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

Institutionen för energi och teknik

Publikation: Bidrag till tidskrift › Artikel i vetenskaplig tidskrift › Peer review

Sammanfattning

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.

Originalspråk	Engelska
Sidor (från-till)	3286-3297
Antal sidor	12
Tidskrift	Communications in Statistics - Theory and Methods
Volym	49
Nummer	13
DOI	https://doi.org/10.1080/03610926.2019.1586946
Status	Publicerad - 2020

Nyckelord

Growth curve model
mixed linear model
reduced rank regression

Åtkomst av dokument

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.",

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