Suppose that y1,...,yn|β are iid Exponential with mean 1/β and that β is marginally Exponential with mean 1. Show that β|y1,...,yn follows a Gamma distribution with shape parameter n+1 and rate parameter 1+∑yi.
Suppose that y1,...,yn|β are iid Exponential with mean 1/β and that β is marginally Exponential with...
Suppose that X1, ..., Xm are iid Bernoulli(p), Y1, ...., Yn are iid Bernoulli(q), and that the X's are independent of the Y's where 0 < p < 1 is the unknown parameter with q = 1 - p. By means of the conditional distribution approach, show that sum of Xi - sum of Yi is sufficient for p. {Hint: Instead of looking at the data (X1, ..., Xm, Y1, ...., Yn), can one justify looking at (X1, ..., Xm,...
Let Y1, Y2, . . . , Yn be independent random variables with Exponential distribution with mean β. Let Y(n) = max(Y1,Y2,...,Yn) and Y(1) = min(Y1,Y2,...,Yn). Find the probability P(Y(1) > y1,Y(n) < yn).
Let Y1,…,Yn~iid Gamma(5,β). Recall that Γ(5) = 4! a) Find the MLE for β. b) Is your answer to a) the MVUE? Use two methods to verify that it is unbiased.
5.4.3 Suppose that X,, X" are iid exponential with mean β(> 0), , y, are iid exponential with mean η(> 0), and that the A's are independent of the Ys. Define ½,-. Then. m, n (i) Show that I , is distributed as /m (ii) Determine the asymptotic distribution of T m, n 2m, 2n as n ->o, when is m, n kept fixed; (ii) Determine the asymptotic distribution of T, as m, when n is kept fixed.
Suppose X1,X2, ,Xm are iid exponential with mean A. Suppose Yı,Yo, exponential with mean β2-Suppose the samples are independent. , Yn are iid (a) Derive the likelihood ratio test (LRT) statistic λ(x,y) for testing versus and show that it is a function of ti-ti (x)-Σ-iz; and t2-t2(y)-Σ1Uj. (b) Show how you could perform a size a test in part (a) using the F distribution
Suppose X1,X2, ,Xm are iid exponential with mean A. Suppose Yı,Yo, exponential with mean β2-Suppose the...
Y1, Y2, ... Yn are a random sample from the Gamma distribution with parameters α and β (a) Suppose that α-4 is known and β is unknown. Find a complete sufficient statistic for β. Find the MVUE of β. (Hint: What is E(Y)?) (b) Suppose that β = 4 is known and a is unknown. Find a complete sufficient statistic for α.
Let Yı,Y2, ..., Yn be iid from a population following the shifted exponential distribution with scale parameter B = 1. The pdf of the population distribution is given by fy(y\0) = y-0) = e x I(y > 0). The "shift" @ > 0 is the only unknown parameter. (a) Find L(@ly), the likelihood function of 0. (b) Find a sufficient statistic for 0 using the Factorization Theorem. (Hint: O is bounded above by y(1) min{Y1, 42, ..., .., Yn}.) (c)...
Suppose Y1, Y2, ..., Yn is an iid sample from a Pareto population distribution described by the pdf fy(y|0) = 4ao y -0-1 y > 20, 2 where the parameter do is known. The unknown parameter is 0 > 0. (a) Find the MOM estimator of 0. (b) Find the MLE of 0.
Let Y1, Y2,. . , Yn be a random sample from the population with pdf f(u:)elsewhere (a) If WIn Yi, show that W, follows an exponential distribution with mean 1/0. (b) Show that 2θΣηι W, follows a χ2 distribution with 2n degrees of freedom. (c) It turns out that if X2 distribution with v degrees of freedom, then E( Use this to show
7.20 Consider Y1,...,Yn as defined in Exercise 7.19. (a) Show that Yilti is an unbiased estimator of B. (b) Calculate the exact variance of Yi/ xi and compare it to the variance of the MLE. 7.19 Suppose that the random variables Yı, ..., Yn satisfy Yi = Bli +ti, i = 1,...,n, where x1, ..., In are fixed constants, and €1,..., En are iid n(0,02), o2 unknown. (a) Find a two-dimensional sufficient statistic for (0,0%). (b) Find the MLE of...