Find the variance assuming X1, X2, · · · , Xn be an i.i.d. sample from the density f (x|θ) = 1/2θ e (−|x|/θ) , −∞ < x < ∞
Find the variance assuming X1, X2, · · · , Xn be an i.i.d. sample from...
4. Let X1, X2, ..., Xn be a random sample from a distribution with the probability density function f(x; θ) = (1/2)e-11-01, o < x < oo,-oo < θ < oo. Find the NILE θ.
4. Let X1, X2, ..., Xn be a random sample from a distribution with the probability density function f(x; θ) = (1/2)e-11-01, o < x < oo,-oo < θ < oo. Find the NILE θ.
3. Let X1, X2, . . . , Xn be a random sample from a distribution with the probability density function f(x; θ) (1/02)Te-x/θ. O < _T < OO, 0 < θ < 00 . Find the MLE θ
Let X1, X2, ... , Xn be a random sample of size n from the exponential distribution whose pdf is f(x; θ) = (1/θ)e^(−x/θ) , 0 < x < ∞, 0 <θ< ∞. Find the MVUE for θ. Let X1, X2, ... , Xn be a random sample of size n from the exponential distribution whose pdf is f(x; θ) = θe^(−θx) , 0 < x < ∞, 0 <θ< ∞. Find the MVUE for θ.
3. Let X1 , X2, . . . , Xn be a randon sample from the distribution with pdf f(r;0) = (1/2)e-z-8,-X < < oo,-oc < θ < oo. Find the maximum likelihood estimator of θ.
Problem 2. (The Convergence of Extreme Value) Let X1, X2, ... be i.i.d sample from the distribution with density function as: f(x) = >1 10 otherwise Define Mn = min(X1, X2, ... , Xn), answer the following questions. 1) Show that Mn P 1 as n +0. 2) Show that n(Mn – 1) converges in distribution as n + 00. Find out the limit distri- bution.
Suppose X1, X2, . . . , Xn (n ≥ 5) are i.i.d. Exp(µ) with the density f(x) = 1 µ e −x/µ for x > 0. (a) Let ˆµ1 = X. Show ˆµ1 is a minimum variance unbiased estimator. (b) Let ˆµ2 = (X1 +X2)/2. Show ˆµ2 is unbiased. Calculate V ar(ˆµ2). Confirm V ar(ˆµ1) < V ar(ˆµ2). Calculate the efficiency of ˆµ2 relative to ˆµ1. (c) Show X is consistent and sufficient. (d) Show ˆµ2 is not consistent...
Let X1,X2,...,Xn be an independent and identically distributed (i.i.d.) random sample of Beta distribution with parameters α = 2 and β = 1, i.e., with probability density function fX(x) = 2x for x ∈ (0,1). Find the probability density function of the first and last order statistics Y1 and Yn.
Please answer question (a) X1 - X X2 – Å a. Let X1, ..., Xn i.i.d. random variables with X; ~ N(u, o). Express the vector in the | Xn – form AX and find its mean and variance covariance matrix. Show some typical elements of the vari- ance covariance matrix. b. Refer to question (a). The sample variance is given by S2 = n11 21–1(X; – X)2, which can be ex- pressed as S2 = n1X'(I – 111')X (why?)....
Answer the following questions: a. Let X1, X2, . . . , Xn be i.i.d. random vectors (a random sample) from Np(μ1, Σ). Find the distribution of X ̄ . Note: X ̄ = 1/n Xi . b. Refer to question (a). Consider the following two random variables: Q1 = 1′X ̄/1'1 and Q2 = 1′Σ−1X ̄/1′Σ−11 ̄ . Find the mean and variance of Q1 and Q2 .