3.4.12 Let X ∼ Geometric(θ ).
(a) Compute mx (s). (b) Use mx to compute the mean of X. (c) Use mx to compute the variance of X.
3.4.12 Let X ∼ Geometric(θ ). (a) Compute mx (s). (b) Use mx to compute the...
Let X,X,, X, be a random sample of size 3 from a uniform distribution having pdf /(x:0) = θ,0 < x < 0,0 < θ, and let):く,), be the corresponding order statistics. a. Show that 2Y, is an unbiased estimator of 0 and find its variance. b. Y is a sufficient statistic for 8. Determine the mean and variance of Y c. Determine the joint pdf of Y, and Y,, and use it to find the conditional expectation Find the...
Let X1, ..., X50 denote a random sample of size 50 from the geometric distribution f(x; θ) = θ(1 − θ) x−1 for x = 1, 2, ... and 0 < θ < 1. Suppose that after taking the observations we find that ¯x = 5. 8. a) Find the maximum likelihood estimator ˆθ of θ. b) Find E[X¯] and var(X¯). c) Use part (b) above together with the CLT and delta method to find the limiting distribution of √...
(a) Let θ : R-+ R be a smooth function. Find the (signed) curvature of the curve a:R- R2 given by cos(θ(t)) dt,I α(s) sin(θ(t)) dt Use your result to give another geometric interpretation to the (signed) curva- ture and its sign? to) rindy,R-- parmetrised with unit speed suchhat y -0and kt) - s for all seR. (a) Let θ : R-+ R be a smooth function. Find the (signed) curvature of the curve a:R- R2 given by cos(θ(t)) dt,I...
7. Section 6.4, Exercise 1 Let X. X be a random sample from the U(0,0) distribution, and let , 2X and mx X, be estimators for 0. It is given that the mean and variance of oz are (a) Give an expression for the bias of cach of the two estimators. Are they unbiased? (b) Give an expression for the MSE of cach of the two estimators. (c) Com pute the MSE of each of the two ctrnators for n...
5.7 Let X, X, be independent r.v.'s from the u(e -a, o+ b) distribution, where a and b are (known) positive constants and θ Ω M. Determine the moment estimate θ of θ, and compute its expectation and variance.
this is a challenging question Let X ~ POI(μ), and let θ-P(X = 0-e-". (a) Is -e-r an unbiased estimator of θ? (b) Show that θ = u(X) is an unbiased estimator of θ, where u(0) 1 and u(x)-0 if (c) Compare the MSEs of, and è for estimating θ-e-, when μ 1 and 2. Let X ~ POI(μ), and let θ-P(X = 0-e-". (a) Is -e-r an unbiased estimator of θ? (b) Show that θ = u(X) is an...
I. Let X be a random sample from an exponential distribution with unknown rate parameter θ and p.d.f (a) Find the probability of X> 2. (b) Find the moment generating function of X, its mean and variance. (c) Show that if X1 and X2 are two independent random variables with exponential distribution with rate parameter θ, then Y = X1 + 2 is a random variable with a gamma distribution and determine its parameters (you can use the moment generating...
Let x be a discrete random variable with PR mass function f(x)=2(1/3)^x, x=1,2,3.. A) Compute Mx(t) B) Compute M'1=EX, M'2=EX^2
Let X be a random variable with cumulative distribution function(a) Find the probability density function fX(x), (b) Find the moment generating function MX(s) for s < 3, (c) Find the mean and variance of X.
Let X1 , . . . , xn be n iid. random variables with distribution N (θ, θ) for some unknown θ > 0. In the last homework, you have computed the maximum likelihood estimator θ for θ in terms of the sample averages of the linear and quadratic means, i.e. Xn and X,and applied the CLT and delta method to find its asymptotic variance. In this problem, you will compute the asymptotic variance of θ via the Fisher Information....