搜索结果: 1-15 共查到“统计学其他学科 regression”相关记录27条 . 查询时间(0.062 秒)
Consistency of M estimates for separable nonlinear regression models
Nonlinear regression separable models con-sistency robust estimation.
2012/9/18
Consider a nonlinear regression model :yi =g(xi, 兤) +ei, i = 1, ..., n,where thexi are random predictorsxi and兤is the unknown parameter vector ranging in a set set 儲伡Rp. All known results on the consi...
Efficient Algorithm for Extremely Large Multi-task Regression with Massive Structured Sparsity
Algorithm Large Multi-task Regression Massive Structured Sparsity
2012/9/17
We develop a highly scalable optimization method called “hierarchical group-thresholding”for solving a multi-task regression model with complex structured sparsity constraints on both input and output...
Local Quantile Regression
local MLE excess bound propagation condition adaptive bandwidth selection.
2012/9/18
Quantile regression is a technique to estimate conditional quantile curves. It pro-vides a comprehensive picture of a response contingent on explanatory variables. In a exible modeling framework, a sp...
Censored quantile regression processes under dependence and penalization
quantile regression Bahadur representation variable selection weak convergence censored data dependent data
2012/9/18
We consider quantile regression processes from censored data under dependent data structures and derive a uniform Bahadur representation for those processes. We also consider cases where the dimension...
Inference of time-varying regression models
Information criterion locally stationary processes nonpara-metric hypothesis testings time-varying coefficient models variable selection.
2012/9/17
We consider parameter estimation, hypothesis testing and vari-able selection for partially time-varying coefficient models. Our asymp-totic theory has the useful feature that it can allow dependent, n...
Adaptive estimation in regression and complexity of approximation of random fields
regression and complexity approximation random fields
2012/9/17
In this thesis we study adaptive nonparametric regression with noise misspecifi-cation and the complexity of approximation of random fields in dependence of the dimension.
First, we consider the prob...
Minimax testing of a composite null hypothesis defined via a quadratic functional in the model of regression
Nonparametric hypotheses testing sharp asymptotics separation rates minimax approach high-dimensional regression.
2012/9/17
We consider the problem of testing a particular type of composite null hypothesis under a nonparametric multivariate regression model. For a given quadraticfunctional Q, the null hypothesis states tha...
Bayesian Mode Regression
Bayesian inference empirical likelihood Markov Chain Monte Carlo methods mode
2012/9/17
Like mean, quantile and variance, mode is also an important measure of central tendency and data summary. Many practical questions often focus on “Which element (gene or file or signal) occurs most of...
Agnostic Notes on Regression Adjustments to Experimental Data: Reexamining Freedman's Critique
Analysis of covariance covariate adjustment randomization in-ference sandwich estimator robust standard errors social experiments program evalua-tion
2012/9/17
Freedman [Adv. in Appl. Math.40(2008) 180–193; Ann. Appl.Stat.2(2008) 176–196] critiqued ordinary least squares regression ad-justment of estimated treatment effects in randomized experiments,using Ne...
Finite sample posterior concentration in high-dimensional regression
asymptotics Bayesian compressible prior high-dimensional posterior contraction regression shrinkage prior.
2012/9/19
We study the behavior of the posterior distribution in ultra high-dimensional Bayesian Gaussian linear regression models havingp佲n,withpthe number of predictors and nthe sample size. In particular, ou...
Adaptive confidence bands in the nonparametric fixed design regression model
Adaptive confidence bands nonparametric fixed design regression model
2012/9/19
In this note, we consider the problem of existence of adaptive confidence bands in the fixed design regression model, adapting ideas in Hoffmann and Nickl [10] to the present case. In the course of th...
A Robust, Fully Adaptive M-estimator for Pointwise Estimation in Heteroscedastic Regression
Adaptation Huber contrast Lepski’s method M-estimation minimax estimation nonparamet-ric regression pointwise estimation robust estimation.
2012/9/19
We introduce a robust and fully adaptive method for pointwise estimation in heteroscedastic regression. We allow for noise and design distributions that are unknown and fulfill very weak assumptions o...
Maximum Likelihood Estimation of Gaussian Cluster Weighted Models and Relationships with Mixtures of Regression
Cluster-weighted modeling finite mixtures of regression EM-algorithm
2012/9/19
Cluster-weighted modeling (CWM) is a mixture approach for modeling the joint probability of a response variable and a set of explanatory variables. The parame-ters are estimated by means of the expect...
Spatially-adaptive sensing in nonparametric regression
Nonparametric regression, adaptive sensing sequential design active learning spatial adaptation spatially-inhomogeneous functions.
2012/9/18
While adaptive sensing has provided improved rates of convergence in sparse regression and classi cation, results in nonparametric regres-sion have so far been restricted to quite speci c classes of f...
Extended BIC for linear regression models with diverging number of relevant features and high or ultra-high feature spaces
Diverging number of parameters Feature selection
2011/7/19
In many conventional scientific investigations with high or ultra-high dimensional feature spaces, the relevant features, though sparse, are large in number compared with classical statistical problem...