搜索结果: 1-10 共查到“科学技术统计学 regression”相关记录10条 . 查询时间(0.015 秒)
High dimensional stochastic regression with latent factors, endogeneity and nonlinearity
α-mixing dimension reduction instrument variables nonstationarity time series
2016/1/25
We consider a multivariate time series model which represents a high dimensional vector process as a sum of three terms: a linear regression of some observed regressors,a linear combination of some la...
Nonparametric Regression with Discrete Covariate and Missing Values
Nonparametric Regression Discrete kernel smoothing Imputation Missing Values Variance Reduction
2016/1/19
We consider nonparametric regression with a mixture of continuous and discrete ex-planatory variables where realizations of the response variable may be missing. An impu-tation based nonparametric reg...
Information Criteria for Deciding between Normal Regression Models
Information Criteria Deciding between Normal Regression Models
2013/6/14
Regression models fitted to data can be assessed on their goodness of fit, though models with many parameters should be disfavored to prevent over-fitting. Statisticians' tools for this are little kno...
Robust Logistic Regression using Shift Parameters
Robust Logistic Regression Shift Parameters
2013/6/17
Annotation errors can significantly hurt classifier performance, yet datasets are only growing noisier with the increased use of Amazon Mechanical Turk and techniques like distant supervision that aut...
We propose a new method named calibrated multivariate regression (CMR) for fitting high dimensional multivariate regression models. Compared to existing methods, CMR calibrates the regularization for ...
Switching Nonparametric Regression Models and the Motorcycle Data revisited
nonparametric regression machine learning mixture of Gaussian processes latent variables EM algorithm motorcy-cle data
2013/6/14
We propose a methodology to analyze data arising from a curve that, over its domain, switches among J states. We consider a sequence of response variables, where each response y depends on a covariate...
This paper explores the homogeneity of coefficients in high-dimensional regression, which extends the sparsity concept and is more general and suitable for many applications. Homogeneity arises when o...
Pivotal estimation in high-dimensional regression via linear programming
Pivotal estimation high-dimensional regression inear programming
2013/4/28
We propose a new method of estimation in high-dimensional linear regression model. It allows for very weak distributional assumptions including heteroscedasticity, and does not require the knowledge o...
Regression with Distance Matrices
functional data analysis mixed data multidimensional scaling shape correlation ma-trix
2013/4/27
Data types that lie in metric spaces but not in vector spaces are difficult to use within the usual regression setting, either as the response and/or a predictor. We represent the information in these...
Distributional Results for Thresholding Estimators in High-Dimensional Gaussian Regression Models
Markov chain Monte Carlo Hamiltonian dynamics Bayesian analysis
2011/7/6
We study the distribution of hard-, soft-, and adaptive soft-thresholding estimators within a linear regression model where the number of parameters k can depend on sample size n and may diverge with ...