The random variable X is distributed as a Pareto distribution with parameters α = 3, θ. E[X] = 1. The random variable Y = 2X. Calculate V ar(Y )
The random variable X is distributed as a Pareto distribution with parameters α = 3, θ....
Two questions exist : ) if it has pdf. A railon variable X has the l'areio distril illi ribution with parameters m, a (m, α > 0 w 0 otherwise Show that if X has this Pareto distribution, then the random variable log(X/m) has the expo- nential distribution with parameter α Let X ~ Gamma(α, β), where α > 1 . Find E[1/X]. ) if it has pdf. A railon variable X has the l'areio distril illi ribution with parameters...
3. X is the random variable for claim sizes. Given A, X follow a single-parameter Pareto distribution with parameters θ 1000 and A. The distribution of A over the entire population is an exponential distribution with mean 3 Calculate Pr(X> 1500)
Problem 5 You are given: i) In 2009, losses follow a Pareto distribution with parameters θ--400 and α i) Inflation of 3.5% impacts all losses uniformly from 2009 to 2010. 2. Calculate the 75th percentile of the portion of the 2010 loss distribution above 500. (A) 639 (B) 641 (C) 1366 (D) 1400 (E) 1414
Q1. Assume that X is Pareto random variables with the density -α-1 , r21, where α > 0 (a) Calculate EX]. What do you need to assume about a for E[X to be finite? (b) Find the density of X + b for b 〉 0. (c) Find the cumulative distribution function of Y log X.
Consider an exponentially distributed random variable X with pdf f(x) = 2e−2x for x ≥ 0. Let Y = √X. a. Find the cdf for Y. b. Find the pdf for Y. c. Find E[Y]. If you want to skip a difficult integration by parts, make a substitution and look for a Gamma pdf. d. This Y is actually a commonly used continuous distribution. Can you name it and identify its parameters? e. Suppose that X is exponentially distributed with...
5. Consider a random sample Y1, . . . , Yn from a distribution with pdf f(y|θ) = 1 θ 2 xe−x/θ , 0 < x < ∞. Calculate the ML estimator of θ. 6. Consider the pdf g(y|α) = c(1 + αy2 ), −1 < y < 1. (a) Show that g(y|α) is a pdf when c = 3 6 + 2α . (b) Calculate E(Y ) and E(Y 2 ). Referencing your calculations, explain why M1 can’t be...
If X follows a two-parameter Pareto distribution with a = 3 and θ = 100, find the density function of Y, where Y- 1.5X
xn be i.id. from the Pareto distribution Pa(θ, c), θ Let Xi 0 (a) Derive a ÚMP test of size α for testing Ho : θ θ when c is known. versus Hi : xn be i.id. from the Pareto distribution Pa(θ, c), θ Let Xi 0 (a) Derive a ÚMP test of size α for testing Ho : θ θ when c is known. versus Hi :
Let Θ be a continuous random variable uniformly distributed on [0,2 Let X = cose and Y sin e. Show that, for this X and Y, X and Y are uncorrelated but not independent. (Hint: As part of the solution, you will need to find E[X], E[Y] and E|XY]. This should be pretty easy; if you find yourself trying to find fx(x) or fy (v), you are doing this the (very) hard way.)
Let Θ be a continuous random variable uniformly distributed on [0,2 Let X = cose and Y sin e. Show that, for this X and Y, X and Y are uncorrelated but not independent. (Hint: As part of the solution, you will need to find E[X], E[Y] and E|XY]. This should be pretty easy; if you find yourself trying to find fx(x) or fy (v), you are doing this the (very) hard way.) Let Θ be a continuous random variable...