Density Estimation in Several Populations With Uncertain Population Membership

Yanyuan Ma; Jeffrey D. Hart; Raymond J. Carroll

doi:10.1198/jasa.2011.tm10798

Density Estimation in Several Populations With Uncertain Population Membership

Yanyuan Ma, Jeffrey D. Hart, Raymond J. Carroll

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

We devise methods to estimate probability density functions of several populations using observations with uncertain population membership, meaning from which population an observation comes is unknown. The probability of an observation being sampled from any given population can be calculated. We develop general estimation procedures and bandwidth selection methods for our setting. We establish large-sample properties and study finite-sample performance using simulation studies. We illustrate our methods with data from a nutrition study.

Original language	English (US)
Pages (from-to)	1180-1192
Number of pages	13
Journal	Journal of the American Statistical Association
Volume	106
Issue number	495
DOIs	https://doi.org/10.1198/jasa.2011.tm10798
State	Published - Sep 2011
Externally published	Yes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUS-CI-016-04
Acknowledgements: This publication is based in part on work supported by King Abdullah University of Science and Technology (award KUS-CI-016-04).
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

Access to Document

10.1198/jasa.2011.tm10798

Cite this

@article{bcec4ebd35ed4044ac484e6e8a50072f,

title = "Density Estimation in Several Populations With Uncertain Population Membership",

abstract = "We devise methods to estimate probability density functions of several populations using observations with uncertain population membership, meaning from which population an observation comes is unknown. The probability of an observation being sampled from any given population can be calculated. We develop general estimation procedures and bandwidth selection methods for our setting. We establish large-sample properties and study finite-sample performance using simulation studies. We illustrate our methods with data from a nutrition study.",

author = "Yanyuan Ma and Hart, {Jeffrey D.} and Carroll, {Raymond J.}",

note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledged KAUST grant number(s): KUS-CI-016-04 Acknowledgements: This publication is based in part on work supported by King Abdullah University of Science and Technology (award KUS-CI-016-04). This publication acknowledges KAUST support, but has no KAUST affiliated authors.",

year = "2011",

month = sep,

doi = "10.1198/jasa.2011.tm10798",

language = "English (US)",

volume = "106",

pages = "1180--1192",

journal = "Journal of the American Statistical Association",

issn = "0162-1459",

publisher = "Taylor and Francis Ltd.",

number = "495",

}

TY - JOUR

T1 - Density Estimation in Several Populations With Uncertain Population Membership

AU - Ma, Yanyuan

AU - Hart, Jeffrey D.

AU - Carroll, Raymond J.

N1 - KAUST Repository Item: Exported on 2020-10-01 Acknowledged KAUST grant number(s): KUS-CI-016-04 Acknowledgements: This publication is based in part on work supported by King Abdullah University of Science and Technology (award KUS-CI-016-04). This publication acknowledges KAUST support, but has no KAUST affiliated authors.

PY - 2011/9

Y1 - 2011/9

N2 - We devise methods to estimate probability density functions of several populations using observations with uncertain population membership, meaning from which population an observation comes is unknown. The probability of an observation being sampled from any given population can be calculated. We develop general estimation procedures and bandwidth selection methods for our setting. We establish large-sample properties and study finite-sample performance using simulation studies. We illustrate our methods with data from a nutrition study.

AB - We devise methods to estimate probability density functions of several populations using observations with uncertain population membership, meaning from which population an observation comes is unknown. The probability of an observation being sampled from any given population can be calculated. We develop general estimation procedures and bandwidth selection methods for our setting. We establish large-sample properties and study finite-sample performance using simulation studies. We illustrate our methods with data from a nutrition study.

UR - http://hdl.handle.net/10754/597926

UR - http://www.tandfonline.com/doi/abs/10.1198/jasa.2011.tm10798

UR - http://www.scopus.com/inward/record.url?scp=80054692410&partnerID=8YFLogxK

U2 - 10.1198/jasa.2011.tm10798

DO - 10.1198/jasa.2011.tm10798

M3 - Article

C2 - 22368314

SN - 0162-1459

VL - 106

SP - 1180

EP - 1192

JO - Journal of the American Statistical Association

JF - Journal of the American Statistical Association

IS - 495

ER -

Density Estimation in Several Populations With Uncertain Population Membership

Abstract

Bibliographical note

Access to Document

Other files and links

Fingerprint

Cite this