Let X1, . . . , Xn ∼ independent N(µ, τ ) for µ known. Find the Likelihood Ratio Test for H0 : τ ≥ τ_0 vs H1 : τ < τ_0. Use the fact that MLE of τ is (1/n)S^2.
Let X1, . . . , Xn ∼ independent N(µ, τ ) for µ known. Find the Likelihood Ratio Test for H0 : τ ...
Let X1, · · ·, Xn∼ N(µ, τ ) with known µ and unknown variance τ > 0. 1. Find the MLE of τ. 2. Find the MLE of √τ .
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.
Let X1,.....,Xn be a random sample from N(μ,σ2). If μ is unknown but σ2 is known, develop a likelihood ratio test for H0: μ >= μ0 vs. H1: μ < μ0
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,.....,Xn be a random sample from N(μ,σ2), and both μ and σ2 are unknown, with -∞<μ<∞ and σ2 > 0. a. Develop a likelihood ratio test for H0: μ <= μ0 vs. H1: μ > μ0 b. Develop a likelihood ratio test for H0: μ >= μ0 vs. H1: μ < μ0
Let X1,.....,Xn be a random sample from N(μ,σ2), and both μ and σ2 are unknown, with -∞<μ<∞ and σ2 > 0. a. Develop a likelihood ratio test for H0: μ <= μ0 vs. H1: μ > μ0 b. Develop a likelihood ratio test for H0: μ >= μ0 vs. H1: μ < μ0
Let X1, . . . , Xn ∼ Exp(θ) and we wish to test H0 : θ = θ_0 vs H1 : θ not= θ_0. Find the asymptotic LRT for this scenario.
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,-
i.i.d 5. Let X1,., Xn N(, 2 R and o2>0 are both unknown. Find an asymp- totically likelihood ratio test (LRT) of approximate size a for testing Но : д? - 2 Н versus :
i.i.d 5. Let X1,., Xn N(, 2 R and o2>0 are both unknown. Find an asymp- totically likelihood ratio test (LRT) of approximate size a for testing Но : д? - 2 Н versus :
Let X1, X2, · · · , Xn ∼ N(µ, σ2 ). Show that the MLE of µ is efficient.