Moment-based Estimation of Mixtures of Regression Models
Research output: Contribution to journal › Journal article › Research
Standard
Moment-based Estimation of Mixtures of Regression Models. / Ekstrøm, Claus Thorn; Pipper, Christian Bressen.
In: arXiv, 2019.Research output: Contribution to journal › Journal article › Research
Harvard
APA
Vancouver
Author
Bibtex
}
RIS
TY - JOUR
T1 - Moment-based Estimation of Mixtures of Regression Models
AU - Ekstrøm, Claus Thorn
AU - Pipper, Christian Bressen
N1 - 17 pages, 3 figures
PY - 2019
Y1 - 2019
N2 - Finite mixtures of regression models provide a flexible modeling framework for many phenomena. Using moment-based estimation of the regression parameters, we develop unbiased estimators with a minimum of assumptions on the mixture components. In particular, only the average regression model for one of the components in the mixture model is needed and no requirements on the distributions. The consistency and asymptotic distribution of the estimators is derived and the proposed method is validated through a series of simulation studies and is shown to be highly accurate. We illustrate the use of the moment-based mixture of regression models with an application to wine quality data.
AB - Finite mixtures of regression models provide a flexible modeling framework for many phenomena. Using moment-based estimation of the regression parameters, we develop unbiased estimators with a minimum of assumptions on the mixture components. In particular, only the average regression model for one of the components in the mixture model is needed and no requirements on the distributions. The consistency and asymptotic distribution of the estimators is derived and the proposed method is validated through a series of simulation studies and is shown to be highly accurate. We illustrate the use of the moment-based mixture of regression models with an application to wine quality data.
KW - math.ST
KW - stat.AP
KW - stat.ME
KW - stat.TH
M3 - Journal article
JO - arXiv
JF - arXiv
ER -
ID: 225383377