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Annals of the Institute of Statistical Mathematics : Volume 69

Annals of the Institute of Statistical Mathematics : Volume 68

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Annals of the Institute of Statistical Mathematics : Volume 60

Annals of the Institute of Statistical Mathematics : Volume 60, Issue 4, December 2008

Preface: Featured section on data-mining and statistical science

Direct importance estimation for covariate shift adaptation

A preferential attachment model with Poisson growth for scale-free networks

Measuring the baseline sales and the promotion effect for incense products: a Bayesian state-space modeling approach

An angular–linear time series model for waveheight prediction

On a simple strategy weakly forcing the strong law of large numbers in the bounded forecasting game

Local empirical processes near boundaries of convex bodies

Estimating a mean matrix: boosting efficiency by multiple affine shrinkage

On potentially negative space time covariances obtained as sum of products of marginal ones

Second-order nonlinear least squares estimation

Semi-self-decomposable distributions on Z+

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A preferential attachment model with Poisson growth for scale-free networks

Content Provider	Springer Nature Link
Author	Sheridan, Paul Yagahara, Yuichi Shimodaira, Hidetoshi
Copyright Year	2008
Abstract	We propose a scale-free network model with a tunable power-law exponent. The Poisson growth model, as we call it, is an offshoot of the celebrated model of Barabási and Albert where a network is generated iteratively from a small seed network; at each step a node is added together with a number of incident edges preferentially attached to nodes already in the network. A key feature of our model is that the number of edges added at each step is a random variable with Poisson distribution, and, unlike the Barabási–Albert model where this quantity is fixed, it can generate any network. Our model is motivated by an application in Bayesian inference implemented as Markov chain Monte Carlo to estimate a network; for this purpose, we also give a formula for the probability of a network under our model.
Starting Page	747
Ending Page	761
Page Count	15
File Format	PDF
ISSN	00203157
Journal	Annals of the Institute of Statistical Mathematics
Volume Number	60
Issue Number	4
e-ISSN	15729052
Language	English
Publisher	Springer-Verlag
Publisher Date	2008-07-10
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Bayesian inference Complex networks Network models Power-law Scale-free Statistics for Business/Economics/Mathematical Finance/Insurance Statistics
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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