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3. Let X1, X2,... , Xn be i.i.dExp(0) NOTE: We have previously found that θMLE X (a) Assuming a l...
2-3. Let ?>0 and ?? R. Let X1,X2, distribution with probability density function , Xn be a random sample from the zero otherwise suppose ? is known. ( Homework #8 ): W-X-5 has an Exponential ( 2. Recall --)-Gamma ( -1,0--) distribution. a) Find a sufficient statistic Y-u(X1, X2, , Xn) for ? b) Suggest a confidence interval for ? with (1-?) 100% confidence level. "Flint": Use ?(X,-8) ? w, c) Suppose n-4, ?-2, and X1-215, X2-2.55, X3-210, X4-2.20. i-1...
4. Let Xi,..., Xn be a random sample with density 303 for 0 < θ < x NOTE: We have previously found that θMLE-X(1) and that FX(1) (x)-1-(!)3m (a) Using the probability integral transform method, find a pivot for 0 based on the MLE. (b) Use the pivot found in (a) to get an ezact 100(1-a)% C.1. for θ (c) Find an approximate 100(1-a)% C.1. for θ based on our result for the MLE. (d) Suppose that we get n...
3. [20 marks] Consider the multinomial distribution with 3 categories, where the random variables Xi, X2 and X3 have the joint probability function where x = (zi, 2 2:23), θ = (θί, θ2), n = x1 + 2 2 + x3, θι, θ2 > 0 and 1-0,-26, > 0. (a) [4 marks] Find the maximum likelihood estimator θ of θ. (b) [4 marks] Find that the Fisher information matrix I(0) (c) [4 marks] Show that θ is an MVUE. (d)...
3. [20 marks] Consider the multinomial distribution with 3 categories, where the random variables Xi, X2 and X3 have the joint probability function where x = (zi, 2 2:23), θ = (θί, θ2), n = x1 + 2 2 + x3, θι, θ2 > 0 and 1-0,-26, > 0. (a) [4 marks] Find the maximum likelihood estimator θ of θ. (b) [4 marks] Find that the Fisher information matrix I(0) (c) [4 marks] Show that θ is an MVUE. (d)...
Suppose we assume that X1, X2, . . . , Xn is a random sample from a「(1, θ) distribution a) Show that the random variable (2/0) X has a x2 distribution with 2n degrees of freedom. (b) Using the random variable in part (a) as a pivot random variable, find a (1-a) 100% confidence interval for
Let Xi., Xn be a random sample from the distribution with density f(r, θ)-303/2.4 for x > θ and 0 otherwise. Determine the MLE of θ and derive 90% central CI interval for θ. If possible find an exact CI. Otherwise determine an approximate CI. Explain your choice
Let Xi., Xn be a random sample from the distribution with density f(r, θ)-303/2.4 for x > θ and 0 otherwise. Determine the MLE of θ and derive 90% central CI interval...
Let X1, X2, X3,…Xn is a random sample, where X~Exp(1/θ) and U=2Y/θ. a) Find the cumulative distribution function of U. (8pts) b) Is U a pivot (2pts) c) Find the 95% CI for θ.(10pts)
Let X1, X2,.,X10 be a sample of size 10 from an exponential distribution with the density function Sae -Xx f(x; A) otherwise 10 We reject Ho : ^ = 1 in favor of H : 1 = 2 if the observed value of Y = smaller than 6 (a) Find the probability of type 1 error for this test. (b) Find the probability of type 2 error for this test (c) Let y5 be the observed value of Y. Find...
Independent random samples X1, X2, . . . , Xn are from
exponential distribution with pdfs
, xi > 0, where λ is fixed but unknown. Let
. Here we have a relative large sample size n = 100.
(ii) Notice that the population mean here is µ = E(X1) = 1/λ ,
population variance σ^2 = Var(X1) = 1/λ^2 is unknown. Assume the
sample standard deviation s = 10, sample average
= 5, construct a 95% large-sample approximate confidence...
5. Let X1,X2,. Xn be a random sample from a Beta(0, 1) distribution. Recall that W -Σ-1 logXi has the gamma distribution Γ(n,1/8) a) Show that 2θW has a χ"(2n) distribution b) Using part a), find c1 and c2 so that P (cı < 쯩 < c2)-1-α, for 0 < α obtain a (1-a) 100% CI for 20n 1, and then