Sliced inverse regression pdf

Save to Binder. Create a New Binder Name. Cancel Create. Previous Article Next Article. Login options Check if you have access through your login credentials or your institution to get full access on this article. Sign in. Full Access Get this Article. Information Contributors Published in. ISSN: United States. Author Tags missing at random estimating equations sliced inverse regression double robustness Grassmann manifold optimization.

Qualifiers article. Funding Sources. Other Metrics View Article Metrics. More Filters. Sliced Inverse Regression for big data analysis. Modem advances in computing power have greatly widened scientists' scope in gathering and investigating information from many variables.

We describe sliced inverse regression SIR , for reducing the … Expand. This model includes a dimension reduction … Expand. View 2 excerpts, cites methods and background.

Cluster-based Sliced Inverse Regression. Abstract In the theory of sufficient dimension reduction, Sliced Inverse Regression SIR is a famous technique that enables us to reduce the dimensionality of regression problems. This … Expand. Asymptotic optimality for sliced inverse regression. Dimension reduction in regression aims at improving poor convergence rates derived from the nonparametric estimation of the regression function in large dimension.

It attempts to provide methods that … Expand. View 3 excerpts, cites methods and background. Bayesian inverse regression for supervised dimension reduction with small datasets. ABSTRACT We consider supervised dimension reduction problems, namely to identify a low dimensional projection of the predictors which can retain the statistical relationship between and the response … Expand.

Bayesian inverse regression for dimension reduction with small datasets. Highly Influenced. View 5 excerpts, cites background and methods.

Collaborative sliced inverse regression. View 3 excerpts, cites background and results. Highly Influenced. View 5 excerpts, cites methods and background. Dimension reduction via Sliced Inverse Regression: Ideas and new proposals. In this thesis, Sliced Inverse Regression SIR , a method for semi-parametric dimension reduction is discussed, analyzed and extended.

Contributions to dimension reduction in regression problems. This report summarizes my contributions to regression methods in high-dimensional settings.

Standard regression methods linear or nonlinear suffer from the so-called curse of dimensionality when … Expand. View 1 excerpt, cites methods. Mathematics, Computer Science. Advances in Contemporary Statistics and Econometrics. Sliced inverse regression SIR focuses on the relationship between a dependent variable y and a p-dimensional explanatory variable x in a semiparametric regression model, in which, the link relies … Expand. In this model, the main goal is … Expand.

Sliced Inverse Regression for Dimension Reduction. Abstract Modern advances in computing power have greatly widened scientists' scope in gathering and investigating information from many variables, information which might have been ignored in the … Expand. Highly Influential.

View 9 excerpts, references background and methods. An asymptotic theory for sliced inverse regression. Sliced Inverse Regression S. Li considers a general regression model of the … Expand.