Estimation in High-Dimensional Analysis and Multivariate Linear Models

Abstract

This article presents a new approach of estimating the parameters describing the mean structure in the Growth Curve model when the number of variables compared with the number of observations is large. An unbiased, consistent, and asymptotic normal estimator is derived as well as its.

Keywords

Growth Curve model; High-dimensional analysis; Kolmogorov asymptotics; Parameter estimation; p/n -asymptotics

Published in

Communications in Statistics - Theory and Methods
2011, volume: 40, number: 7, pages: 1241-1253
Publisher: TAYLOR & FRANCIS INC

SLU Authors

• von Rosen, Dietrich

  • Department of Energy and Technology, Swedish University of Agricultural Sciences
    

UKÄ Subject classification

Probability Theory and Statistics

Publication identifier

• DOI: https://doi.org/10.1080/03610920903576556

Permanent link to this page (URI)

https://res.slu.se/id/publ/57336