The largest order statistics for the inradius in an isotropic STIT tessellation
A planar stationary and isotropic STIT tessellation at time t > 0 is observed in the window W ρ = t − 1 π ρ ⋅ [ − 1 2 , 1 2 ] 2 , for ρ > 0. With each cell of the tessellation, we associate the inradius, which is the radius of the largest disk contained in the cell. Using the Chen-Stein method...
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| Veröffentlicht in: | Extremes (Boston) 2019-12, Vol.22 (4), p.571-598 |
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| creator | Chenavier, Nicolas Nagel, Werner |
| description | A planar stationary and isotropic STIT tessellation at time
t
> 0 is observed in the window
W
ρ
=
t
−
1
π
ρ
⋅
[
−
1
2
,
1
2
]
2
, for
ρ
> 0. With each cell of the tessellation, we associate the inradius, which is the radius of the largest disk contained in the cell. Using the Chen-Stein method, we compute the limit distributions of the largest order statistics for the inradii of all cells whose nuclei are contained in
W
ρ
as
ρ
goes to infinity. |
| doi_str_mv | 10.1007/s10687-019-00356-0 |
| format | Article |
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t
> 0 is observed in the window
W
ρ
=
t
−
1
π
ρ
⋅
[
−
1
2
,
1
2
]
2
, for
ρ
> 0. With each cell of the tessellation, we associate the inradius, which is the radius of the largest disk contained in the cell. Using the Chen-Stein method, we compute the limit distributions of the largest order statistics for the inradii of all cells whose nuclei are contained in
W
ρ
as
ρ
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t
> 0 is observed in the window
W
ρ
=
t
−
1
π
ρ
⋅
[
−
1
2
,
1
2
]
2
, for
ρ
> 0. With each cell of the tessellation, we associate the inradius, which is the radius of the largest disk contained in the cell. Using the Chen-Stein method, we compute the limit distributions of the largest order statistics for the inradii of all cells whose nuclei are contained in
W
ρ
as
ρ
goes to infinity.</description><subject>Civil Engineering</subject><subject>Economics</subject><subject>Environmental Management</subject><subject>Finance</subject><subject>Hydrogeology</subject><subject>Insurance</subject><subject>Management</subject><subject>Mathematics</subject><subject>Mathematics and Statistics</subject><subject>Nuclei (cytology)</subject><subject>Probability</subject><subject>Quality Control</subject><subject>Reliability</subject><subject>Safety and Risk</subject><subject>Statistics</subject><subject>Statistics for Business</subject><subject>Tessellation</subject><subject>Windows (intervals)</subject><issn>1386-1999</issn><issn>1572-915X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kEFLwzAYhosoOKd_wFPAk4fql6RJk-MY6gaDHazgLaRpumXUZiad4L83s6I3T_n4eJ6XfG-WXWO4wwDlfcTARZkDljkAZTyHk2yCWUlyidnraZqp4DmWUp5nFzHuIEmYs0m2rrYWdTpsbByQD40NKA56cHFwJqLWBzQkwPVBN-4Q04B0j1z0Q_B7Z9BztazQYGO0XZcs319mZ63uor36eafZy-NDNV_kq_XTcj5b5YbKcshrbiXWAjBthRCFJSAZaYUUbW1kUTc6LZmmwhCOTdEUheBGAC0YIw2vraHT7HbM3epO7YN70-FTee3UYrZSxx0QLGSK_cCJvRnZffDvh3So2vlD6NP3FCGcABBBSKLISJngYwy2_Y3FoI4lq7FklUpW3yUrSBIdpZjgfmPDX_Q_1hdLOH3f</recordid><startdate>20191201</startdate><enddate>20191201</enddate><creator>Chenavier, Nicolas</creator><creator>Nagel, Werner</creator><general>Springer US</general><general>Springer Nature B.V</general><general>Springer Verlag (Germany)</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88I</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>FYUFA</scope><scope>F~G</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H8D</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>L.-</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0C</scope><scope>M2P</scope><scope>M7S</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYYUZ</scope><scope>Q9U</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0001-7680-4361</orcidid></search><sort><creationdate>20191201</creationdate><title>The largest order statistics for the inradius in an isotropic STIT tessellation</title><author>Chenavier, Nicolas ; 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t
> 0 is observed in the window
W
ρ
=
t
−
1
π
ρ
⋅
[
−
1
2
,
1
2
]
2
, for
ρ
> 0. With each cell of the tessellation, we associate the inradius, which is the radius of the largest disk contained in the cell. Using the Chen-Stein method, we compute the limit distributions of the largest order statistics for the inradii of all cells whose nuclei are contained in
W
ρ
as
ρ
goes to infinity.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s10687-019-00356-0</doi><tpages>28</tpages><orcidid>https://orcid.org/0000-0001-7680-4361</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1386-1999 |
| ispartof | Extremes (Boston), 2019-12, Vol.22 (4), p.571-598 |
| issn | 1386-1999 1572-915X |
| language | eng |
| recordid | cdi_hal_primary_oai_HAL_hal_02189209v1 |
| source | EBSCOhost Business Source Complete; SpringerLink Journals - AutoHoldings |
| subjects | Civil Engineering Economics Environmental Management Finance Hydrogeology Insurance Management Mathematics Mathematics and Statistics Nuclei (cytology) Probability Quality Control Reliability Safety and Risk Statistics Statistics for Business Tessellation Windows (intervals) |
| title | The largest order statistics for the inradius in an isotropic STIT tessellation |
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