搜索结果: 121-135 共查到“统计学 regression”相关记录243条 . 查询时间(0.072 秒)
We consider heteroscedastic nonparametric regression models, when both the mean function and variance function are unknown and to be estimated with nonparametric approaches. We derive convergence rate...
Quasi-estimation as a Basis for Two-stage Solving of Regression Problem
Gauss-Markov’s scheme least squares method quasi-estimator
2010/10/19
An effective two-stage method for an estimation of parameters of the linear regression is considered. For this purpose we introduce a certain quasi-estimator that, in contrast to usual estimator, pro...
Asymptotic Normality of Support Vector Machines for Classification and Regression
Nonparametric regression support vector machines asymptotic normality
2010/10/14
In nonparametric classification and regression problems, support vector machines (SVMs) attract much attention in theoretical and in applied statistics. In an abstract sense, SVMs can be seen as regu...
Quantile calculus and censored regression
Differential equation estimating integral equation quantile equality fraction regression quantile
2010/10/14
Quantile regression has been advocated in survival analysis to assess evolving covariate effects. However, challenges arise when the censoring time is not always observed and may be covariate-depende...
Robust linear regression through PAC-Bayesian truncation
Linear regression Generalization error Shrinkage
2010/10/14
We consider the problem of predicting as well as the best linear combination of d given functions in least squares regression under $L^\infty$ constraints on the linear combination. When the input dis...
Nonparametric kernel estimation of the probability density function of regression errors using estimated residuals
Kernel density estimation Leave-one-out kernel estimator Two-steps estimator
2010/10/14
This paper deals with the nonparametric density estimation of the regression error term assuming its independence with the covariate. The difference between the feasible estimator which uses the estim...
High-dimensional Ising model selection using ${\ell_1}$-regularized logistic regression
High-dimensional model selection
2010/10/14
We consider the problem of estimating the graph associated with a binary Ising Markov random field. We describe a method based on $\ell_1$-regularized logistic regression, in which the neighborhood of...
Regularization in regression: comparing Bayesian and frequentist methods in a poorly informative situation
Regularization regression comparing Bayesian frequentist methods
2010/10/14
We propose a global noninformative approach for Bayesian variable selection that builds on Zellner's g-priors and is similar to Liang et al. (2008). Our proposal does not require any kind of calibrati...
We consider the problem of robustly predicting as well as the best linear combination of d given functions in least squares regression, and variants of this problem including constraints on the param...
Regression with strongly correlated data
regression least squares highly correlated errors Peelle’s pertinentpuzzle
2010/4/27
This paper discusses linear regression of strongly correlated data that
arises, for example, in magnetohydrodynamic equilibrium reconstructions.
We have proved that, generically, the covariance matr...
Kink estimation in stochastic regression with dependent errors and predictors
Change point Kink High-order kernel Zero-crossing technique Long-range dependence Random Design Separationrate lemma
2010/3/11
In this article we study the estimation of the location of jump
points in the first derivative (referred to as kinks) of a regression function
μ in two random design models with different long-range...
Beta-binomial/gamma-Poisson regression models for repeated counts with random parameters
bivariate counts longitudinal data overdispersion random effects regressionmodels
2010/3/11
Beta-binomial/Poisson models have been used by many authors to model multivariate
count data. Lora and Singer (Statistics in Medicine, 2008) extended such models
to accommodate repeated multivariate...
Approximation by Log-Concave Distributions with Applications to Regression
Convex support isotonic regression linear regression Mallows’ distance projection
2010/3/10
We study the approximation of arbitrary distributions P on d-dimensional space by distributions
with log-concave density. Approximation means minimizing a Kullback–Leibler type functional.
We show t...
Multivariate quantiles and multiple-output regression quantiles：From L1 optimization to halfspace depth
Multivariate quantile quantile regression halfspace depth
2010/3/10
A new multivariate concept of quantile, based on a directional
version of Koenker and Bassett’s traditional regression quantiles, is
introduced for multivariate location and multiple-output regressi...
Discussion of “Multivariate quantiles and multiple-output regression quantiles：From L1 optimization to halfspace depth”
Multivariate quantiles multiple-output regression quantiles L1 optimization halfspace depth
2010/3/10
First I would like to congratulate the authors for developing a new concept
of directional quantile contours. The work will contribute well to the pursuit
of multivariate quantiles. The multiple out...