Graphical Models for Associations between Variables, some of which are Qualitative and some Quantitative

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Graphical Models for Associations between Variables, some of which are Qualitative and some Quantitative. / Lauritzen, Steffen L.; WERMUTH, N.

In: Annals of Statistics, Vol. 17, No. 1, 1989, p. 31-57.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Lauritzen, SL & WERMUTH, N 1989, 'Graphical Models for Associations between Variables, some of which are Qualitative and some Quantitative', Annals of Statistics, vol. 17, no. 1, pp. 31-57. https://doi.org/10.1214/aos/1176347003

APA

Lauritzen, S. L., & WERMUTH, N. (1989). Graphical Models for Associations between Variables, some of which are Qualitative and some Quantitative. Annals of Statistics, 17(1), 31-57. https://doi.org/10.1214/aos/1176347003

Vancouver

Lauritzen SL, WERMUTH N. Graphical Models for Associations between Variables, some of which are Qualitative and some Quantitative. Annals of Statistics. 1989;17(1):31-57. https://doi.org/10.1214/aos/1176347003

Author

Lauritzen, Steffen L. ; WERMUTH, N. / Graphical Models for Associations between Variables, some of which are Qualitative and some Quantitative. In: Annals of Statistics. 1989 ; Vol. 17, No. 1. pp. 31-57.

Bibtex

@article{1ac44d4ec0994d60b1c0d1290d9c2568,
title = "Graphical Models for Associations between Variables, some of which are Qualitative and some Quantitative",
abstract = "We define and investigate classes of statistical models for the analysis of associations between variables, some of which are qualitative and some quantitative. In the cases where only one kind of variables is present, the models are well-known models for either contingency tables or covariance structures. We characterize the subclass of decomposable models where the statistical theory is especially simple. All models can be represented by a graph with one vertex for each variable. The vertices are possibly connected with arrows or lines corresponding to directional or symmetric associations being present. Pairs of vertices that are not connected are conditionally independent given some of the remaining variables according to specific rules.",
author = "Lauritzen, {Steffen L.} and N WERMUTH",
year = "1989",
doi = "10.1214/aos/1176347003",
language = "English",
volume = "17",
pages = "31--57",
journal = "Annals of Statistics",
issn = "0090-5364",
publisher = "Institute of Mathematical Statistics",
number = "1",

}

RIS

TY - JOUR

T1 - Graphical Models for Associations between Variables, some of which are Qualitative and some Quantitative

AU - Lauritzen, Steffen L.

AU - WERMUTH, N

PY - 1989

Y1 - 1989

N2 - We define and investigate classes of statistical models for the analysis of associations between variables, some of which are qualitative and some quantitative. In the cases where only one kind of variables is present, the models are well-known models for either contingency tables or covariance structures. We characterize the subclass of decomposable models where the statistical theory is especially simple. All models can be represented by a graph with one vertex for each variable. The vertices are possibly connected with arrows or lines corresponding to directional or symmetric associations being present. Pairs of vertices that are not connected are conditionally independent given some of the remaining variables according to specific rules.

AB - We define and investigate classes of statistical models for the analysis of associations between variables, some of which are qualitative and some quantitative. In the cases where only one kind of variables is present, the models are well-known models for either contingency tables or covariance structures. We characterize the subclass of decomposable models where the statistical theory is especially simple. All models can be represented by a graph with one vertex for each variable. The vertices are possibly connected with arrows or lines corresponding to directional or symmetric associations being present. Pairs of vertices that are not connected are conditionally independent given some of the remaining variables according to specific rules.

U2 - 10.1214/aos/1176347003

DO - 10.1214/aos/1176347003

M3 - Journal article

VL - 17

SP - 31

EP - 57

JO - Annals of Statistics

JF - Annals of Statistics

SN - 0090-5364

IS - 1

ER -

ID: 127879916