6期

最新文章

• Testing the suitability of polynomial models in errors-in-variables problems AI翻译
  作者：Hall, Peter; Ma, Yanyuan
  作者单位：University of Melbourne; Texas A&M University System; Texas A&M University College Station
  摘要：A low-degree polynomial model for a response curve is used commonly in practice. It generally incorporates a linear or quadratic function of the covariate. In this paper we suggest methods for testing the goodness of fit of a general polynomial model when there are errors in the covariates. There, the true covariates are not directly observed, and conventional bootstrap methods for testing are not applicable. We develop a new approach, in which deconvolution methods are used to estimate the di...
• Strong invariance principles for sequential Bahadur-Kiefer and vervaat error processes of long-range dependent sequences (vol 34, pg 1013, 2006) AI翻译
  作者：Csoergo, Miklos; Szyszkowicz, Barbara; Wang, Lihong
  作者单位：Carleton University; Nanjing University
• Rate-optimal estimation for a general class of nonparametric regression models with unknown link functions AI翻译
  作者：Horowitz, Joel L.; Mammen, Enno
  作者单位：Northwestern University; University of Mannheim
  摘要：This paper discusses a nonparametric regression model that naturally generalizes neural network models. The model is based on a finite number of one-dimensional transformations and can be estimated with a one-dimensional rate of convergence. The model contains the generalized additive model with unknown link function as a special case. For this case, it is shown that the additive components and link function can be estimated with the optimal rate by a smoothing spline that is the solution of a...
• Conditional density estimation in a regression setting AI翻译
  作者：Efromovich, Sam
  作者单位：University of Texas System; University of Texas Dallas
  摘要：Regression problems are traditionally analyzed via univariate characteristics like the regression function, scale function and marginal density of regression errors. These characteristics are useful and informative whenever the association between the predictor and the response is relatively simple. More detailed information about the association can be provided by the conditional density of the response given the predictor. For the first time in the literature, this article develops the theor...
• Measuring and testing dependence by correlation of distances AI翻译
  作者：Szekely, Gabor J.; Rizzo, Maria L.; Bakirov, Nail K.
  作者单位：University System of Ohio; Bowling Green State University; HUN-REN; HUN-REN Alfred Renyi Institute of Mathematics; Hungarian Academy of Sciences; Russian Academy of Sciences
  摘要：Distance correlation is a new measure of dependence between random vectors. Distance covariance and distance correlation are analogous to product-moment covariance and correlation, but unlike the classical definition of correlation, distance correlation is zero only if the random vectors are independent. The empirical distance dependence measures are based on certain Euclidean distances between sample elements rather than sample moments, yet have a compact representation analogous to the class...
• Estimation and confidence sets for sparse normal mixtures AI翻译
  作者：Cai, T. Tony; Jin, Jiashun; Low, Mark G.
  作者单位：University of Pennsylvania; Purdue University System; Purdue University
  摘要：For high dimensional statistical models, researchers have begun to focus on situations which can be described as having relatively few moderately large coefficients. Such situations lead to some very subtle statistical problems. In particular, Ingster and Donoho and Jin have considered a sparse normal means testing problem, in which they described the precise demarcation or detection boundary. Meinshausen and Rice have shown that it is even possible to estimate consistently the fraction of non...
• Rejoinder:: The Dantzig selector:: Statistical estimation when p is much larger than n AI翻译
  作者：Candes, Emmanuel; Tao, Terence
  作者单位：California Institute of Technology; University of California System; University of California Los Angeles
• Estimation of a k-monotone density: Limit distribution theory and the spline connection AI翻译
  作者：Balabdaoui, Fadoua; Wellner, Jon A.
  作者单位：University of Gottingen; University of Washington; University of Washington Seattle
  摘要：We study the asymptotic behavior of the Maximum Likelihood and Least Squares Estimators of a k-monotone density go at a fixed point x(0) when k > 2. We find that the jib derivative of the estimators at x(0) converges at the rate n(-(k-j)/(2k+1)) for j = 0.... k - 1. The limiting distribution depends on an almost surely uniquely defined stochastic process H-k that stays above (below) the k-fold integral of Brownian motion plus a deterministic drift when k is even (odd). Both the MLE and LSE are...
• Accelerated convergence for nonparametric regression with coarsened predictors AI翻译
  作者：Delaigle, Aurore; Hall, Peter; Mueller, Hans-Georg
  作者单位：University of Bristol; University of Melbourne; University of California System; University of California Davis
  摘要：We consider nonparametric estimation of a regression function for a situation where precisely measured predictors are used to estimate the regression curve for coarsened, that is, less precise or contaminated predictors. Specifically, while one has available a sample (W(1), Y(1)),..., (W(n) ,Y(n)) of independent and identically distributed data, representing observations with precisely measured predictors, where E(Y(i)/W(i)) = g (W(i)), instead of the smooth regression function g, the target o...
• Discussion:: The Dantzig selector:: Statistical estimation when p is much larger than n AI翻译
  作者：Ritov, Ya'acov
  作者单位：Hebrew University of Jerusalem