A Phase Transition for Large Values of Bifurcating Autoregressive Models
We describe the asymptotic behavior of the number Z n [ a n , ∞ ) of individuals with a large value in a stable bifurcating autoregressive process, where a n → ∞ . The study of the associated first moment is equivalent to the annealed large deviation problem of an autoregressive process in a random...
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Veröffentlicht in: | Journal of theoretical probability 2021-12, Vol.34 (4), p.2081-2116 |
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container_issue | 4 |
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container_title | Journal of theoretical probability |
container_volume | 34 |
creator | Bansaye, Vincent Bitseki Penda, S. Valère |
description | We describe the asymptotic behavior of the number
Z
n
[
a
n
,
∞
)
of individuals with a large value in a stable bifurcating autoregressive process, where
a
n
→
∞
. The study of the associated first moment is equivalent to the annealed large deviation problem of an autoregressive process in a random environment. The trajectorial behavior of
Z
n
[
a
n
,
∞
)
is obtained by the study of the ancestral paths corresponding to the large deviation event together with the environment of the process. This study of large deviations of autoregressive processes in random environment is of independent interest and achieved first. The estimates for bifurcating autoregressive process involve then a law of large numbers for non-homogenous trees. Two regimes appear in the stable case, depending on whether one of the autoregressive parameters is greater than 1 or not. It yields different asymptotic behaviors for large local densities and maximal value of the bifurcating autoregressive process. |
doi_str_mv | 10.1007/s10959-020-01033-w |
format | Article |
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Z
n
[
a
n
,
∞
)
of individuals with a large value in a stable bifurcating autoregressive process, where
a
n
→
∞
. The study of the associated first moment is equivalent to the annealed large deviation problem of an autoregressive process in a random environment. The trajectorial behavior of
Z
n
[
a
n
,
∞
)
is obtained by the study of the ancestral paths corresponding to the large deviation event together with the environment of the process. This study of large deviations of autoregressive processes in random environment is of independent interest and achieved first. The estimates for bifurcating autoregressive process involve then a law of large numbers for non-homogenous trees. Two regimes appear in the stable case, depending on whether one of the autoregressive parameters is greater than 1 or not. It yields different asymptotic behaviors for large local densities and maximal value of the bifurcating autoregressive process.</description><identifier>ISSN: 0894-9840</identifier><identifier>EISSN: 1572-9230</identifier><identifier>DOI: 10.1007/s10959-020-01033-w</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Asymptotic properties ; Autoregressive models ; Autoregressive processes ; Bifurcations ; Deviation ; Mathematics ; Mathematics and Statistics ; Phase transitions ; Probability ; Probability Theory and Stochastic Processes ; Statistics</subject><ispartof>Journal of theoretical probability, 2021-12, Vol.34 (4), p.2081-2116</ispartof><rights>Springer Science+Business Media, LLC, part of Springer Nature 2020</rights><rights>Springer Science+Business Media, LLC, part of Springer Nature 2020.</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c397t-be04c93c4c1f839e1bccb1024f356c24e096f05228a78d9f00559632a44856b23</citedby><cites>FETCH-LOGICAL-c397t-be04c93c4c1f839e1bccb1024f356c24e096f05228a78d9f00559632a44856b23</cites><orcidid>0000-0001-8728-1586 ; 0000-0002-7631-3244</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10959-020-01033-w$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10959-020-01033-w$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>230,314,776,780,881,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://hal.science/hal-03034151$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Bansaye, Vincent</creatorcontrib><creatorcontrib>Bitseki Penda, S. Valère</creatorcontrib><title>A Phase Transition for Large Values of Bifurcating Autoregressive Models</title><title>Journal of theoretical probability</title><addtitle>J Theor Probab</addtitle><description>We describe the asymptotic behavior of the number
Z
n
[
a
n
,
∞
)
of individuals with a large value in a stable bifurcating autoregressive process, where
a
n
→
∞
. The study of the associated first moment is equivalent to the annealed large deviation problem of an autoregressive process in a random environment. The trajectorial behavior of
Z
n
[
a
n
,
∞
)
is obtained by the study of the ancestral paths corresponding to the large deviation event together with the environment of the process. This study of large deviations of autoregressive processes in random environment is of independent interest and achieved first. The estimates for bifurcating autoregressive process involve then a law of large numbers for non-homogenous trees. Two regimes appear in the stable case, depending on whether one of the autoregressive parameters is greater than 1 or not. It yields different asymptotic behaviors for large local densities and maximal value of the bifurcating autoregressive process.</description><subject>Asymptotic properties</subject><subject>Autoregressive models</subject><subject>Autoregressive processes</subject><subject>Bifurcations</subject><subject>Deviation</subject><subject>Mathematics</subject><subject>Mathematics and Statistics</subject><subject>Phase transitions</subject><subject>Probability</subject><subject>Probability Theory and Stochastic Processes</subject><subject>Statistics</subject><issn>0894-9840</issn><issn>1572-9230</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp9kL1OwzAURi0EEqXwAkyWmBgC139JPAYEFKkIhsJqOa6dpgpxsZNWvD0pQbAxWbo633d9D0LnBK4IQHYdCUghE6CQAAHGkt0BmhCR0URSBodoArnkicw5HKOTGNcAICXABM0K_LLS0eJF0G2su9q32PmA5zpUFr_pprcRe4dvatcHo7u6rXDRdz7YKtgY663FT35pm3iKjpxuoj37eafo9f5ucTtL5s8Pj7fFPDFMZl1SWuBGMsMNcTmTlpTGlAQod0ykhnILMnUgKM11li-lAxBCpoxqznORlpRN0eXYu9KN2oT6XYdP5XWtZsVc7WfAgHEiyJYM7MXIboL_GA7p1Nr3oR2-p6gYtuc5SfcUHSkTfIzBut9aAmpvV4121WBXfdtVuyHExlAc4Lay4a_6n9QXiwp7Ew</recordid><startdate>20211201</startdate><enddate>20211201</enddate><creator>Bansaye, Vincent</creator><creator>Bitseki Penda, S. Valère</creator><general>Springer US</general><general>Springer Nature B.V</general><general>Springer</general><scope>AAYXX</scope><scope>CITATION</scope><scope>1XC</scope><orcidid>https://orcid.org/0000-0001-8728-1586</orcidid><orcidid>https://orcid.org/0000-0002-7631-3244</orcidid></search><sort><creationdate>20211201</creationdate><title>A Phase Transition for Large Values of Bifurcating Autoregressive Models</title><author>Bansaye, Vincent ; Bitseki Penda, S. Valère</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c397t-be04c93c4c1f839e1bccb1024f356c24e096f05228a78d9f00559632a44856b23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Asymptotic properties</topic><topic>Autoregressive models</topic><topic>Autoregressive processes</topic><topic>Bifurcations</topic><topic>Deviation</topic><topic>Mathematics</topic><topic>Mathematics and Statistics</topic><topic>Phase transitions</topic><topic>Probability</topic><topic>Probability Theory and Stochastic Processes</topic><topic>Statistics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bansaye, Vincent</creatorcontrib><creatorcontrib>Bitseki Penda, S. Valère</creatorcontrib><collection>CrossRef</collection><collection>Hyper Article en Ligne (HAL)</collection><jtitle>Journal of theoretical probability</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bansaye, Vincent</au><au>Bitseki Penda, S. Valère</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Phase Transition for Large Values of Bifurcating Autoregressive Models</atitle><jtitle>Journal of theoretical probability</jtitle><stitle>J Theor Probab</stitle><date>2021-12-01</date><risdate>2021</risdate><volume>34</volume><issue>4</issue><spage>2081</spage><epage>2116</epage><pages>2081-2116</pages><issn>0894-9840</issn><eissn>1572-9230</eissn><abstract>We describe the asymptotic behavior of the number
Z
n
[
a
n
,
∞
)
of individuals with a large value in a stable bifurcating autoregressive process, where
a
n
→
∞
. The study of the associated first moment is equivalent to the annealed large deviation problem of an autoregressive process in a random environment. The trajectorial behavior of
Z
n
[
a
n
,
∞
)
is obtained by the study of the ancestral paths corresponding to the large deviation event together with the environment of the process. This study of large deviations of autoregressive processes in random environment is of independent interest and achieved first. The estimates for bifurcating autoregressive process involve then a law of large numbers for non-homogenous trees. Two regimes appear in the stable case, depending on whether one of the autoregressive parameters is greater than 1 or not. It yields different asymptotic behaviors for large local densities and maximal value of the bifurcating autoregressive process.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s10959-020-01033-w</doi><tpages>36</tpages><orcidid>https://orcid.org/0000-0001-8728-1586</orcidid><orcidid>https://orcid.org/0000-0002-7631-3244</orcidid><oa>free_for_read</oa></addata></record> |
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source | SpringerLink Journals - AutoHoldings |
subjects | Asymptotic properties Autoregressive models Autoregressive processes Bifurcations Deviation Mathematics Mathematics and Statistics Phase transitions Probability Probability Theory and Stochastic Processes Statistics |
title | A Phase Transition for Large Values of Bifurcating Autoregressive Models |
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