Parameter Estimators of Sparse Random Intersection Graphs with Thinned Communities

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussavertaisarvioitu

Standard

Parameter Estimators of Sparse Random Intersection Graphs with Thinned Communities. / Karjalainen, Joona; van Leeuwaarden, J.; Leskelä, Lasse.

Algorithms and Models for the Web Graph: 15th International Workshop, WAW 2018, Moscow, Russia, May 17-18, 2018, Proceedings. toim. / Anthony Bonato; Paweł Prałat; Andrei Raigorodskii. 2018. s. 44-58 (Lecture Notes in Computer Science ; Vuosikerta 10836).

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussavertaisarvioitu

Harvard

Karjalainen, J, van Leeuwaarden, J & Leskelä, L 2018, Parameter Estimators of Sparse Random Intersection Graphs with Thinned Communities. julkaisussa A Bonato, P Prałat & A Raigorodskii (toim), Algorithms and Models for the Web Graph: 15th International Workshop, WAW 2018, Moscow, Russia, May 17-18, 2018, Proceedings. Lecture Notes in Computer Science , Vuosikerta. 10836, Sivut 44-58, Moscow, Venäjä, 17/05/2018. https://doi.org/10.1007/978-3-319-92871-5_4

APA

Karjalainen, J., van Leeuwaarden, J., & Leskelä, L. (2018). Parameter Estimators of Sparse Random Intersection Graphs with Thinned Communities. teoksessa A. Bonato, P. Prałat, & A. Raigorodskii (Toimittajat), Algorithms and Models for the Web Graph: 15th International Workshop, WAW 2018, Moscow, Russia, May 17-18, 2018, Proceedings (Sivut 44-58). (Lecture Notes in Computer Science ; Vuosikerta 10836). https://doi.org/10.1007/978-3-319-92871-5_4

Vancouver

Karjalainen J, van Leeuwaarden J, Leskelä L. Parameter Estimators of Sparse Random Intersection Graphs with Thinned Communities. julkaisussa Bonato A, Prałat P, Raigorodskii A, toimittajat, Algorithms and Models for the Web Graph: 15th International Workshop, WAW 2018, Moscow, Russia, May 17-18, 2018, Proceedings. 2018. s. 44-58. (Lecture Notes in Computer Science ). https://doi.org/10.1007/978-3-319-92871-5_4

Author

Karjalainen, Joona ; van Leeuwaarden, J. ; Leskelä, Lasse. / Parameter Estimators of Sparse Random Intersection Graphs with Thinned Communities. Algorithms and Models for the Web Graph: 15th International Workshop, WAW 2018, Moscow, Russia, May 17-18, 2018, Proceedings. Toimittaja / Anthony Bonato ; Paweł Prałat ; Andrei Raigorodskii. 2018. Sivut 44-58 (Lecture Notes in Computer Science ).

Bibtex - Lataa

@inproceedings{6cfdf83f23e74a6cb5ee980ba1c86521,
title = "Parameter Estimators of Sparse Random Intersection Graphs with Thinned Communities",
abstract = "This paper studies a statistical network model generated by a large number of randomly sized overlapping communities, where any pair of nodes sharing a community is linked with probability q via the community. In the special case with q=1 the model reduces to a random intersection graph which is known to generate high levels of transitivity also in the sparse context. The parameter q adds a degree of freedom and leads to a parsimonious and analytically tractable network model with tunable density, transitivity, and degree fluctuations. We prove that the parameters of this model can be consistently estimated in the large and sparse limiting regime using moment estimators based on partially observed densities of links, 2-stars, and triangles.",
keywords = "Random Graphs, Statistics, Network Analysis, Probability",
author = "Joona Karjalainen and {van Leeuwaarden}, J. and Lasse Leskel{\"a}",
year = "2018",
month = "5",
doi = "10.1007/978-3-319-92871-5_4",
language = "English",
isbn = "978-3-319-92870-8",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "44--58",
editor = "Anthony Bonato and Paweł Prałat and Andrei Raigorodskii",
booktitle = "Algorithms and Models for the Web Graph",

}

RIS - Lataa

TY - GEN

T1 - Parameter Estimators of Sparse Random Intersection Graphs with Thinned Communities

AU - Karjalainen, Joona

AU - van Leeuwaarden, J.

AU - Leskelä, Lasse

PY - 2018/5

Y1 - 2018/5

N2 - This paper studies a statistical network model generated by a large number of randomly sized overlapping communities, where any pair of nodes sharing a community is linked with probability q via the community. In the special case with q=1 the model reduces to a random intersection graph which is known to generate high levels of transitivity also in the sparse context. The parameter q adds a degree of freedom and leads to a parsimonious and analytically tractable network model with tunable density, transitivity, and degree fluctuations. We prove that the parameters of this model can be consistently estimated in the large and sparse limiting regime using moment estimators based on partially observed densities of links, 2-stars, and triangles.

AB - This paper studies a statistical network model generated by a large number of randomly sized overlapping communities, where any pair of nodes sharing a community is linked with probability q via the community. In the special case with q=1 the model reduces to a random intersection graph which is known to generate high levels of transitivity also in the sparse context. The parameter q adds a degree of freedom and leads to a parsimonious and analytically tractable network model with tunable density, transitivity, and degree fluctuations. We prove that the parameters of this model can be consistently estimated in the large and sparse limiting regime using moment estimators based on partially observed densities of links, 2-stars, and triangles.

KW - Random Graphs

KW - Statistics

KW - Network Analysis

KW - Probability

U2 - 10.1007/978-3-319-92871-5_4

DO - 10.1007/978-3-319-92871-5_4

M3 - Conference contribution

SN - 978-3-319-92870-8

T3 - Lecture Notes in Computer Science

SP - 44

EP - 58

BT - Algorithms and Models for the Web Graph

A2 - Bonato, Anthony

A2 - Prałat, Paweł

A2 - Raigorodskii, Andrei

ER -

ID: 21779775