1. The Weibull distribution has many applications in reliability engineering, survival analysis, and general insurance. function...
1. The Weibull distribution has many applications in reliability engineering, survival analysis, and general insurance. function Let p> 0, δ > 0. Consider the probability density x>0 zero otherwise. Find the probability distribution of w-x6 a) Determine the probability distribution of W by finding the c.d.f. of W, Fw(w). Find the cd.f. of X, Fx(x) = P(X x). “Hint', 1: u-substitution: u "Hint" 2: There is no such thing as a negative cumulative distribution function "Hint" 3: Should be Fx(0)-0,...
1. The Weibull distribution has many applications in reliability engineering, survival analysis, and general insurance. Let β > 0, δ > 0. Consider the probability density function x>0 zero otherwise. Find the probability distribution of W-X c Determine the probability distribution of W by finding the m.g.f. of W, Mw(t) Find the mgf. of w. Mw(t)-E(e, w )-E(e'x®). 1: u-substitution:v5 t X i) Hint -substitution:-»5. Hint', 2: Must have t< for the integral to converge . i What is the...
1. The Weibull distribution has many applications in reliability engineering, survival analysis, and general insurance. Let β > 0, δ > 0. Consider the probability density function x>0 zero otherwise. Find the probability distribution of W-X a Determine the probability distribution of W by finding the c.d.f. of W, F w(w). i Find the c.d.f. of X, Fx(x) "Hint" 1: u-substitution: u- "Hint" 2: "Hint" 3: Should be FX(0)-0, P(Xs) There is no such thing as a negative cumulative distribution...
1. The Weibull distribution has many applications in reliability engineering, survival analysis, and general insurance. Let β > 0, δ > 0. Consider the probability density function x>0 zero otherwise. Find the probability distribution of W-X b) Determine the probability distribution of W by finding the p.d.f. of W, /w(w). using the change-of-variable technique. Find the pd.f. of W. w(w)d ii) What is the name of the probability distribution of W? What are its parameters?
2- 5. The Weibull distribution has many applications in reliability engineering, survival analysis, and general insurance. Let B>0, 8>0. Consider the probability density function x>0 zero otherwise Recall (Homework #1) V-Χδ has an Exponential(8-T )-Gamma(u-l,e-1 ) distribution. Let X1, . , X/ be a random sample from the above probability distribution. y-ΣΧ.Σν i has a Gamma(u-n, θ- 1 ) distribution. !!! i-l 2. suppose δ is known. Let Xi, X2, , Xn be a random sample from the distribution with...
The Pareto probability distribution has many applications in economics, biology, and physics. Let β> 0 and δ> 0 be the population parameters, and let XI, X2, , Xn be a random sample from the distribution with probability density function zero otherwise. Suppose B is known Recall: a method of moments estimator of δ is δ = the maximum likelihood estimator of δ is δ In In X-in β has an Exponential (0--) distribution Suppose S is known Recall Fx(x) =...
Problem 1-5 1. If X has distribution function F, what is the distribution function of e*? 2. What is the density function of eX in terms of the densitv function of X? 3. For a nonnegative integer-valued random variable X show that 4. A heads or two consecutive tails occur. Find the expected number of flips. coin comes up heads with probability p. It is flipped until two consecutive 5. Suppose that PX- a p, P X b 1-p, a...
Please give detailed steps. Thank you. 2. Consider the following joint distribution of two discrete variables X and Y: fx,y(x, y) 01 2 3 お88 Recall that the marginal distribution of X is defined as: fx(x) and the marginal distribution of Y is defined as fy(v) -xf(i) Find fx(x) and fy(y) in the support of X and Y (or in simpler terms, find 1), P(Y = 0), P(Y-1), P(Y-2) and P(Y P(X-0), P(X 3)) b. The conditional density of Y...
1. Consider a continuous random variable X with the probability density function Sx(x) = 3<x<7, zero elsewhere. a) Find the value of C that makes fx(x) a valid probability density function. b) Find the cumulative distribution function of X, Fx(x). "Hint”: To double-check your answer: should be Fx(3)=0, Fx(7)=1. 1. con (continued) Consider Y=g(x)- 20 100 X 2 + Find the support (the range of possible values) of the probability distribution of Y. d) Use part (b) and the c.d.f....
2. A random variable has a probability density function given by: Bmx-(B+1) x20 x<m fx(x)= 10 where m>0 and B > 2. Let m and ß be constants; answer the questions in terms of m and B. (a) Find the cumulative distribution function (cdf) Fx(x) of this random variable; (b) Find the mean of X; (c) Find E[X']; and (d) Find the variance of X. [12 points]