Generalised De-Preferential Random Graphs
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
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| _version_ | 1866909960172994560 |
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| author | Bandyopadhyay, Antar Joshi, Kunal |
| author_facet | Bandyopadhyay, Antar Joshi, Kunal |
| contents | We consider some further generalizations of the novel random graph models as introduced by Bandyopadhyay and Sen \cite{BaSe2025} and find asymptotic for the degree of a fixed vertex and along with the asymptotic degree distribution. We show that in the \emph{case of the inverse power law} the order of these statistics is much slower than the case of the simple inverse function, which was considered in \cite{BaSe2025}. However, the results for the linear case remain exactly the same even after introducing a "shift" parameter. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_12408 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Generalised De-Preferential Random Graphs Bandyopadhyay, Antar Joshi, Kunal Probability We consider some further generalizations of the novel random graph models as introduced by Bandyopadhyay and Sen \cite{BaSe2025} and find asymptotic for the degree of a fixed vertex and along with the asymptotic degree distribution. We show that in the \emph{case of the inverse power law} the order of these statistics is much slower than the case of the simple inverse function, which was considered in \cite{BaSe2025}. However, the results for the linear case remain exactly the same even after introducing a "shift" parameter. |
| title | Generalised De-Preferential Random Graphs |
| topic | Probability |
| url | https://arxiv.org/abs/2512.12408 |