3期

最新文章

• A consistent test for the functional form of a regression based on a difference of variance estimators AI翻译
  作者：Dette, H
  作者单位：Ruhr University Bochum
  摘要：In this paper we study the problem of testing the functional farm of a given regression model. A consistent test is proposed which is based on the difference of the least squares variance estimator in the assumed regression model and a nonparametric variance estimator. The corresponding test statistic can be shown to be asymptotically normal under the null hypothesis and under fixed alternatives with different rates of convergence corresponding to both cases. This provides a simple asymptotic ...
• Bartlett identities and large deviations in likelihood theory AI翻译
  作者：Mykland, PA
  作者单位：University of Chicago
  摘要：The connection between large and small deviation results for the signed square root statistic R is studied, both for likelihoods and for likelihood-like criterion functions. We show that if p - 1 Barlett identities are satisfied to first order, but the pth identity is violated to this order, then cum,(R) = O(n(-q/2)) for 3 less than or equal to q < p, whereas cum(p)(R) = kappa(P)n(-(p-2)/2) + O(n(-p/2)). We also show that the large deviation behavior of R is determined by the values of p and k...
• A score test for linkage using identity by descent data from sibships AI翻译
  作者：Dudoit, S; Speed, TP
  作者单位：University of California System; University of California Berkeley
  摘要：We consider score tests of the null hypothesis H-0: theta = 1/2 against the alternative hypothesis H-1: 0 less than or equal to theta < 1/2, based upon counts multinomially distributed with parameters n and rho(theta, pi)(1xm) = pi(1xm)T(theta)(mxm), where T(theta) is a transition matrix with T(0) = I, the identity matrix, and T(1/2) = (1,..., 1)(T)(alpha(1),...,alpha(m)). This type of testing problem arises in human genetics when testing the null hypothesis of no linkage between a marker and ...
• Multivariate analysis by data depth - Discussion AI翻译
  作者：Hettmansperger, TP; Oja, H; Visuri, S
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park; University of Jyvaskyla; Tampere University
• Wedgelets: Nearly minimax estimation of edges AI翻译
  作者：Donoho, DL
  作者单位：Stanford University
  摘要：We study a simple horizon model for the problem of recovering an image from noisy data; in this model the image has an edge with alpha-Holder regularity. Adopting the viewpoint of computational harmonic analysis, we develop an overcomplete collection of atoms called wedgelets, dyadically organized indicator functions with a variety of locations, scales and orientations. The wedgelet representation provides nearly optimal representations of objects in the horizon model, as measured by minimax d...
• Hierarchical mixtures-of-experts for exponential family regression models: Approximation and maximum likelihood estimation AI翻译
  作者：Jiang, WX; Tanner, MA
  作者单位：Northwestern University
  摘要：We consider hierarchical mixtures-of-experts (HME) models where exponential family regression models with generalized linear mean functions of the form psi(alpha + x(T)beta) are mixed. Here psi(.) is the inverse link function. Suppose the true response y follows an exponential family regression model with mean function belonging to a class of smooth functions of the form psi(h(x)) where h(.) is an element of W-2; K0(infinity) (a Sobolev class over [0, 1](s)). It is shown that the HME probabili...
• Asymptotics when the number of parameters tends to infinity in the Bradley-Terry model for paired comparisons AI翻译
  作者：Simons, G; Yao, YC
  作者单位：University of North Carolina; University of North Carolina Chapel Hill; Academia Sinica - Taiwan
  摘要：We are concerned here with establishing the consistency and asymptotic normality for the maximum likelihood estimator of a merit vector (u(0),..., u(t)), representing the merits of t+1 teams (players, treatments, objects), under the Bradley-Terry model, as t --> infinity. This situation contrasts with the well-known Neyman-Scott problem under which the number of parameters grows with t (the amount of sampling), and for which the maximum likelihood estimator fails even to attain consistency. A ...
• Multivariate analysis by data depth - Rejoinder AI翻译
  作者：Liu, RY; Singh, K
  作者单位：Rutgers University System; Rutgers University New Brunswick
• Multivariate analysis by data depth - Discussion AI翻译
  作者：Baggerly, KA; Scott, DW
  作者单位：Rice University
• Multivariate analysis by data depth: Descriptive statistics, graphics and inference AI翻译
  作者：Liu, RY; Parelius, JM; Singh, K
  作者单位：Rutgers University System; Rutgers University New Brunswick
  摘要：A data depth can be used to measure the depth or outlyingness of a given multivariate sample with respect to its underlying distribution. This leads to a natural center-outward ordering of the sample points. Based on this ordering, quantitative and graphical methods are introduced for analyzing multivariate distributional characteristics such as location, scale, bias, skewness and kurtosis, as well as for comparing inference methods. All graphs are one-dimensional curves in the plane and can b...