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課程名稱︰高等統計推論二 課程性質︰數學系選修 課程教師︰江金倉 開課學院:理學院 開課系所︰數學系、數學研究所、應用數學科學研究所 考試日期︰2015年 考試時限:未知 試題 : Statistical Inference (Test 1)                                   ~ 1 (10%) Let X1,...,Xn be a random sample from a p.d.f f(x|θ0) and θn be an  unbiased estimator for θ0 whcih attains the Cramer-Rao lower bound, where                         ︿  θ0∈Θ and dim(Θ) = 1. Suppose that the MLE θ of θ0 is a solution of                2                ︿  ~  ∂l(θ|X1,...,Xn) = 0 and -∂l(θ|X1,...,Xn) > 0. Show that θn = θn  θ             θ 2.(15%) Let X1,...,Xn be a random sample from a population with probability  density function fX (x|θ) = (θ0)x^(θ0 -1), 0 < x <1, 0 < θ0 < ∞.  Derive the asymptotic distribution of the maximum likliehood estimator of θ0. 3. (15%) (5%) Derive the asymptotic normality of the maximum likelihood  estimator under some suitable conditions.              i.i.d 4. (8%) (7%) Let Y1,...,Yn ~ (p0)f(y) + (1-p0)g(y) with p0 being unknwon,  and f(.) and g(.) being knwon p.d.f's. Implement the EM-algorithm to obtain          ^(r)        ^(r)  an EM-sequecne {p } and show that p will converge to the MLE as r→∞.             n 5. (15%) Let {Xi,δi,Zi}i=1 be a random sample with Xi = min{Ti,Ci},  δi=I(Xi=Ti), and Zi being a p ×1 covariate vector. Suppose that λ(t|z) =          T  (λ0)(t)exp(β0 z) is the hazard function of T conditioning on Z=z. where  (λ0)(t) is a baseline hazard function and β0 is a p ×1 parameter vector.  Conditioning on Z,T and C are further assumed to be independent. Write the  partial likelihood estimation criterion for β. 6. (15%) Let (Y1,x11,...,x1p),...,(Yn,xn1,...,xnp) be independent with  E [Yi|xi1,...,xip] = (mi)π0(xi1,...,xip) and Var(Yi|xi1,...,xip) =   π0                       π0  ψ*mi*π0(xi1,...,xip)*(1-π0(xi1,...,xip)), i=1,...,n, where xi1,...,xip are  cobariates, π0(xi1,...xip) = exp(A)/(1+exp(A)), where           A = β00 + β01*xi1 + ... + β0p*xip,  and ψ is a scale parameter. Show that the quasi-score estimator is different  from the least squares estimator for (β00,β01,...,β0p). 7. (10%) Suppose that Yi~Xυi, i=1,...,k, are mutually independent. Try to                       k  find the Satterthwaite approximation for Σ ai*Yi, where ai's are known                       i=1  constant. -- ※ 發信站: 批踢踢實業坊(ptt.cc), 來自: 1.162.68.176 ※ 文章網址: https://www.ptt.cc/bbs/NTU-Exam/M.1428997460.A.0E0.html
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