c and d only, for c use formula:
3. [20 marks Consider the multinomial distribution with 3 categories, where the random variables Xi, X2 and Xs have the joint probability function (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) 4 marks Find the approximate distribution of Y 2X-X2, when the sample size n is large (e) [4 marks] Assume that X-(253, 234, 513). Find the...
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)...
2. 20 marks] Let z1,., xn be a random sample drawn independently from a one-parameter curved normal distribution which has density -oo < x < 00, θ>0, , riid i.e., X r, and 2,2-1 Γη (e) 3 marks Find the Fisher information Z(0) (f) [3 marks] Is θ2 an MVUE of θ? Justify your answer (g) 3 marks] Assume that T = 1.32 and x-3.76 for a random sample of size n = 100. Find the Wald 95% confidence interval...
[20 marks] Let xi, . . . , Xn be a random sample drawn independently from a one-parameter curved normal distribution which has density -oo 〈 x 〈 oo, θ > 0, 2πθ nx, and r2 - enote T-1 Tn (d) [3 marks] Find the maximum likelihood estimator θ2 of. (You do not need to perform the second derivative test.) (e) 3 marks Find the Fisher information T( (f) [3 marks] Is θ2 an MVUE of θ? Justify your answer....
2. Consider tossing a coin twice. Denote H ="head" and T ="tail" (a) List all outcomes in the sample space S (b) Let X count the number of heads. List all outcomes in the events Ao = {X = 0}, Ai = {X=1 and A2 {X = 2}. Are all the events Ao,A1,A2 mutually exclusive? Explain. (c) Suppose P(H) = 0.6. Find the probability mass function of X: f(x) = P{X =x} (d) Find the cumulative distribution function of X:...
Use R language. question 7 Q6. Hasting's approximation: For 2 > 0, "(z), the cdf of standard normal r.v., can be approximated by the function h(x) = 1 -0.5(1 +212 +2222 +2323 +2424) - 4 with a1 = 0.196854, a2 = 0.115194, az = 0.000344, and a4 = 0.019527. The approxima- tion error may be upper bounded by 2.5 x 10-4. Use a for loop to evaluate h(1.645) and compare the result of pnorm(1.645). Round all your answers to 5...
Likelihood Ratio Tests - I only require (a) and (b) here. I'll post (c) and (d) for another question Let X1,..., Xn be a random sample from the distribution with pdf { 0-1e--)e f(r μ, θ ) - 0. where E Rand 0 > 0 (a) If 0 is known but a is unknown, find a likelihood ratio test (LRT) of size a for testing Η : μ> Ho Ho Ho versus where oi a known constant (b) If 0...
Likelihood Ratio Tests - I only require (a) and (b) here. I'll post (c) and (d) for another question Let X1,..., Xn be a random sample from the distribution with pdf { 0-1e--)e f(r μ, θ ) - 0. where E Rand 0 > 0 (a) If 0 is known but a is unknown, find a likelihood ratio test (LRT) of size a for testing Η : μ> Ho Ho Ho versus where oi a known constant (b) If 0...
Likelihood Ratio Tests - I only require (c) and (d) here. I have posted (a) and (b) in another question Let X1,..., Xn be a random sample from the distribution with pdf { 0-1e--)e f(r μ, θ ) - 0. where E Rand 0 > 0 (a) If 0 is known but a is unknown, find a likelihood ratio test (LRT) of size a for testing Η : μ> Ho Ho Ho versus where oi a known constant (b) If...