Chimera - regular vines MATLAB (4 to 7 nodes)
doi: 10.4121/21184552
CC0Vine copulas have become the standard tool for modelling complex probabilistic dependence. It has been shown that the
number of regular vines grows extremely quickly with the number of nodes. Chimera is the first attempt to map the vast space of
regular vines. No dataset containing all regular vines is available. The atlas of regular vines, Chimera, comprises all 24 4×4 matrices representing regular vines
on 4 nodes, 480 5×5 matrices representing regular vines on 5 nodes, 23,040 6×6 matrices representing regular vines on 6
nodes, 2,580,480 7×7 matrices representing regular vines on 7 nodes and 660,602,880 8×8 matrices representing regular
vines on 8 nodes. Regular vines in Chimera are classified according to their tree-equivalence class. All regular vines were fitted to synthetic data to demonstrate the potential of Chimera. It provides thus a tool for researchers to navigate this vast space in an orderly fashion.
This dataset contain vine matrices in for matlab
- 2023-04-28 first online, published, posted
DATA
- 1,262 bytesMD5:
0fea426c98d4fc0f355f2a28d6b934e9README.md - 433 bytesMD5:
f7499e95af3490167a73db60eea1074bsubmats_4_T4Matlab.mat - 414 bytesMD5:
befc8e86b5e8ef15090570b2ba757ab1submats_4_T5Matlab.mat - 1,277 bytesMD5:
7f625035b03d7682f1151e7c722f15ccsubmats_5_T6Matlab.mat - 4,599 bytesMD5:
9ac30c91c5436009476b087d6b570230submats_5_T7Matlab.mat - 1,848 bytesMD5:
f75d960e8d90dd1a35e77fe5510e8e9esubmats_5_T8Matlab.mat - 42,267 bytesMD5:
7d71fcc1ebd97334884bb6dc731ac9cfsubmats_6_T10Matlab.mat - 62,360 bytesMD5:
14c786f0c101c74f98e7becf511c88a1submats_6_T11Matlab.mat - 62,573 bytesMD5:
1c13a08cbcb53c8f8aef34d26226e0d8submats_6_T12Matlab.mat - 133,506 bytesMD5:
4c5a10626bf9b3e86dad01c2cdb5e40csubmats_6_T13Matlab.mat - 42,002 bytesMD5:
4ce41e38b2972e15f890cca158bd939esubmats_6_T14Matlab.mat - 7,407 bytesMD5:
364c70048c7ee3e7c66ae2749e952708submats_6_T9Matlab.mat - 62,081 bytesMD5:
43e9dbad2089a6ae2c7f511cfa6ef660submats_7_T15Matlab.mat - 408,437 bytesMD5:
d83f99b8d850565068079c6002682391submats_7_T16Matlab.mat - 1,684,775 bytesMD5:
e09124ee7b7c6832a10e8e094e50fc3asubmats_7_T17Matlab.mat - 457,339 bytesMD5:
9b1451869329b511f0d90c6b8ed76d19submats_7_T18Matlab.mat - 811,477 bytesMD5:
b15d4ad9217a07e34af5b9af2014d880submats_7_T19Matlab.mat - 6,885,085 bytesMD5:
43f0700b998b228f4303f8797018fcbcsubmats_7_T20Matlab.mat - 2,250,774 bytesMD5:
c43d0a6ed47bdb191fc6d2292d07dee6submats_7_T21Matlab.mat - 6,871,064 bytesMD5:
7b160adc94d1d8ac44564fbdaaea4c62submats_7_T22Matlab.mat - 9,717,978 bytesMD5:
f55ff08eeeaac2289b182d18eef810f5submats_7_T23Matlab.mat - 9,781,613 bytesMD5:
f51076a9102a368b8b4831468edfe5d7submats_7_T24Matlab.mat - 2,537,781 bytesMD5:
b73c5e085d0d719bf3207322694954ccsubmats_7_T25Matlab.mat -
download all files (zip)
41,828,352 bytes unzipped
