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Modeling confounding by half-sibling regression. / Schölkopf, Bernhard; Hogg, David W; Wang, Dun; Foreman-Mackey, Daniel; Janzing, Dominik; Simon-Gabriel, Carl-Johann; Peters, Jonas.
In:
Proceedings of the National Academy of Sciences of the United States of America, Vol. 113, No. 27, 05.07.2016, p. 7391-7398.
Research output: Contribution to journal › Journal article › Research › peer-review
Harvard
Schölkopf, B, Hogg, DW, Wang, D, Foreman-Mackey, D, Janzing, D, Simon-Gabriel, C-J & Peters, J 2016, '
Modeling confounding by half-sibling regression',
Proceedings of the National Academy of Sciences of the United States of America, vol. 113, no. 27, pp. 7391-7398.
https://doi.org/10.1073/pnas.1511656113APA
Schölkopf, B., Hogg, D. W., Wang, D., Foreman-Mackey, D., Janzing, D., Simon-Gabriel, C-J., & Peters, J. (2016).
Modeling confounding by half-sibling regression.
Proceedings of the National Academy of Sciences of the United States of America,
113(27), 7391-7398.
https://doi.org/10.1073/pnas.1511656113Vancouver
Schölkopf B, Hogg DW, Wang D, Foreman-Mackey D, Janzing D, Simon-Gabriel C-J et al.
Modeling confounding by half-sibling regression.
Proceedings of the National Academy of Sciences of the United States of America. 2016 Jul 5;113(27):7391-7398.
https://doi.org/10.1073/pnas.1511656113Author
Schölkopf, Bernhard ; Hogg, David W ; Wang, Dun ; Foreman-Mackey, Daniel ; Janzing, Dominik ; Simon-Gabriel, Carl-Johann ; Peters, Jonas. / Modeling confounding by half-sibling regression. In: Proceedings of the National Academy of Sciences of the United States of America. 2016 ; Vol. 113, No. 27. pp. 7391-7398.
Bibtex
@article{7966f24598674040abcf41dab44e6099,
title = "Modeling confounding by half-sibling regression",
abstract = "We describe a method for removing the effect of confounders to reconstruct a latent quantity of interest. The method, referred to as {"}half-sibling regression,{"} is inspired by recent work in causal inference using additive noise models. We provide a theoretical justification, discussing both independent and identically distributed as well as time series data, respectively, and illustrate the potential of the method in a challenging astronomy application.",
keywords = "Journal Article",
author = "Bernhard Sch{\"o}lkopf and Hogg, {David W} and Dun Wang and Daniel Foreman-Mackey and Dominik Janzing and Carl-Johann Simon-Gabriel and Jonas Peters",
year = "2016",
month = jul,
day = "5",
doi = "10.1073/pnas.1511656113",
language = "English",
volume = "113",
pages = "7391--7398",
journal = "Proceedings of the National Academy of Sciences of the United States of America",
issn = "0027-8424",
publisher = "The National Academy of Sciences of the United States of America",
number = "27",
}
RIS
TY - JOUR
T1 - Modeling confounding by half-sibling regression
AU - Schölkopf, Bernhard
AU - Hogg, David W
AU - Wang, Dun
AU - Foreman-Mackey, Daniel
AU - Janzing, Dominik
AU - Simon-Gabriel, Carl-Johann
AU - Peters, Jonas
PY - 2016/7/5
Y1 - 2016/7/5
N2 - We describe a method for removing the effect of confounders to reconstruct a latent quantity of interest. The method, referred to as "half-sibling regression," is inspired by recent work in causal inference using additive noise models. We provide a theoretical justification, discussing both independent and identically distributed as well as time series data, respectively, and illustrate the potential of the method in a challenging astronomy application.
AB - We describe a method for removing the effect of confounders to reconstruct a latent quantity of interest. The method, referred to as "half-sibling regression," is inspired by recent work in causal inference using additive noise models. We provide a theoretical justification, discussing both independent and identically distributed as well as time series data, respectively, and illustrate the potential of the method in a challenging astronomy application.
KW - Journal Article
U2 - 10.1073/pnas.1511656113
DO - 10.1073/pnas.1511656113
M3 - Journal article
C2 - 27382154
VL - 113
SP - 7391
EP - 7398
JO - Proceedings of the National Academy of Sciences of the United States of America
JF - Proceedings of the National Academy of Sciences of the United States of America
SN - 0027-8424
IS - 27
ER -
