liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
On estimation in some reduced rank extended growth curve models
Linköping University, Department of Mathematics, Mathematical Statistics . Linköping University, Faculty of Science & Engineering. Dept. Energy and Technology, Swedish Univ. of Agricultural Sci., Uppsala, Sweden.
Dept. Statist.Stockholm Univ., Stockholm, Sweden.
2017 (English)In: Mathematical Methods of Statistics, ISSN 1066-5307, E-ISSN 1934-8045, Vol. 26, no 4, p. 299-310Article in journal (Refereed) Published
Abstract [en]

The general multivariate analysis of variance model has been extensively studied in the statistical literature and successfully applied in many different fields for analyzing longitudinal data. In this article, we consider the extension of this model having two sets of regressors constituting a growth curve portion and a multivariate analysis of variance portion, respectively. Nowadays, the data collected in empirical studies have relatively complex structures though often demanding a parsimonious modeling. This can be achieved for example through imposing rank constraints on the regression coefficient matrices. The reduced rank regression structure also provides a theoretical interpretation in terms of latent variables. We derive likelihood based estimators for the mean parameters and covariance matrix in this type of models. A numerical example is provided to illustrate the obtained results.

Place, publisher, year, edition, pages
New York, NY, United States: Allerton Press, Inc. , 2017. Vol. 26, no 4, p. 299-310
Keywords [en]
growth curve model, maximum likelihood estimator, multivariate analysis of variance, reduced rank model
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:liu:diva-152254DOI: 10.3103/S1066530717040044Scopus ID: 2-s2.0-85039067289OAI: oai:DiVA.org:liu-152254DiVA, id: diva2:1258240
Available from: 2018-10-24 Created: 2018-10-24 Last updated: 2019-01-09Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

von Rosen, Dietrich

Search in DiVA

By author/editor
von Rosen, Dietrich
By organisation
Mathematical Statistics Faculty of Science & Engineering
In the same journal
Mathematical Methods of Statistics
Probability Theory and Statistics

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 42 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf