t) P(X > s) for any S,12 0
Assume that a lifetime random variable (T) is exponentially distributed with the intensity λ > 0. 1. Determine conditional density of the residual lifetime, T - u, given that T u 2. Find conditional expectation, E [T|T > u]
The lifetime of a type-A bulb is exponentially distributed with parameter λ. The lifetime of a type-B bulb is exponentially distributed with parameter μ, where μ>λ>0. You have a box full of lightbulbs of the same type, and you would like to know whether they are of type A or B. Assume an a priori probability of 1/4 that the box contains type-B lightbulbs. Assume that λ=3 and μ=4. Find the LMS estimate of T2, the lifetime of another lightbulb...
Problem 6. Let V, W, and U be finite-dimensional vector spaces, and let T : V → W and S : W → U be linear transformations (a) Prove that if B-(Un . . . , v. . . . ,6) is a basis of V such that Bo-(Un .. . ,%) s a basis of ker(T) then (T(Fk+), , T(n)) is a basis of im(T) (b) Prove that if (w!, . . . ,u-, υ, . . . ,i)...
a) Let T be an exponentially distributed random variable with parameter l= 1. Let U be a uniformly distributed random variable. Use inversion to show how to calculate samples {tı, t2, ..} from samples {U1, U2, ..} of U. b) Use any software of your choice to estimate by Monte Carlo simulation: E[sin(tanh, LT))
2. Let X and Y be independent, exponentially distributed random variables where X has mean 1/λ and Y has mean 1/μ. (a) What is the joint p.d.f of X and Y? (b) Set up a double integral for determining Pt <X <Y) (c) Evaluate the above integral. (d) Which of the following equations true, and which are false? {Z > t} = {X > t, Y > t} (e) Compute P[Z> t) wheret 0. (f) Compute the p.d.f. of Z.
1. Consider a time T of a call duration. If it rains (under the event T is exponentially distributed with the parameter À-1/6. If it does not rain (under the event F), T is exponentially distributed with the parameter λ 1/2 The percentage of raining time is 0.3 (a) Find the PDF of Tand the expected value ET]. (b) Find the PDF of T given that B [T 6] 2. Random variables X and Yhave the joint PDF otherwise (a)...