2期

最新文章

• D-OPTIMAL DESIGNS FOR MULTINOMIAL LOGISTIC MODELS AI翻译
  作者：Bu, Xianwei; Majumdar, Dibyen; Yang, Jie
  作者单位：AbbVie; University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital
  摘要：We consider optimal designs for general multinomial logistic models, which cover baseline-category, cumulative, adjacent-categories and continuation-ratio logit models, with proportional odds, nonproportional odds or partial proportional odds assumption. We derive the corresponding Fisher information matrices in three different forms to facilitate their calculations, determine the conditions for their positive definiteness, and search for optimal designs. We conclude that, unlike the designs f...
• MODEL-ASSISTED INFERENCE FOR TREATMENT EFFECTS USING REGULARIZED CALIBRATED ESTIMATION WITH HIGH-DIMENSIONAL DATA AI翻译
  作者：Tan, Zhiqiang
  作者单位：Rutgers University System; Rutgers University New Brunswick
  摘要：Consider the problem of estimating average treatment effects when a large number of covariates are used to adjust for possible confounding through outcome regression and propensity score models. We develop new methods and theory to obtain not only doubly robust point estimators for average treatment effects, which remain consistent if either the propensity score model or the outcome regression model is correctly specified, but also model-assisted confidence intervals, which are valid when the ...
• WORST-CASE VERSUS AVERAGE-CASE DESIGN FOR ESTIMATION FROM PARTIAL PAIRWISE COMPARISONS AI翻译
  作者：Pananjady, Ashwin; Mao, Cheng; Muthukumar, Vidya; Wainwright, Martin J.; Courtade, Thomas A.
  作者单位：University of California System; University of California Berkeley; University of California System; University of California Berkeley; Yale University
  摘要：Pairwise comparison data arises in many domains, including tournament rankings, web search and preference elicitation. Given noisy comparisons of a fixed subset of pairs of items, we study the problem of estimating the underlying comparison probabilities under the assumption of strong stochastic transitivity (SST). We also consider the noisy sorting subclass of the SST model. We show that when the assignment of items to the topology is arbitrary, these permutation-based models, unlike their pa...
• PREDICTION ERROR AFTER MODEL SEARCH AI翻译
  作者：Tian, Xiaoying
  作者单位：Stanford University
  摘要：Estimation of the prediction error of a linear estimation rule is difficult if the data analyst also uses data to select a set of variables and constructs the estimation rule using only the selected variables. In this work, we propose an asymptotically unbiased estimator for the prediction error after model search. Under some additional mild assumptions, we show that our estimator converges to the true prediction error in L-2 at the rate of O(n(-1/2)), with n being the number of data points. O...
• INFERENCE FOR ARCHIMAX COPULAS AI翻译
  作者：Chatelain, Simon; Fougeres, Anne-Laure; Neslehova, Johanna G.
  作者单位：Centre National de la Recherche Scientifique (CNRS); Ecole Centrale de Lyon; Institut National des Sciences Appliquees de Lyon - INSA Lyon; Universite Claude Bernard Lyon 1; Universite Jean Monnet; CNRS - National Institute for Mathematical Sciences (INSMI); McGill University
  摘要：Archimax copula models can account for any type of asymptotic dependence between extremes and at the same time capture joint risks at medium levels. An Archimax copula is characterized by two functional parameters: the stable tail dependence function l, and the Archimedean generator psi which distorts the extreme-value dependence structure. This article develops semiparametric inference for Archimax copulas: a nonparametric estimator of l and a moment-based estimator of psi assuming the latter...
• ON ESTIMATION OF ISOTONIC PIECEWISE CONSTANT SIGNALS AI翻译
  作者：Gao, Chao; Han, Fang; Zhang, Cun-Hui
  作者单位：University of Chicago; University of Washington; University of Washington Seattle; Rutgers University System; Rutgers University New Brunswick
  摘要：Consider a sequence of real data points X-1, ..., X-n with underlying means theta(1)*, ..., theta(n)*. This paper starts from studying the setting that theta(i)* is both piecewise constant and monotone as a function of the index i. For this, we establish the exact minimax rate of estimating such monotone functions, and thus give a nontrivial answer to an open problem in the shape-constrained analysis literature. The minimax rate under the loss of the sum of squared errors involves an interesti...
• NONASYMPTOTIC UPPER BOUNDS FOR THE RECONSTRUCTION ERROR OF PCA AI翻译
  作者：Reiss, Markus; Wahl, Martin
  作者单位：Humboldt University of Berlin
  摘要：We analyse the reconstruction error of principal component analysis (PCA) and prove nonasymptotic upper bounds for the corresponding excess risk. These bounds unify and improve existing upper bounds from the literature. In particular, they give oracle inequalities under mild eigenvalue conditions. The bounds reveal that the excess risk differs significantly from usually considered subspace distances based on canonical angles. Our approach relies on the analysis of empirical spectral projectors...
• LEARNING A TREE-STRUCTURED ISING MODEL IN ORDER TO MAKE PREDICTIONS AI翻译
  作者：Bresler, Guy; Karzand, Mina
  作者单位：Massachusetts Institute of Technology (MIT); University of Wisconsin System; University of Wisconsin Madison
  摘要：We study the problem of learning a tree Ising model from samples such that subsequent predictions made using the model are accurate. The prediction task considered in this paper is that of predicting the values of a subset of variables given values of some other subset of variables. Virtually all previous work on graphical model learning has focused on recovering the true underlying graph. We define a distance (small set TV or ssTV) between distributions P and Q by taking the maximum, over all...
• FUNDAMENTAL LIMITS OF DETECTION IN THE SPIKED WIGNER MODEL AI翻译
  作者：El Alaoui, Ahmed; Krzakala, Florent; Jordan, Michael
  作者单位：Stanford University; Sorbonne Universite; Universite PSL; Ecole Normale Superieure (ENS); Universite Paris Cite; Centre National de la Recherche Scientifique (CNRS); Sorbonne Universite; University of California System; University of California Berkeley
  摘要：We study the fundamental limits of detecting the presence of an additive rank-one perturbation, or spike, to a Wigner matrix. When the spike comes from a prior that is i.i.d. across coordinates, we prove that the log-likelihood ratio of the spiked model against the nonspiked one is asymptotically normal below a certain reconstruction threshold which is not necessarily of a spectral nature, and that it is degenerate above. This establishes the maximal region of contiguity between the planted an...
• LASSO GUARANTEES FOR β-MIXING HEAVY-TAILED TIME SERIES AI翻译
  作者：Wong, Kam Chung; Li, Zifan; Tewari, Ambuj
  作者单位：University of Michigan System; University of Michigan; Yale University
  摘要：Many theoretical results for lasso require the samples to be i.i.d. Recent work has provided guarantees for lasso assuming that the time series is generated by a sparse Vector Autoregressive (VAR) model with Gaussian innovations. Proofs of these results rely critically on the fact that the true data generating mechanism (DGM) is a finite-order Gaussian VAR. This assumption is quite brittle: linear transformations, including selecting a subset of variables, can lead to the violation of this ass...