Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Ulf Schepsmeier"'
Publikováno v:
Journal of Statistical Software, Vol 52, Iss 3 (2013)
Flexible multivariate distributions are needed in many areas. The popular multivariate Gaussian distribution is however very restrictive and cannot account for features like asymmetry and heavy tails. Therefore dependence modeling using copulas is no
Externí odkaz:
https://doaj.org/article/7114213032e0489899a2cb3fa3514cb8
Publikováno v:
Econometric Reviews. 38:1024-1054
We propose a family of goodness-of-fit tests for copulas. The tests use generalizations of the information matrix (IM) equality of White and so relate to the copula test proposed by Huang and Prokh...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a953d4ff0d69de22cf86fc3127a10c3b
https://doi.org/10.1080/07474938.2018.1514023
https://doi.org/10.1080/07474938.2018.1514023
Autor:
Ulf Schepsmeier
Publikováno v:
Econometric Reviews. 38:25-46
We introduce a new goodness-of-fit test for regular vine (R-vine) copula models. R-vine copulas are a very flexible class of multivariate copulas based on a pair-copula construction (PCC). The test arises from the information matrix equality and spec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::28a04b3390ff07224e0c34aefeb58ba6
https://doi.org/10.1080/07474938.2016.1222231
https://doi.org/10.1080/07474938.2016.1222231
Autor:
Ulf Schepsmeier, Claudia Czado
Publikováno v:
Journal of the Royal Statistical Society Series C: Applied Statistics. 65:415-429
Summary The analysis of car crash output parameters such as firewall intrusion points assist the overall engineering process. Such data are nowadays collected from many numerical simulations and it is not possible for the engineer to analyse this gro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e34d052c6ddeff24886b7794886bdd11
https://doi.org/10.1111/rssc.12125
https://doi.org/10.1111/rssc.12125
Autor:
Ulf Schepsmeier
Publikováno v:
Journal of Multivariate Analysis. 138:34-52
We introduce a new goodness-of-fit test for regular vine (R-vine) copula models, a flexible class of multivariate copulas based on a pair-copula construction (PCC). The test arises from the information matrix ratio and assumes fixed margins. The corr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2e3e5fb9a7f40dca4a46c4d0afe6a0f2
https://doi.org/10.1016/j.jmva.2015.01.001
https://doi.org/10.1016/j.jmva.2015.01.001
Publikováno v:
Journal of Multivariate Analysis. 138:74-88
We present a vine copula based composite likelihood approach to model spatial dependencies, which allows to perform prediction at arbitrary locations. This approach combines established methods to model (spatial) dependencies. On the one hand the geo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::792c65882fd71688e98a113b701d0224
https://doi.org/10.1016/j.jmva.2015.01.021
https://doi.org/10.1016/j.jmva.2015.01.021
Publikováno v:
Biometrics. 71:323-332
We introduce an extension of R-vine copula models for the purpose of spatial dependency modeling and model based prediction at unobserved locations. The newly derived spatial R-vine model combines the exibility of vine copulas with the classical geos
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fa3eb91cd408816ed2e46b5c8a3760f0
https://doi.org/10.1111/biom.12279
https://doi.org/10.1111/biom.12279
Autor:
Ulf Schepsmeier, Jakob Stöber
Publikováno v:
Computational Statistics. 28:2679-2707
We describe a new algorithm for the computation of the score function and observed information in regular vine (R-vine) copula models. R-vine copulas are constructed hierarchically from bivariate copulas as building blocks only, and the algorithm exp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::224343dae874153d8a66dcee3b220897
https://doi.org/10.1007/s00180-013-0423-8
https://doi.org/10.1007/s00180-013-0423-8
Autor:
Jakob Stöber, Ulf Schepsmeier
Publikováno v:
Statistical Papers. 55:525-542
Data sets with complex relationships between random variables are increasingly studied in statistical applications. A popular approach to model their dependence is the use of copula functions. Our contribution is to derive expressions for the observe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99f9acfb2a8f0a244f47758b3a402a24
https://doi.org/10.1007/s00362-013-0498-x
https://doi.org/10.1007/s00362-013-0498-x
Publikováno v:
Biometrics. 71(2)
We introduce an extension of R-vine copula models to allow for spatial dependencies and model based prediction at unobserved locations. The proposed spatial R-vine model combines the flexibility of vine copulas with the classical geostatistical idea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::53e22becd500976dad019da1faef0aa2
https://pubmed.ncbi.nlm.nih.gov/25660495
https://pubmed.ncbi.nlm.nih.gov/25660495