Let X1, X2 be iid, normal(µ, σ2 = 1).
Show that the statistic T = X1 + X2 is sufficient for µ
Let X1, X2 be iid, normal(µ, σ2 = 1). Show that the statistic T = X1...
Let X1, X2, · · · , Xn ∼ N(µ, σ2 ). Show that the MLE of µ is efficient.
Let X1, X2, X3 ∼(iid) Exponential(λ). (a) Show that T(X1, X2, X3) = X1 + X2 + X3 is a sufficient statistic for λ. (b) Find the MVUE for λ. (c) Show that is not a sufficient statistic for λ. (d) Let = and find . Give an argument for why is not the best estimator of λ. We were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to transcribe this imageWe were unable to...
t (0, c(X1-X2)2) įs a Let X, and X2 be iid. N(0, (Au)100% confidence interval for σ- 1) σ2) variables) . Find a constant so tha t (0, c(X1-X2)2) įs a Let X, and X2 be iid. N(0, (Au)100% confidence interval for σ- 1) σ2) variables) . Find a constant so tha
Let X1, X2, . . . , Xn be IID N(0, σ2 ) variables. Find the rejection region for the likelihood ratio test at level α = 0.1 for testing H0 : σ2 = 1 vs H1 : σ2 = 2.
X1, X2, . . . , Xn i.i.d. ∼ N (µ, σ2 ). Assume µ is known; show that ˆθ = 1 n Pn i=1(Xi− µ) 2 is the MLE for σ 2 and show that it is unbiased. Exactly 6.4-2. Xi, X2, . . . , xn i d. N(μ, μ)2 is the MLE for σ2 and show that it is unbiased. r'). Assume μ is known; show that θ- n Ση! (X,-
Let X1, . . . , Xn ∼ iid log Normal (µ, σ^2 ) for σ^ 2 known. Find the LRT for H0 : µ = µ_0 vs H1 : µ not= µ_0. f(x)=(2π)^(-1/2)(xσ)^(-1)*exp(-(ln x-µ)^2 /(2σ^2))
Let X1, ...., Xm be iid N(μ1,σ2) and Y1, ..., Yn be iid N(μ2,σ2), and X's and Y's are independent. Here -∞<μ1,μ2<∞ and 0<σ<∞ are unknown. Derive the MLE for (μ1,μ2,σ2). Is the MLE sufficient for (μ1,μ2,σ2)? Also derive the MLE for (μ1-μ2)/σ.
5.13. Suppose X1, X2, , xn are iid N(μ, σ2), where-oo < μ < 00 and σ2 > 0. (a) Consider the statistic cS2, where c is a constant and S2 is the usual sample variance (denominator -n-1). Find the value of c that minimizes 2112 var(cS2 (b) Consider the normal subfamily where σ2-112, where μ > 0. Let S denote the sample standard deviation. Find a linear combination cl O2 , whose expectation is equal to μ. Find the...
1.(c) 2.(a),(b) 5. Let Xi,..., X, be iid N(e, 1). (a) Show that X is a complete sufficient statistic. (b) Show that the UMVUE of θ 2 is X2-1/n x"-'e-x/θ , x > 0.0 > 0 6. Let Xi, ,Xn be i.i.d. gamma(α,6) where α > l is known. ( f(x) Γ(α)θα (a) Show that Σ X, is complete and sufficient for θ (b) Find ElI/X] (c) Find the UMVUE of 1/0 -e λ , X > 0 2) (x...
8. Let X, X2, , xn all be be distributed Normal(μ, σ2). Let X1, X2, , xn be mu- tually independent. a) Find the distribution of U-Σǐ! Xi for positive integer m < n b) Find the distribution of Z2 where Z = M Hint: Can the solution from problem #2 be applied here for specific values of a and b?