Let X1....Xn be i.i.d sample with a continous distribution function F(.) and X(1)<......<X(n) are the orser-statistics of the sample. Let the constant Mp be defined by F(Mp)=p.
Show that for 1≤k1≤k2≤ n, P{X(k1) ≤Mp ≤X(k2)}=P{k1 ≤Bionmial(n,p) k2}
Let X1....Xn be i.i.d sample with a continous distribution function F(.) and X(1)<......<X(n) are the orser-statistics...
(7) Let X1,Xn are i.i.d. random variables, each with probability distribution F and prob- ability density function f. Define U=max{Xi , . . . , X,.), V=min(X1, ,X,). (a) Find the distribution function and the density function of U and of V (b) Show that the joint density function of U and V is fe,y(u, u)= n(n-1)/(u)/(v)[F(v)-F(u)]n-1, ifu < u.
(7) Let X1,Xn are i.i.d. random variables, each with probability distribution F and prob- ability density function f. Define U=max{Xi...
Let X1, X2, · · · Xn be a i.i.d. sample from Bernoulli(p) and let . Show that Yn converges to a degenerate distribution at 0 as n → ∞.
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.
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.
7. Let X1 , Xn be i.i.d. with the density p(r,0) = a*(1 - 0)1-k1{x = 0,1} (a) Find the ML estimator of 0 (b) Is it unbiased? (c) Compute its MSE
7. Let X1 , Xn be i.i.d. with the density p(r,0) = a*(1 - 0)1-k1{x = 0,1} (a) Find the ML estimator of 0 (b) Is it unbiased? (c) Compute its MSE
Let X1, X2, ...,Xn denote a random sample of size n from a Pareto distribution. X(1) = min(X1, X2, ..., Xn) has the cumulative distribution function given by: αη 1 - ( r> B X F(x) = . x <B 0 Show that X(1) is a consistent estimator of ß.
2. Let X1,..., Xn be i.i.d. according to a normal distribution N(u,02). (a) Get a sufficient statistic for u. Show your work. (b) Find the maximum likelihood estimator for u. (c) Show that the MLE in part (b) is an unbiased estimator for u. (d) Using Basu's theorem, prove that your MLE from before and sº, the sample variance, are independent. (Hint: use W; = X1-0 and (n-1)32)
Let Ņ, X1. X2, . . . random variables over a probability space It is assumed that N takes nonnegative inteqer values. Let Zmax [X1, -. .XN! and W-min\X1,... ,XN Find the distribution function of Z and W, if it suppose N, X1, X2, are independent random variables and X,, have the same distribution function, F, and a) N-1 is a geometric random variable with parameter p (P(N-k), (k 1,2,.)) b) V - 1 is a Poisson random variable with...
8.60-Modified: Let X1,...,Xn be i.i.d. from an exponential distribution with the density function a. Check the assumptions, and find the Fisher information I(T) b. Find CRLB c. Find sufficient statistic for τ. d. Show that t = X1 is unbiased, and use Rao-Blackwellization to construct MVUE for τ. e. Find the MLE of r. f. What is the exact sampling distribution of the MLE? g. Use the central limit theorem to find a normal approximation to the sampling distribution h....
Let X1, X2, .. , Xn be a random sample of size n from a geometric distribution with pmf =0.75 . 0.25z-1, f(x) X-1.2.3. ) Let Zn 3 n n-2ућ. Find Mz, (t), the mgf of Žn. Then find the limiting mgf limn→oo MZm (t). What is the limiting distribution of Z,'?
Let X1, X2, .. , Xn be a random sample of size n from a geometric distribution with pmf =0.75 . 0.25z-1, f(x) X-1.2.3.
) Let Zn 3...