184 citations as recorded by crossref.

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14. Modeling and application of industrial process fault detection based on pruning vine copula J. Wan & S. Li 10.1016/j.chemolab.2018.11.005
15. Assessing the hydrodynamic boundary conditions for risk analyses in coastal areas: a multivariate statistical approach based on Copula functions T. Wahl et al. 10.5194/nhess-12-495-2012
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22. Monitoring Test for Stability of Dependence Structure in Multivariate Data Based on Copula J. Lee & B. Kim 10.3390/e18120457
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30. A new scheme for multivariate, multisite weather generator with inter-variable, inter-site dependence and inter-annual variability based on empirical copula approach X. Li & V. Babovic 10.1007/s00382-018-4249-5
31. A mutual information based R-vine copula strategy to estimate VaR in high frequency stock market data C. Sharma et al. 10.1371/journal.pone.0253307
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33. Holocene climate variability in the Levant from the Dead Sea pollen record T. Litt et al. 10.1016/j.quascirev.2012.06.012
34. Idealized models of the joint probability distribution of wind speeds A. Monahan 10.5194/npg-25-335-2018
35. An Upper Limit to Youth Psychotherapy Benefit? A Meta-Analytic Copula Approach to Psychotherapy Outcomes P. Jones et al. 10.1177/2167702619858424
36. Is southwestern China experiencing more frequent precipitation extremes? M. Liu et al. 10.1088/1748-9326/9/6/064002
37. Quantifying the joint distribution of drought indicators in Borneo fire-prone area M. Najib et al. 10.1088/1755-1315/880/1/012002
38. Copula-based approximation of particle breakage as link between DEM and PBM A. Spettl et al. 10.1016/j.compchemeng.2017.01.023
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43. A pathway for multivariate analysis of ecological communities using copulas M. Anderson et al. 10.1002/ece3.4948
44. Evaluation of the ability of regional climate models and a statistical model to represent the spatial characteristics of extreme precipitation L. Yang et al. 10.1002/joc.6602
45. Seasonal copula models for the analysis of glacier discharge at King George Island, Antarctica M. Gómez et al. 10.1007/s00477-016-1217-7
46. Probabilistic spatial prediction of categorical data using elliptical copulas X. Huang & Z. Wang 10.1007/s00477-017-1485-x
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48. Projecting changes in regional temperature and precipitation extremes in the United States J. Schoof & S. Robeson 10.1016/j.wace.2015.09.004
49. Multivariate bias adjustment of high-dimensional climate simulations: the Rank Resampling for Distributions and Dependences (R2D2) bias correction M. Vrac 10.5194/hess-22-3175-2018
50. Joint probability risk modelling of storm surge and cyclone wind along the coast of Bay of Bengal using a statistical copula N. Bushra et al. 10.1002/joc.6068
51. An Examination of Tail Dependence in Bordeaux Futures Prices and Parker Ratings D. Cyr et al. 10.1017/jwe.2017.18
52. Joint probability-based classifier based on vine copula method for land use classification of multispectral remote sensing data Y. Zhang et al. 10.1007/s12145-020-00487-0
53. Evaluating the effects of climate extremes on crop yield, production and price using multivariate distributions: A new copula application F. Alidoost et al. 10.1016/j.wace.2019.100227
54. Minimum temperature mapping with spatial copula interpolation P. Bostan et al. 10.1016/j.spasta.2020.100464
55. Stochastic Response Assessment of Cross-Sea Bridges under Correlated Wind and Waves via Machine Learning C. Fang et al. 10.1061/(ASCE)BE.1943-5592.0001554
56. Measured and modeled spatial rain rate correlation to improve the prediction method for satellite site diversity T. Tjelta et al. 10.1002/2014RS005476
57. Vulnerability of hop‐yields due to compound drought and heat events over European key‐hop regions V. Potopová et al. 10.1002/joc.6836
58. Copula-based stochastic uncertainty analysis of satellite precipitation products E. Sharifi et al. 10.1016/j.jhydrol.2019.01.035
59. Climate derivatives strategies as an alternative to set up guaranteed prices for agricultural producers in México S. Cruz-Aké et al. 10.1080/13504851.2021.1985061
60. A Similarity-Based Implementation of the Schaake Shuffle R. Schefzik 10.1175/MWR-D-15-0227.1
61. Design Flood Volume of the Three Gorges Dam Project D. Liu et al. 10.1061/(ASCE)HE.1943-5584.0000287
62. Bayesian sequential design for Copula models S. Senarathne et al. 10.1007/s11749-019-00661-7
63. Assessing Hydrologic Uncertainty Processor Performance for Flood Forecasting in a Semiurban Watershed S. Han et al. 10.1061/(ASCE)HE.1943-5584.0001828
64. Investigation of multivariate pairs trading under copula approach with mixture distribution F. He et al. 10.1016/j.amc.2024.128635
65. The distribution of Kendall's tau for testing the significance of cross-correlation in persistent data K. Hamed 10.1080/02626667.2011.586948
66. Ensemble Model Output Statistics for Wind Vectors N. Schuhen et al. 10.1175/MWR-D-12-00028.1
67. Analysis of extreme precipitation characteristics in low mountain areas based on three-dimensional copulas—taking Kuandian County as an example C. Wang et al. 10.1007/s00704-015-1692-7
68. Interdependence between temperature and precipitation: modeling using copula method toward climate protection B. Hussain et al. 10.1007/s40808-021-01256-8
69. Joint Modeling of Precipitation and Temperature Using Copula Theory for Current and Future Prediction under Climate Change Scenarios in Arid Lands (Case Study, Kerman Province, Iran) T. Mesbahzadeh et al. 10.1155/2019/6848049
70. A physiographic approach to downscaling fractional snow cover data in mountainous regions R. Walters et al. 10.1016/j.rse.2014.07.001
71. A new method for wind speed forecasting based on copula theory Y. Wang et al. 10.1016/j.envres.2017.09.034
72. Climate change‐induced impacts on urban flood risk influenced by concurrent hazards A. Pedersen et al. 10.1111/j.1753-318X.2012.01139.x
73. Spatial extreme modeling using student t copula approach in Ngawi Regency M. Fauziyah et al. 10.1088/1742-6596/1538/1/012051
74. Developing an earthquake model based on simultaneous peak ground acceleration occurrences using the D-vine copula approach A. Ahdika et al. 10.1007/s40808-023-01846-8
75. Heterogeneous spatiotemporal copula‐based kriging for air pollution prediction J. Wang et al. 10.1111/tgis.12823
76. Selecting and estimating regular vine copulae and application to financial returns J. Dißmann et al. 10.1016/j.csda.2012.08.010
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78. Analysis of Reserves in Multiple Life Insurance using Copula I. Lee et al. 10.5351/CSAM.2014.21.1.023
79. Entropy–Copula in Hydrology and Climatology A. AghaKouchak 10.1175/JHM-D-13-0207.1
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83. A method for preferential selection of dates in the Schaake shuffle approach to constructing spatiotemporal forecast fields of temperature and precipitation M. Scheuerer et al. 10.1002/2016WR020133
84. Statistical modelling of extreme storms using copulas: A comparison study F. Li et al. 10.1016/j.coastaleng.2018.09.007
85. Decentralized monitoring for large‐scale process using copula‐correlation analysis and Bayesian inference–based multiblock principal component analysis Y. Tian et al. 10.1002/cem.3158
86. Construction of combined drought index based on bivariate joint distribution Y. Li et al. 10.1016/j.aej.2021.01.006
87. Using Vine Copulas to Generate Representative System States for Machine Learning I. Konstantelos et al. 10.1109/TPWRS.2018.2859367
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89. Functional Enrichment of Utopian Distribution of Plant Life-Forms J. Furze et al. 10.4236/ajps.2013.412A1006
90. Impact of bias nonstationarity on the performance of uni- and multivariate bias-adjusting methods: a case study on data from Uccle, Belgium J. Van de Velde et al. 10.5194/hess-26-2319-2022
91. Dynamic Copula Processes A. Galli et al. 10.2139/ssrn.1616503
92. Mixture of D-vine copulas for modeling dependence D. Kim et al. 10.1016/j.csda.2013.02.018
93. Virtual Storage-Based Model for Estimation of Economic Benefits of Electric Vehicles in Renewable Portfolios J. Vasilj et al. 10.3390/en13092315
94. Evaluating the Dependence between Temperature and Precipitation to Better Estimate the Risks of Concurrent Extreme Weather Events H. Wazneh et al. 10.1155/2020/8763631
95. Joint statistical models for significant wave height and wave period in a changing climate E. Vanem 10.1016/j.marstruc.2016.06.001
96. Multisite and multivariable statistical downscaling using a Gaussian copula quantile regression model M. Ben Alaya et al. 10.1007/s00382-015-2908-3
97. Nonlinear time series analysis of palaeoclimate proxy records N. Marwan et al. 10.1016/j.quascirev.2021.107245
98. Multivariate probabilistic forecasting using ensemble Bayesian model averaging and copulas A. Möller et al. 10.1002/qj.2009
99. Parametric models for distributions when interest is in extremes with an application to daily temperature M. Stein 10.1007/s10687-020-00378-z
100. Conditional simulation of remotely sensed rainfall data using a non-Gaussian v-transformed copula A. AghaKouchak et al. 10.1016/j.advwatres.2010.02.010
101. Assessing probabilistic wind load effects via a multivariate extreme wind speed model: A unified framework to consider directionality and uncertainty X. Zhang & X. Chen 10.1016/j.jweia.2015.09.002
102. Probabilistic Gaussian Copula Regression Model for Multisite and Multivariable Downscaling M. Ben Alaya et al. 10.1175/JCLI-D-13-00333.1
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105. Mixture of D-Vine copulas for chemical process monitoring W. Zheng et al. 10.1016/j.chemolab.2017.08.002
106. Generating Nonnormal Multivariate Data Using Copulas: Applications to SEM P. Mair et al. 10.1080/00273171.2012.692629
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114. Compound summer temperature and precipitation extremes over central Europe K. Sedlmeier et al. 10.1007/s00704-017-2061-5
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126. How well do regional climate models simulate the spatial dependence of precipitation? An application of pair‐copula constructions I. Hobæk Haff et al. 10.1002/2014JD022748
127. Flexible Lévy-Based Models for Time Series of Count Data with Zero-Inflation, Overdispersion, and Heavy Tails C. Kollie et al. 10.1155/2023/1780404
128. Speech signal modeling using multivariate distributions A. Aroudi et al. 10.1186/s13636-015-0078-1
129. Emulator For Eroded Beach And Dune Profiles Due To Storms A. Gharagozlou et al. 10.1029/2022JF006620
130. Analysis of the Parametric Correlation in Mathematical Modeling of In Vitro Glioblastoma Evolution Using Copulas J. Ayensa-Jiménez et al. 10.3390/math9010027
131. Multivariate ensemble Model Output Statistics using empirical copulas D. Wilks 10.1002/qj.2414
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146. The use of copula functions for predictive analysis of correlations between extreme storm tides K. Domino et al. 10.1016/j.physa.2014.07.020
147. Bivariate return periods of temperature and precipitation explain a large fraction of European crop yields J. Zscheischler et al. 10.5194/bg-14-3309-2017
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153. Copula-based joint distribution analysis of the ENSO effect on the drought indicators over Borneo fire-prone areas M. Najib et al. 10.1007/s40808-021-01267-5
154. Managing soil natural capital: An effective strategy for mitigating future agricultural risks? R. Cong et al. 10.1016/j.agsy.2014.05.003
155. Joint distribution of temperature and precipitation in the Mediterranean, using the Copula method G. Lazoglou & C. Anagnostopoulou 10.1007/s00704-018-2447-z
156. Accounting for correlational structures in stochastic comparative life cycle assessments through copula modeling R. Gil et al. 10.1007/s11367-020-01859-w
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158. Integrating Entropy and Copula Theories for Hydrologic Modeling and Analysis Z. Hao & V. Singh 10.3390/e17042253
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160. Making the Output of Seasonal Climate Models More Palatable to Agriculture: A Copula-Based Postprocessing Method M. Li et al. 10.1175/JAMC-D-19-0093.1
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