Small area estimation using reduced rank regression models

Tatjana von Rosen; Dietrich von Rosen

doi:10.1080/03610926.2019.1586946

Small area estimation using reduced rank regression models

Tatjana von Rosen
, Dietrich von Rosen

Department of Energy and Technology

Publication: Contribution to journal › Journal article › peer-review

Abstract

Small area estimation techniques have got a lot of attention during the last decades due to their important applications in survey studies. Mixed linear models and reduced rank regression analysis are jointly used when considering small area estimation. Estimates of parameters are presented as well as prediction of random effects and unobserved area measurements.

Original language	English
Pages (from-to)	3286-3297
Number of pages	12
Journal	Communications in Statistics - Theory and Methods
Volume	49
Issue number	13
DOIs	https://doi.org/10.1080/03610926.2019.1586946
Publication status	Published - 2020

Keywords

Growth curve model
mixed linear model
reduced rank regression

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10.1080/03610926.2019.1586946

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title = "Small area estimation using reduced rank regression models",

abstract = "Small area estimation techniques have got a lot of attention during the last decades due to their important applications in survey studies. Mixed linear models and reduced rank regression analysis are jointly used when considering small area estimation. Estimates of parameters are presented as well as prediction of random effects and unobserved area measurements.",

keywords = "Growth curve model, mixed linear model, reduced rank regression, Growth curve model, mixed linear model, reduced rank regression",

author = "\{von Rosen\}, Tatjana and \{von Rosen\}, Dietrich",

year = "2020",

doi = "10.1080/03610926.2019.1586946",

language = "English",

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journal = "Communications in Statistics - Theory and Methods",

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T1 - Small area estimation using reduced rank regression models

AU - von Rosen, Tatjana

AU - von Rosen, Dietrich

PY - 2020

Y1 - 2020

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AB - Small area estimation techniques have got a lot of attention during the last decades due to their important applications in survey studies. Mixed linear models and reduced rank regression analysis are jointly used when considering small area estimation. Estimates of parameters are presented as well as prediction of random effects and unobserved area measurements.

KW - Growth curve model

KW - mixed linear model

KW - reduced rank regression

KW - Growth curve model

KW - mixed linear model

KW - reduced rank regression

UR - https://res.slu.se/id/publ/100606

U2 - 10.1080/03610926.2019.1586946

DO - 10.1080/03610926.2019.1586946

M3 - Journal article

SN - 0361-0926

VL - 49

SP - 3286

EP - 3297

JO - Communications in Statistics - Theory and Methods

JF - Communications in Statistics - Theory and Methods

IS - 13

ER -

Small area estimation using reduced rank regression models

Abstract

Keywords

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